Current Projects

Fall 2026 Projects

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Legend: 1 = Primary Discipline | 2 = Secondary Discipline | 3 = Optional Discipline(s)

Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
ARM Institute Native Mobile App for RoboticsCareer.org Zajac, Brian 0 0 0 2 0 0 0 0 0 1 0 0 0

Non-Disclosure Agreement: NO

Intellectual Property: YES

Physical Prototype or On-Campus Equipment: NO

Images and Additional Links (if provided)

The ARM Institute (Advanced Robotics for Manufacturing) is a public-private partnership headquartered in Pittsburgh, Pennsylvania, funded by the U.S. Department of Defense. Its mission is to strengthen American manufacturing through robotics, artificial intelligence, and workforce development. The ARM Institute's signature workforce program is RoboticsCareer.org, a federally funded national platform that connects job seekers, students, and transitioning workers with thousands of robotics jobs, internships, and vetted training programs — from high school STEM credentials to PhDs. Last year, over 100,000 individuals used the platform to explore careers and opportunities in robotics and physical AI manufacturing.

The platform is responsive and accessible on both desktop and mobile web browsers. However, based on user feedback, ARM is seeking to develop a native mobile app to deliver improved performance, a better user interface and experience, and greater engagement through features like push notifications. Due to the large scope of this project, it has been split into two serial parts. This Phase 1 project covers the full arc from discovery through a functional, testable prototype. Design decisions and early user feedback gathered in Phase 1 will directly shape the full development effort in Phase 2.

Students will begin by conducting market research to understand how comparable workforce and job-matching apps are designed, what features drive engagement, and who the primary user groups are. From this, they will define the app's core feature set and develop user personas that reflect the platform's diverse audience. Students will then translate these findings into wireframes and a high-fidelity interactive prototype aligned with Apple and Google platform design guidelines. The open design element of this project lies in the research and synthesis process: students have freedom to identify, compare, and justify the features, layouts, and engagement mechanisms that will best serve RoboticsCareer.org users. From there, students will build a functional prototype, implementing the core user flows connected to mocked or limited live data, sufficient for internal use and a closed beta with real users. Feedback gathered from that beta will be documented and packaged as a direct input to the Phase 2 development team. The project concludes with four deliverables: a market research and competitive analysis report, a defined feature set with supporting user personas, a high-fidelity interactive prototype ready for stakeholder review, a functional beta app suitable for closed internal testing, a structured beta feedback report, and a backend requirements document that the ARM development team can use to prepare the server-side infrastructure for Phase 2.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
B Braun Medical Inc Heat Shrink Tubing Manogharan,Guhaprasanna 2 0 0 0 0 0 3 0 0 0 0 1 0

Non-Disclosure Agreement: YES

Intellectual Property: YES

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

The objective of this project is to develop and evaluate a heat-shrink tubing assembly process that improves the reliability, pull strength, and leak resistance of tube-to-tube and tube-to-rigid body connections. The project will include the design of an assembly fixture capable of controlling critical process parameters, including temperature, exposure time, and rotation; 3D-printed couplers (initial geometry and material specified by B Braun); and the execution of a design of experiments to assess the impact of shrink-tubing assembly variables on joint integrity. Project success will be defined by demonstrated improvements in assembly consistency, supporting inspection data, and practical process enhancements that support manufacturing efficiency and overall product quality.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
Cardinal Systems, Inc. Evaluate the feasibility of automating portions of our manufacturing process through robotic automation. Zajac, Brian 0 0 0 3 0 0 0 0 0 1 0 2 0

Non-Disclosure Agreement: NO

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

Company Background

Cardinal Systems Inc., celebrating their 50th year in business, is a Pennsylvania-based manufacturer of steel wall, vinyl-lined swimming pools. Our manufacturing operations include heavy gauge sheet metal forming and fabrication, extruded plastic products, thermoforming, packaging, and assembly.
As we continue to improve efficiency and remain competitive, we are exploring opportunities to incorporate advanced robotics into our manufacturing operations.

Summary

Cardinal Systems Inc. respectfully requests Penn State's consideration of a collaborative project to evaluate the feasibility of automating portions of our manufacturing process through robotic automation.

Our company currently owns four (4) Yaskawa GP180 industrial robots that were purchased for a previous automation project. Unfortunately, that project was never completed due to the vendors’ unexpected closure, leaving the robots unused but fully available for future applications.

Rather than investing immediately in system integration, Cardinal Systems seeks Penn State's assistance to conduct a comprehensive simulation, manufacturing assessment, and return-on-investment (ROI) analysis. The results of this study would provide the technical and financial information needed to determine whether a phased automation project is justified and to establish a roadmap for future implementation.

Project Objective

The purpose of this project is not to implement robotic automation immediately. Instead, we seek Penn State's engineering students’ assistance in evaluating how our existing robotic assets could be effectively integrated into our manufacturing processes.

Specifically, we are requesting a comprehensive engineering study that includes; Evaluation of current manufacturing operations, identification of processes suitable for robotic automation, digital simulation of proposed robotic work cells, process flow analysis, cycle-time modeling, throughput analysis, preliminary robotic cell layouts, identification of required tooling and peripheral equipment, capital cost estimates for implementation, return-on-investment (ROI) analysis, and phased implementation recommendations.

The completed study would provide Cardinal Systems with the information necessary to make informed decisions regarding future automation investments.

Conclusion

Cardinal Systems Inc. believes this project presents an excellent opportunity to combine Penn State's expertise in advanced manufacturing and industrial engineering with a practical application.

By evaluating the deployment of four existing Yaskawa GP180 robots through simulation and engineering analysis, Penn State can help us determine the technical and financial feasibility of robotic automation before implementation. The resulting study will provide a roadmap for modernization while minimizing investment risk and maximizing the value of existing assets.

We appreciate your consideration and welcome the opportunity to discuss this proposal further. We look forward to exploring how Penn State and Cardinal Systems can work together to advance manufacturing innovation in Pennsylvania.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
Carl Bromley (sole proprietor, inventor) Semi-Autonomous Pothole Patcher Lewis, Alfred 0 0 0 2 0 0 3 0 3 0 3 1 0

Non-Disclosure Agreement: NO

Intellectual Property: YES

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

In one recent year, the Commonwealth of Pennsylvania spent $93 million patching potholes with some needing a do-over one year later. The goal of this project is to provide the means of quickly removing loose debris from a pothole, gauging to near perfection the amount of material needed to fill the hole, filling the hole and compacting the patch material to a smooth drivable surface.

Deep potholes will be filled in layers with each layer no more than two inches thick and compacted separately to provide a good foundation for additional layers above it.

The final layer will be filled, leveled, and shaped prior to compacting so that its final configuration after rolling is flat and (ideally) bump-free.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
Cryo-EM Lab Portable High-Pressure Freezing System Pacey, Mark 1 0 0 0 0 0 3 0 0 0 3 2 0

Non-Disclosure Agreement: NO

Intellectual Property: YES

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

The objective of this project is to develop a portable, modular system for the immediate vitrification of biological tissues at the point of care. By targeting a <20-minute "ischemic window", this device ensures that samples for Cryo-Electron Tomography research are preserved in a near-native state, free from the ice crystal damage associated with atmospheric freezing. The design aims to eliminate bulky hydraulic systems, resulting in a compact, bedside-ready solution.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
Echogen Power Systems (DE), Inc. Active Thermocline Management in Packed-Bed Thermal Energy Storage Systems Lewis, Alfred 0 0 0 0 0 0 0 3 0 0 0 1 0

Non-Disclosure Agreement: NO

Intellectual Property: YES

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

Overview:

Thermal energy storage systems utilizing packed beds are increasingly being considered for utility-scale energy storage applications due to their low cost, scalability, and use of readily available materials. A key challenge in packed-bed thermal storage systems is the formation and degradation of the thermocline region that separates hot and cold sections of the storage media. As the thermocline widens due to flow maldistribution, mixing, thermal diffusion, and cyclic operation, the amount of usable stored energy decreases and overall system performance is reduced.

The objective of this project is to design, model, build, and test a laboratory-scale packed-bed thermal storage system using gravel or glass spheres as the storage medium and water as the heat transfer fluid. The team will characterize thermocline formation during charging and discharging operations, develop numerical and CFD models to predict system performance, and investigate passive and active control strategies to minimize thermocline growth and maximize usable thermal storage capacity.

The project will provide insight into the relationship between flow distribution, operating conditions, control strategies, and thermal stratification in packed-bed storage systems. The resulting models, test data, and design recommendations will support the development of future large-scale thermal energy storage technologies.

Project deliverables:
- Lab-scale system and instrumentation design package
- Test procedure and documentation
- Lab-scale test system
- Baseline experimental results
- CFD and/or reduced-order model development and validation against baseline results
- Thermocline mitigation study (literature review and recommendations for test)
- Thermocline mitigation test results and comparison to baseline
- Final report and documentation
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
Gabe Brown Family Beyond Eye-Gaze: Natural Speech Interfaces for Assistive Communication Pacey, Mark 1 0 0 3 0 0 2 0 0 0 0 3 0

Non-Disclosure Agreement: NO

Intellectual Property: YES

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

This project gives you the chance to help restore faster and more natural communication for Gabe, a Penn State College of Engineering alumnus who relies on an eye-gaze device after a traumatic brain injury. Instead of typing letter by letter with his eyes, your team will design a wearable silent speech interface that senses the residual movements of his face, jaw, and throat during attempted speech and converts them into spoken messages. The system is meant to complement his existing eye-gaze interface, which stays available for confirmation, correction, training labels, and reliable fallback communication.

On the hardware side, you will build a piezoelectric-first wearable using flexible PVDF films coupled to the skin at candidate sites including the underside of the chin, the temporomandibular joint, and the lateral throat, with a repeatable mounting system built from medical-grade tape, a soft patch, or an adjustable collar. A miniature inertial measurement unit will be integrated into the housing to capture head and jaw motion and help separate attempted speech from unrelated movement. You will evaluate three configurations: piezoelectric sensing alone, IMU sensing alone, and the two combined. One or two dry EMG channels may be retained as a comparison modality and added to the final wearable only if they measurably improve cross-day reliability or accuracy. A previous student team built a facial EMG system using MyoWare sensors and an Arduino Uno, and this project moves that work toward lighter, less obtrusive mechanical sensing.

On the software side, you will collect synchronized recordings during attempted speech, then train and compare lightweight personalized classifiers such as support vector machines, one-dimensional convolutional networks, and few shot or contrastive models suited to limited training data. Low confidence predictions should be rejected rather than spoken, and the existing eye-gaze system can supply confirmation and accurate training labels. Inference should run locally where practical to keep latency low and keep the user's data on the device.

The first target is a reliable personalized vocabulary of roughly 10 to 20 words, commands, or phrases selected by Gabe and his family, not open vocabulary speech reconstruction. Expected deliverables include a working real-time wearable prototype, clear system diagrams and code documentation, and evaluation data covering macro F1-score, false activation rate, decision latency, calibration and setup time, accuracy after the device is removed and replaced, and performance across multiple days. Design goals are at least 90% same-session accuracy and 80% cross-session accuracy on the personalized closed set. The work spans wearable sensor design, signal processing, applied machine learning, and embedded real-time inference, and it gives a fellow engineer a faster way to talk with his family and caregivers.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
GHK Consulting Computational Design of a Quieter Electric Outboard Motor Housing Banyay, Gregory 0 0 0 0 0 0 3 0 0 0 0 1 0

Non-Disclosure Agreement: NO

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: NO

Images and Additional Links (if provided)

PROPOSED CAPSTONE DESIGN PROJECT
Computational Design of a Quieter Electric Outboard Motor Housing

Torqeedo Deep Blue 50 RXL electric outboard (see manufacturer image)
Purpose and Scope
An electric outboard motor housing can radiate objectionable noise when vibration from the motor and drivetrain excites its structural modes. A team of four to six senior engineering students will design a quieter housing by developing and applying an integrated structural-acoustic computational procedure during one 15-week semester. AI programs will be made available for use in this project.
The principal design modification will be strategically placed concentrated masses that alter natural frequencies and mode shapes. The team will produce and evaluate a computational prototype rather than fabricate or acoustically test a physical housing. Stiffeners may be considered as an additional concept or recommended for future work.
Computational Approach
• Develop or adapt a finite-element model of a simplified electric outboard motor housing and calculate its natural frequencies and mode shapes using MATLAB-based FEM software.
• Transfer housing geometry, surface normals, modal frequencies, and surface-normal velocities to acoustic code supplied by the advisor.
• Calculate and rank the relative acoustic power radiated by approximately three to five normalized structural modes; absolute operating sound level will not be predicted unless a motor-force model is available.
• Conduct a structured parametric study of added-mass locations and values, repeating the structural and acoustic calculations for each candidate design. For this step, AI programs will be used in the optimization search.
• Select a preferred configuration that substantially reduces the dominant radiating mode without significantly increasing radiation from the other selected modes.
• Prepare a preliminary engineering design and financial justification based on added weight, sensitivity, manufacturability, implementation cost, and potential customer value.
Sponsor Support and Design Criteria
Students will use MATLAB-based finite-element analysis tools available through Penn State. The sponsor will provide the acoustic solver, initial models, example inputs, operating guidance, and regular design reviews. Student-developed intellectual property will be assigned to the sponsor. No nondisclosure agreement is requested.
Principal Deliverables
• Documented baseline FEM model, natural frequencies, mode-shape visualizations, and FEM-to-acoustic data-transfer procedure.
• Baseline acoustic-power results and ranking of approximately three to five selected structural modes.
• Parametric comparison of baseline and modified designs, including mode shapes, acoustic power, added mass, and sensitivity.
• Recommended preliminary housing design with engineering drawings or mass-location specifications and a financial/manufacturing assessment.
• Simulation models and data, final technical report, presentation, poster, and one-page summary; future-work recommendations may include stiffeners and experimental validation.

One-Semester Plan
Period Principal activity
Weeks 1-4 Software instruction; examples; baseline FEM model
Weeks 5-8 Baseline modes; FEM-to-acoustic transfer; initial radiation results
Weeks 9-12 Mode ranking; added-mass location and value study
Weeks 13-15 Design refinement, tradeoffs, final report and presentation
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
Goodwill Industries of North Central Pa, Inc. Sustainable Textile Market Development Zajac, Brian 0 0 0 0 0 0 0 0 0 1 2 0 0

Non-Disclosure Agreement: NO

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

Goodwill Industries of North Central Pennsylvania is a nonprofit organization headquartered in Falls Creek, PA, with a mission of meeting life challenges through opportunity, education, training, and work. The organization employs over 700 people across 15 Pennsylvania counties and is one of the state's largest recyclers, diverting more than five million pounds of donated goods from landfills each year.

Goodwill receives over 40,000 pounds of donated clothing every week. Items that do not meet the quality standard for resale in its retail stores are compressed into 1,000-pound bales and sold to a single buyer who ships the material in bulk to low-income countries overseas. This arrangement is financially marginal (the per-pound return is low) and Goodwill is concerned that the market could shrink or disappear, much like what has happened in plastics recycling. The organization is already piloting a more promising alternative: a partnership with a company that recycles donated clothing into new fabric and pays significantly more per pound. That program, however, accepts only certain materials and colors, and excludes items with buttons, logos, or other embellishments, limiting how much volume it can absorb.

The goal of this project is to identify, evaluate, and compare alternative end-use markets for Goodwill's non-resalable clothing stream, with particular interest in options that handle cotton and impose fewer material restrictions. Students will begin by characterizing the incoming clothing stream (analyzing it by material type, color, contamination rate, and embellishment presence) to establish volume and composition data. They will then research the landscape of textile recycling, upcycling, industrial reuse, and other sustainable outlets, and engage directly with potential partners and vendors to verify both the technical and commercial feasibility of each option. For each viable alternative, students will map the process changes Goodwill would need to make in sorting, baling, or logistics, and estimate the operational cost of those changes. Students are expected to surface opportunities Goodwill may not be aware of and build a data-supported case for the best path forward. Final deliverables include a material flow characterization of the incoming stream, a quantitative comparison table across finalist markets (covering volume capacity, revenue per pound, material restrictions, and logistics costs), a recommended strategy with supporting justification, and an implementation roadmap for Goodwill to act on the findings.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
Gordon Food Service, Inc. Maximizing Storage Capacity and Pick Rate in a Distribution Center Through Rack Reconfiguration and Slotting Optimization Zajac, Brian 0 0 0 0 0 0 0 0 0 1 0 2 0

Non-Disclosure Agreement: YES

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

Gordon Food Service is a family owned food distribution company founded in 1897 and headquartered in Grand Rapids, Michigan. It is the largest family operated broadline food distributor in North America, delivering fresh, frozen, and dry food products and related supplies to restaurants, healthcare facilities, schools, and other foodservice operations across the United States and Canada, and it also operates a chain of retail stores that are open to the public. Its distribution centers move high volumes of temperature controlled product every day, which makes efficient use of storage space and labor essential to the operation.

This project focuses on increasing the effective storage and throughput capacity of the freezer zone of an existing Gordon Food Service distribution center. During seasonal peaks the facility experiences high slot occupancy while cubic utilization across the rack system remains substantially lower. This gap suggests that the current rack configuration, including bay heights and slot sizes, is not well aligned with the product profiles moving through the building.

The operational consequences are significant. Inbound product that does not fit its assigned location must be down stacked, which creates uneven cube on some of the pallets. Inbound product that arrives with less than maximum reserve cube leads to uneven utilization of reserve storage and increased travel for put away and replenishment. The site does use a slotting tool to model alternative configurations, but the process relies on manual trial and error and its effectiveness is limited by incomplete vendor pallet shipping data.

The student team will analyze the current state and design a comprehensive rack and slotting configuration that improves cubic utilization and material handling efficiency in the freezer reserve area. The scope includes building models to compare inbound pallet profiles against slot sizes and optimizing reserve and pick placement. All recommendations must be practical to implement within a live operational environment and must align with the long range growth plan for the site.

The team is expected to produce five deliverables. The first is a current state analysis and alignment model that examines freezer storage utilization, compares slot occupancy against cubic utilization, and analyzes how incoming products compare to available reserve slot sizes while taking pick location size into account, using both historical data and future forecasts to identify alignment gaps. The second is a rack configuration and reserve height proposal that determines the optimal rack height for storing freezer reserve pallets, presented as a set of full and partial re racking options with layout drawings and an estimate of the efficiency and capacity gained. The third is a data driven slotting methodology for the freezer that minimizes travel time for selectors without creating material handling inefficiencies, including a module selection slotting strategy that determines the most efficient front to back placement. The fourth is a projected impact analysis that uses simulation to show the impact on storage capacity, reserve utilization, material handling, and selection. The fifth is a written report and a presentation suitable for review by operations leadership.

The team will work directly with operations and engineering leadership during site visits and will have access to facility layouts, operating data, and outputs from the existing slotting tool. Baseline performance data will be shared with the assigned team at the kickoff meeting.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
Hatch Associates Consultants, Inc. Effective solutions for slurries in piping systems in a corrosive environment Lewis, Alfred 0 0 0 0 0 0 0 0 0 0 2 1 0

Non-Disclosure Agreement: NO

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

A mineral processing facility requires the design of piping systems associated with two 600 HP cyclone feed pumps located downstream of a SAG mill. The scope includes approximately 100 ft of 18-inch cyclone feed slurry piping with pump changeover isolation valves, 100 ft of 20-inch process water piping with isolation and control valves, and 300 ft of 6-inch and smaller gland water and utility piping.

The process water is recirculated throughout the plant and contains approximately 1,500 mg/L chlorides and trace hydrocarbon flotation reagents. Operating temperatures range from 80°F to 140°F. The process water is also the carrier fluid for the cyclone feed slurry; therefore, the slurry piping and valves are exposed to both abrasive wear from solids and corrosive attack from the circulating process water.

Students shall evaluate and recommend pipe materials, fitting types, valve types, materials of construction, linings/coatings, and end connections for each service. Multiple alternatives shall be compared considering abrasion resistance, corrosion resistance, availability, delivery time, constructability, maintenance requirements, and lifecycle cost.

The final recommendation should provide a practical and defensible design basis that maximizes plant availability while maintaining an appropriate balance between performance, maintainability, and cost.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
Honda Research Institute Agents on a Wire Choi, Kyusun 0 0 1 2 0 0 3 0 0 0 0 0 0

Non-Disclosure Agreement: NO

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

Most AI agent research runs in the cloud where computing power is effectively unlimited. Real robots and drones do not have that luxury. This project challenges students to take an existing embedded platform, such as a small drone or single-board computer, and deploy an AI agent that runs entirely on the device itself. Students will then design the architecture and collaboration behaviors that allow two or more of these systems to coordinate on a shared task while operating under tight compute, power, and connectivity constraints. Along the way, students will gain hands-on experience with on-device inference, runtime design, multi-agent coordination protocols including task allocation and messaging, behavior architectures, and building robustness into systems that must operate with intermittent or low-bandwidth communication.

Deliverables include an embedded or drone platform running an on-device agent, a collaboration architecture specification and implementation for at least two coordinating units, a live demonstration of a coordinated multi-unit task, and a written analysis of the compute, power, and communication trade-offs encountered during development.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
HumaniCore Ai, LLC EU Regulatory Compliance Module for Independent AI Audit Software Verbanac, Alan 0 0 0 1 0 0 0 0 0 2 0 0 0

Non-Disclosure Agreement: YES

Intellectual Property: YES

Physical Prototype or On-Campus Equipment: NO

Images and Additional Links (if provided)

HumaniCore AI provides independent third-party certification of AI enabled people decisions across the full employment lifecycle, covering both the vendors that build AI enabled people decision tools and the enterprises that deploy them. The European Union has enacted the most significant AI regulation in the world, and this project extends the company audit capability to the European market.
Transparency obligations under Article 50 of the EU AI Act apply from August 2, 2026, and obligations for high-risk AI systems used in employment decisions apply on a schedule running to December 2, 2027 under recently adopted amendments. The student team will study the amended EU AI Act and related European law, translate the employment obligations into a structured requirements matrix, develop the European Union regulatory requirements package in the format specified by the sponsor, develop a European protected grounds reference standard, design an audit report template aligned to European documentation requirements, and generate a fully synthetic European test dataset to exercise the work end to end. No real personal data is used at any point in the project.
Deliverables include the requirements matrix, the European Union regulatory requirements package, the protected grounds reference standard, the report template with sample output, the synthetic dataset with test harness, and a documented handoff package prepared for review by the sponsor's senior engineering team, which includes a first author IEEE published machine learning engineer.
Students will gain experience translating enacted regulation into testable software requirements, applying professional software engineering practices including versioning, citation traceability, and test discipline, and delivering professional engineering work to a live venture at the intersection of artificial intelligence, employment law, and governance.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
Idaho National Laboratory Project Zidane: Developing a Threat Informed MISP Capability for Deployable Microreactor Programs Verbanac, Alan 0 0 0 1 0 0 0 3 0 0 0 2 0

Non-Disclosure Agreement: NO

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: NO

Images and Additional Links (if provided)

Project Zidane focuses on developing a prototype cyber threat intelligence capability for a transportable microreactor program. The project is inspired by publicly available concepts associated with advanced and transportable nuclear energy systems but does not represent any actual reactor, facility, organization, system architecture, or security posture.

Over the course of the project we will examin how microreactor programs might receive cybersecurity information from government agencies, technology vendors, security researchers, and other public sources. Currently, this information is often broad, duplicative, inconsistently structured, and not written specifically for the nuclear sector. The student team will design a process for identifying which publicly reported cyber campaigns may be relevant to the mission, technologies, suppliers, operating environment, and supporting infrastructure of a transportable microreactor program.

Students will learn the fundamentals of cyber threat intelligence collection, source evaluation, campaign analysis, and intelligence reporting. They will use MITRE ATTACK to describe observed adversary tactics and techniques and will learn how to organize campaign information within the Malware Information Sharing Platform (MISP). Vulnerabilities may be included when they are relevant to a documented campaign, but the primary focus will be on evaluating adversary campaigns, behaviors, targeting patterns, and defensive implications.

The student team will select one or more defined areas of focus, such as supply chain compromise, remote access, engineering environments, operational technology, microgrid dependencies, ransomware, defense industry targeting, or advanced technology espionage. The team will develop criteria for determining whether a campaign is directly relevant, strongly analogous, generally instructive, or outside the scope of the fictional program.

The final prototype will demonstrate how publicly available threat information can be collected, evaluated, structured, enriched, and communicated to support defensive decision making. Automation will be limited to a manageable function that reduces analyst workload, such as identifying potentially relevant reports, importing structured data, enriching campaign records, identifying duplicate information, or generating an analyst review queue. Final relevance and confidence determinations will remain the responsibility of the analyst.

All research will use publicly available information. Students will not scan, test, access, or interact with operational systems, nuclear facilities, vendors, or other external organizations. Project Zidane is an academic scenario and all system descriptions, assumptions, and conclusions will be fictional.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
International Society of Service Innovation Professionals Exploring AI for Personalizing Multiple Choice Questions in the ISSIP Service Innovation Professional Certification Study Guide Zajac, Brian 0 0 0 2 0 0 0 0 0 1 0 0 0

Non-Disclosure Agreement: NO

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: NO

Images and Additional Links (if provided)

The International Society of Service Innovation Professionals (ISSIP) is a global nonprofit professional association founded in 2012 and headquartered in San Jose, California. With a community of over 2,000 individuals spanning more than 200 universities and 76 countries, ISSIP's mission is to advance service systems innovation to benefit people, business, and society. One of its professional development offerings being developed next is the Service Innovation Professional Certification, supported by a 100-question multiple choice study guide that prepares candidates for the credential.

The current study guide is a single, generalized resource that does not account for the diverse career trajectories of its users. A prospective candidate pursuing a career in industry faces meaningfully different priorities than one entering academia or government service, yet all three currently receive the same preparation material. The goal of this project is to leverage artificial intelligence to personalize the certification study experience based on learner career goals, improving relevance and ultimately the value of the credential for each user type.

Students will begin by analyzing the existing 100-question study guide to understand question content, difficulty, and thematic coverage. They will then research and evaluate AI-based personalization approaches, with freedom to identify, compare, and justify the methodology best suited to the task. Students are not directed toward a specific AI technique but are expected to evaluate the landscape of options and select an approach based on evidence. This work is well-suited for students with backgrounds in industrial engineering, particularly those with interest in human factors, decision modeling, and systems design, with computer science backgrounds a strong complement for the technical implementation work. The project concludes with two deliverables: three career-path-specific versions of the study guide personalized for industry, academic, and government career trajectories, and a comprehensive whitepaper documenting the problem, the importance of personalization in professional certification, the approaches considered, the methodology selected and justified, progress made, and recommended future directions for ISSIP to build on this work.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
JGM, Steel Fabricators and Constructors, LLC Breaking the Bottleneck: Capacity, Automation & Expansion Strategy for JGM Steel Zajac, Brian 0 0 0 0 0 0 0 0 0 1 0 2 0

Non-Disclosure Agreement: NO

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

JGM is a structural steel fabrication and erection company based in Coatesville, Pennsylvania, where roughly 60 shop employees fabricate, weld, and process structural steel for construction projects nationwide. The Coatesville plant currently runs five 10-hour shifts plus a Saturday shift and produces about 120,000 earned labor hours a year, and JGM wants to meaningfully grow output without proportionally growing its direct workforce. This capstone team will study the plant's current production process, from receiving raw steel through fabrication, welding, and shipping, to identify the biggest bottlenecks limiting throughput, and will evaluate opportunities to increase capacity through better process flow, material handling, and automated steel-processing equipment. By the end of the project, the team should deliver a documented current-state process and capacity assessment, a prioritized list of bottlenecks and improvement opportunities, and a future-state capacity model or set of recommendations showing how JGM could increase output. The findings will directly inform JGM's investment decisions and long-term growth plans for the Coatesville facility, and the team will present its results to JGM's executive leadership at the end of the semester.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
Lockheed Martin Aerospace Tufting Applicator and Visual Flow Mapping Mittan, Paul 0 0 3 2 0 0 3 0 3 0 0 1 0

Non-Disclosure Agreement: NO

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

Lockheed Martin’s cutting-edge flight-test and wind-tunnel programs rely on aerodynamic data to fine-tune vehicle performance and validate design simulations. For decades we’ve used tufting—hundreds of short strings taped to the airframe—to visualize surface flow. Because applying tufts and interpreting the video is labor-intensive, we’re teaming with Penn State to automate the whole process: a tuft applicator that loads tape and string, cuts, combines, and precisely applies the tufts on any aircraft surface, and an AI-driven visual-processing suite that defines optimal imaging parameters, detects each tuft, and uses image-recognition and surface-projection algorithms to instantly compute the local flow vector. This multidisciplinary project calls for students with strong mechanical, software, and computer-engineering skills to design the applicator hardware and build the computer-vision pipeline. The team will engage in hands-on prototyping, AI research, and have a direct impact on real aerospace testing. Join us to turn a tedious manual task into a rapid, automated system that delivers immediate, quantitative flow data for the next generation of fixed-wing and rotary-wing vehicles.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
Minitab, LLC Evaluating a Business Model for Retrofitting Autonomous Vehicles using Simul8 Zajac, Brian 0 0 0 0 0 0 0 0 0 1 0 0 0

Non-Disclosure Agreement: NO

Intellectual Property: YES

Physical Prototype or On-Campus Equipment: NO

Images and Additional Links (if provided)

Autonomous vehicles are often based on standard human-driven models, but they require additional sensing and computing hardware to operate. Installing this hardware on the main production line can be disruptive and costly. Instead, many autonomous vehicle manufacturers use a retrofitting approach where human-driven vehicles are produced on the main line, and the vehicle is later converted into an autonomous vehicle at a secondary facility.

An automotive SME were considering investing in a specialist vehicle-retrofitting facility and has appointed your team as engineering consultants to assess whether the proposed business model is operationally and financially viable.

The company will only proceed with the investment if the facility can generate more than $1 million in profit during its first six months of operation.


Customer Pricing Model

Customers will be charged:

- $3,000 when their vehicle is retrofitted and returned within 100 working hours

- $1,500 when the retrofit takes longer than 100 working hours

This pricing model means that the facility must balance customer demand, processing capacity, staffing, equipment utilisation and turnaround time to maximise profitability.

Details of the proposed facility layout, process flow, staffing levels and processing data are provided as part of this ask.


Your Challenge

Using Simul8, your team will:

1. Develop a simulation of the proposed retrofitting facility.

2. Evaluate the performance of the current operating model.

3. Identify bottlenecks, delays and underutilized resources.

4. Assess whether the facility can achieve the required profit target within six months.

5. Investigate alternative staffing, resource, layout or process-flow options.

6. Recommend a more efficient and profitable operating approach.

7. Present your findings and use the simulation to demonstrate the impact of your recommendations to the business stakeholders

Your final recommendation should clearly explain whether the proposed business is viable and what changes would be required to improve its operational performance and financial return.


This project is based on a real- world project that the Simul8 Consultants delivered and presented the outcome.

Note: This project is well suited to Industrial Engineers that have completed or are concurrently enrolled in IE 453 (Simulation Modeling for Decision Support) or have other prior experience with discrete event simulation.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
Montana State University (MilTech) 1 Reutilization of FRPA antennas to develop an adaptive GPS antenna solution. Cubanski, Dave 0 0 3 2 0 0 1 0 0 0 0 3 0

Non-Disclosure Agreement: YES

Intellectual Property: YES

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

The United States Marine Corps (USMC) is replacing Fixed Reception Pattern Antennas (FRPAs) with Controlled Reception Pattern Antennas (CRPAs). The goal of this project is to research, design, and prototype a solution to reutilize FRPA antennas to produce a solution that provides a higher level of jamming protection as well as possible direction finding (DF). This may be accomplished through the strategic placement of multiple FRPAs onto a platform. Solution may use platform body masking to decrease the jamming effects on the Position, Navigation, and Timing (PNT) solution through an adaptive Radio Frequency (RF) selection solution. This project will benefit the taxpayer and USMC by providing a significant cost savings through the reutilization of current USMC equipment.

Engineers needed for the project include:
i. RF Engineer
ii. Computer Science
iii. Mechanical Engineer

If you are a veteran, have a desire to work in a government lab, or want to be an engineer working to build technology that is needed by warfighters, then this is the Fall Capstone project for you! You will be working with a MilTech team of USMC and USA veterans, Montana State University engineers, and PSU engineers. Help us develop technology that supports Marines, saving lives and money!
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
Montana State University (MilTech) 2 Weather Report Analysis to Barometric Pressure Sensor Verbanac, Alan 0 0 0 1 0 0 0 0 0 0 0 0 0

Non-Disclosure Agreement: YES

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: NO

Images and Additional Links (if provided)

Are you a veteran, or want to support the Marines? If so, this may be the project for you! You are being asked to create a tool that will perform an assessment of weather reports for a specific region to determine the viability of Barometric sensor readings during a mission. Solution may also produce an expected barometric map for known points (Waypoints on Map). The solution would be utilizing existing COTS barometric sensor(s) and GPS receivers. The tool will correlate barometric sensor readings to a GPS location and combine these with weather readings that are then overlayed on an open source map.

This project will include discussions with Naval Information Warfare Center - Atlantic, MilTech (Montana State University) engineers, and a USMC program office to provide guidance throughout this project. If you are a veteran, have a desire to work in a government lab, or want to be an engineer working to build technology that is needed by warfighters, then this is the Fall Capstone project for you! You will be working with a MilTech team of USMC and USA veterans, Montana State University engineers, and PSU engineers. Help us develop technology that supports Marines, saving lives and money!
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
Naval Surface Warfare Center Dahlgren Division COTS Data Fusion Cubanski, Dave 0 0 2 3 0 0 1 0 0 0 0 0 0

Non-Disclosure Agreement: NO

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

Students should design, deploy, and test a network consisting of multiple (at least two) static or mobile sensing platforms equipped with one each of various sensors. These sensors will include, at minimum, a mmWave 80GHz radar and a visual camera. The sensing platforms must be capable of communicating with an additional coordination platform, which will combine the sensed data to perform data fusion. The coordination platform should be able to identify position, range, and identification of the target. This full system should be tested and demonstrated to work properly using multiple different targets at multiple ranges and positions. The group should demonstrate cases in which the system fails to accurately track or identify a target with only the individual sensors but can successfully identify when all sensors are used simultaneously in data fusion. This effort is expected to span two semesters, with the outcome from the first team being transferred to the second team for completion.

Deliverables:
? CLIN-1 - Market Survey and Feasibility Study
? CLIN-2 - System Design Document
? CLIN-3 - Engineering Drawing
? CLIN-4 - Test Plan
? CLIN-5 - Prototype
? CLIN-6 - Technical Report
? CLIN-7 - Final Poster
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
Nittany Motorsports 1 Manufacturing Method Selection for Formula SAE Bell Cranks Zajac, Brian 0 0 0 0 0 0 0 0 0 1 3 2 0

Non-Disclosure Agreement: NO

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

Penn State’s Formula SAE Electric team designs and builds a formula-style race car each year, relying on four bell cranks that transfer wheel loads through the suspension and define the car’s motion ratio and load-path behavior. The current bell cranks were produced using powder-bed fusion and machining at roughly $5,000 per part, a cost the team can no longer sustain. With these parts reaching the end of their service life, the team must identify a new manufacturing method and material combination that meets structural requirements while remaining feasible for a student organization with limited resources.

This project will establish the bell crank’s engineering requirements, survey viable manufacturing processes and materials, and compare leading options on performance, mass, cost, lead time, and manufacturability. Students will recommend a manufacturing route, produce a prototype, and validate its stiffness and structural soundness. Deliverables include a requirements specification, comparative study, process documentation, prototype test report, and a validation report appropriate to the chosen manufacturing method.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
Nittany Motorsports 2 PCB Vibration Tester for Formula SAE Vehicle Neal, Gary 0 0 0 0 0 0 3 0 0 2 0 1 0

Non-Disclosure Agreement: NO

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

PCBs in many applications, including in FSAE cars, are often subject to vibrations of varying frequencies and magnitudes. When the PCBs vibrate, the soldering on them can crack and lead to poor connections. This has happened repeatedly in the past to the battery management system PCBs on Nittany Motorsports. Because of the risk of failure, it is important to be able to verify that the solder joints will not crack under the vibration loads they typically experience before they are put into use. The goal of this project is to provide a way to perform this verification.

A PCB vibration tester and sufficient documentation to be able to remake it solely from the documentation. The tester should have a way to attach PCBs to it. It should be able to vibrate the PCB from 10Hz-2000Hz in accordance with ISO 16750-3. It should be able to vibrate the PCBs in three mutually perpendicular directions. Each direction may require the PCB to be mounted differently if needed, but it should be possible. It should be able to run for 2 hours without interruption. It should be able to vary the intensity and frequency of vibration. It should have a way to measure the vibrations that the PCB is seeing.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
Owens Corning Cutting and Fabrication Standards for EZSheath™ and FOAMULAR® Products Wang, Qian 0 0 0 0 0 0 0 0 0 2 0 1 0

Non-Disclosure Agreement: NO

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

The purpose of this project is to establish practical, evidence-based cutting and fabrication standards for EZSheath and FOAMULAR products that can be converted into a customer-facing guidance document for builders, OEMs, fabricators, distributors, and strategic partners. Builders and OEMs need clear recommendations that are specific enough to drive consistent outcomes but simple enough to use in the field. The student team will research, test, document, and recommend standards for cutting and fabricating EZSheath and FOAMULAR products.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
Partners in Food Solutions 1 Design of a rice blender Spencer, Maria 0 0 0 0 0 0 0 0 0 2 0 1 0

Non-Disclosure Agreement: NO

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

Partners in Food Solutions (PFS) is implementing a project to locally design and prototype a cost-effective rice blender for micro and small-scale rice mills in Nigeria, with a target fabrication cost of less than $ 3,000 and a blending capacity of 25–100 kg per batch. Building on the successful procurement and installation of four imported rice blenders across the country, each costing approximately $ 18,000, the project aims to develop and validate an affordable, locally manufactured prototype while strengthening Nigeria's capacity to fabricate rice blenders.
To achieve this objective, PFS is seeking technical support to design, prototype, and validate a rice blender that meets the required performance, quality, and affordability standards for micro and small-scale rice mills. The prototype should achieve a coefficient of variation (CV) of 15% or less to ensure uniform distribution of Fortified Rice Kernels (FRKs), while maintaining the grain quality by minimizing head rice breakage during the blending process.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
Partners in Food Solutions 2 Design of an avocado pomace dryer Spencer, Maria 0 0 0 0 0 0 2 0 0 3 3 1 0

Non-Disclosure Agreement: NO

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

Partners in Food Solutions is working with several avocado processors in Africa supporting them with Technical and Business advisory services. Several of these processors produce avocado oil. In production of avocado oil, there is generation of upwards of 90% pomace based on the raw material volume. This pomace includes, avocado skins, avocado seeds and the fresh that remains after the oil is extracted.

Many processors face the challenge of handling this wet pomace due to the bulkiness and perishability. PFS would like to explore the design of a dryer that could be scaled up to help the processors dehydrate the pomace efficiently and effectively to reduce the moisture to less than 10% so that it can be stored without spoilage and upcycled to other products.

The objective of this project will be to design a dryer that can dry 50 kg of the pomace at a time with the aim of assessing the technical and commercial viability of scaling this up to commercial scale.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
Partners in Food Solutions 3 Improvement of a flour batch-mixer Spencer, Maria 0 0 0 0 0 0 0 0 0 2 0 1 0

Non-Disclosure Agreement: NO

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

Partners in Food Solutions has, in the past, worked with some designers as well as fabrication workshops to produce a 50 kg batch mixer that is used by micro-millers to add powdered vitamins and minerals to corn flour. This equipment is now in use at over 150 milling sites across Kenya.

Though the mixer has, in general, achieved a good mixing efficiency, there are cases where the efficiency does not meet the standard. One of the observations that we have made is that at times some of the flour gets stuck to the sides of the drum and this could contribute to some parts of the batch having varying amounts of the vitamins and minerals. Another challenge that the operators have mentioned is that in some cases, the mixed flour does not freely discharge from the gate at the bottom of the mixer after the mixing cycle ends.

We would like to have the current design relooked into with the objective of improving on the current features to eliminate the issues described above. Once we get a prototype that is optimal, PFS can use it for future scale-up.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
Philips Ultrasound LLC Automated Chemical Compatibility Tester Cubanski, Dave 3 0 0 0 0 0 1 0 0 0 3 2 0

Non-Disclosure Agreement: YES

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

Background:
There is an ongoing shift toward stricter regulatory expectations requiring robust justification of lifetime compatibility for medical devices. To mitigate downstream regulatory risk, a more rigorous approach is needed to chemical compatibility testing. The current reliance on continuous soaking methods does not accurately reflect real clinical use conditions.
Goals:
1) Develop an automated testing system that closely mimics clinical use conditions The system should be capable of covering the entire exterior surface of the probe with the disinfectant.
2) The system should incorporate both spraying and drying processes and be capable of running for a defined number of test cycles. The system should control the number of cycles and keep track of the number of applied cycles.
3) Performing functional testing on the system and comparing the results against the currently used soaking method.
Scope:
Testing will focus on component-level patient-contacting materials. The test system only needs to replicate the disinfecting (not cleaning or rubbing etc.) process.
Material characterization is out of scope for this project.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
Pratt and Whitney Strain-stress behavior of metallic coating on a metallic substrate via XRD or other methods Kimel, Allen 0 0 0 0 0 0 0 0 0 0 1 2 0

Non-Disclosure Agreement: NO

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

The goal of the project is to evaluate the strain-stress behavior of metallic coating on a metallic substrate using in-situ 4-point bending set-up or other loading set-up in a XRD system. Other methods and approaches can be also evaluated.

Phase one: design the specimen relative to the loading cell. The specimen will be provided by PW and may have slight curvature. The metallic coating is up to 100um.

Phase two: design the measurement experiment in the XRD system. Define loading increments and measurement protocol.

Phase three: run measurements of 2-3 coupons with various compositions or microstructural changes. Assess measurement error, repeatability and changes in strain stress behavior coupon to coupon.

A reference to a similar work is https://link.springer.com/article/10.2478/s13531-011-0051-4
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
Proportion-Air Small Manual Precision Regulator Manogharan,Guhaprasanna 0 0 0 0 0 0 0 0 2 0 0 1 0

Non-Disclosure Agreement: YES

Intellectual Property: YES

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

1 Develop Prototype into market ready product
2 Improve flow and stability or regulator with CFD software
3 Must be capable of delivering stable and precise outlet pressure under demanding flow conditions.
4 Should provide stable outlet pressure, despite inlet pressure swings
5 Design Constraints/Requirements/Specifications:
a Control pressure ranges from 0-100 psi
b Mfg. costs to under $80.00
c Streamlined & Low-Profile design
d Must be a balanced design regulator
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
PSU Cocoziello Institute 1 Beaver Stadium Pedestrian Flow Data System for Concessions and Egress Choi, Kyusun 0 0 1 2 0 0 3 0 0 3 0 0 0

Non-Disclosure Agreement: NO

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

On a home football Saturday, Beaver Stadium moves more than 100,000 people through its gates in a few hours. Most decisions about concession staffing, inventory, and post-game egress are based on experience rather than actual data on how people move. This project asks a student team to design and test a way to collect pedestrian flow data during a game day. That includes choosing sensing methods (for example, anonymous camera counts, Wi-Fi/Bluetooth probes, or manual counts), deciding where to place them, and figuring out how often to collect data. The team would then use that data to show where and when queues build up within the stadium, outside of the stadium, and how egress happens towards parking lots or other transportation options.
We also want the data collected in a way that can feed a simulation of pedestrian and vehicle movement around the stadium. So a key part of the project is defining a clear data format, so that things like gate counts, origin–destination flows, walking speeds, densities, queue lengths, and egress rates that can be used directly as inputs to and checks on a simulation model.
Expected outcome: A tested data-collection method and a dataset from at least one home game, organized in a consistent format. It should be directly useful for improving concessions and egress operations, and structured so it can serve as the input and validation data for a demonstration simulation of pedestrian traffic around the stadium.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
PSU Cocoziello Institute 2 Data Governance Platform for Campus Facility Digital Twins Verbanac, Alan 0 0 0 1 0 0 0 0 0 2 0 0 0

Non-Disclosure Agreement: NO

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: NO

Images and Additional Links (if provided)

Universities and other large organizations are building "digital twins" of their buildings and campuses — live connected digital models that pull together data from building models, geographic information systems, sensors, maintenance records, space management systems, security cameras, and more to improve operations, sustainability, and emergency planning and response. But as these systems grow, a challenging question keeps coming up: who should be allowed to access what data, when, and for what purpose?

Most organizations know who the lead owner is for each data source, but there's rarely a structured data governance process to request, review, and approve access across systems. Today, that usually means emailing the right office and waiting. This project asks a student team to design and build a working prototype of a data governance process and platform: a system where users can request access to specific data, have that request routed through a clear approval workflow, and have every decision logged and auditable. The team will define the different types of users (facilities staff, researchers, security, outside partners, public), what data each should be allowed to see, and build software that runs that approval process automatically instead of relying on manual requests.

Good data governance isn't just about restricting access — it's also what makes new capabilities possible. When data from separate systems can be securely combined, it opens the door to applying artificial intelligence across those combined sources: for example, spotting maintenance issues before they happen, predicting occupancy and energy use, or flagging unusual patterns that a human monitoring one system at a time would miss. Part of the project is showing how the data governance platform doesn't just control access, but actively enables this kind of cross-system analysis and AI use.

The team will work with a realistic example facility — think a museum, stadium, hospital, or airport — and demonstrate the system handling multiple users requesting different kinds of access for different digital twin use cases, with the platform granting, denying, and logging each request appropriately.

Expected outcome: A clearly defined data governance process — covering access requests, approvals, and audit logging — demonstrated through a working software prototype that shows how that governance can safely enable AI-driven insights across combined data sources.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
PSU Cocoziello Institute 3 From RFID Tags to Digital Twins: Mapping Movement in Real Time Choi, Kyusun 0 0 1 3 0 0 2 0 0 0 0 0 0

Non-Disclosure Agreement: NO

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

How can a building know where people and objects are in real time without relying on cameras, smartphones, or identifiable information? In this project, students will build a low-cost, privacy-conscious indoor tracking system using passive UHF RFID technology. Using RFID wristbands or tags, antennas, readers, a microcontroller, and local Wi-Fi/MQTT, the team will detect movement between zones and explore how antenna placement, signal strength, and algorithms affect tracking accuracy.

The project will connect to a live digital twin of a space in Pattee Library called the Digital Twin Literacy Center, enabling RFID data to drive visualizations, web applications, and immersive experiences. Students will gain hands-on experience with RFID, IoT, embedded computing, networking, Python, data analytics, and digital twins while solving a real-world sensing challenge. No prior experience with RFID or digital twins is required. This proof of concept could ultimately scale to larger spaces and buildings across Penn State.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
PSU College of Arts and Architecture Art and Engineering of Composite Musical Instruments Kimel, Allen 0 0 0 0 0 0 0 0 0 0 1 2 0

Non-Disclosure Agreement: NO

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

Art and Engineering of composite musical instruments
By V. Brown and D. Whisler
Fall 2026

The modern composite is finding increased use in a wider range of consumer applications, from inexpensive phone cases, wallets, and accessories to high velocity transportation vehicles. Whereas its origins began as a simply toughened version of existing materials, i.e. straw in bricks and glass fibers in resin, the modern application towards ultralight and ultrastrong designs sees composites as a high-performance substitute for many traditionally metal or wood products.

Musical instruments are one such category that makes extensive use of wood and metal, among other materials. Additionally, many have stayed true to their historical past: the violin since 16th century and trombone originating a century early are two such examples where their shape and construction of wood and brass, respectively, have persisted virtually unchanged to present day. With recent advancements in composite materials, modern sensing, and acoustics, we now have the capabilities to build sturdier, lighter, weather resistant variants. Musical accessories, and entire instruments can now be made lighter, perhaps more user customizable, but ideally still able to capture the tonality, warmth, and essence of the original just with a modern design.

For this capstone project, we are looking to design, engineer, and fabricate musical instruments from carbon fiber. Our focus this semester is primarily on the tuba, and any related subassembly supporting usage and transportation, as we seek to make it lighter and more easily packaged while preserving its sound. As a team, we will be exploring material design, ergonomics, sound and acoustics, and some hands-on fabrication in the Learning Factory as we investigate the composites used to make all (or part) of the instrument. This means your multi-disciplinary team will have multiple perspectives to consider: material sections capable of withstanding the rigors and demands of a 30 lb instrument, the aesthetics and costs for both early and accomplished players, and of course, the end product that meets the need of actual tuba musicians. While the modern carbon fiber materials can address some of the shortcomings with brass (namely weight), its intonation and inherent differences compared to a denser metal means delving into research and working within the material property limits.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
PSU College of Engineering 1 Secure Local AI Platform for Protected Information Environments Verbanac, Alan 0 0 0 1 0 0 0 0 0 0 0 0 0

Non-Disclosure Agreement: NO

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: NO

Images and Additional Links (if provided)

Organizations increasingly need AI-assisted learning, knowledge management, and engineering support capabilities, but many cannot use public AI services because the information involved is sensitive, proprietary, export-controlled, security-related, or otherwise restricted from external disclosure. Modern AI tools have the potential to significantly improve education, training, knowledge management, engineering analysis, and technical decision support. However, many organizations cannot utilize public AI services because their information may be sensitive, proprietary, export-controlled, security-related, privacy-protected, or otherwise restricted from external disclosure. This project seeks to develop and evaluate a locally deployed AI platform capable of supporting these activities while maintaining organizational control of data, with robust data integrity, and complying with applicable security, privacy, intellectual property, and regulatory requirements.
While this project will use representative test data, actual use cases could include:
• Critical infrastructure (e.g., nuclear facilities)
• Healthcare systems
• Defense and national security
• Export-controlled environments (ITAR/EAR)
• Proprietary industrial operations
• Research laboratories
Project deliverables can include:
• Local LLM deployment and benchmarking
• Evaluation of open-source models for different use cases
• Secure document ingestion and retrieval
• Role-based access concepts
• Local RAG architecture
• Hardware recommendations
• User experience design
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
PSU College of Engineering 2 Secure Local AI Platform for Protected Information Environments Verbanac, Alan 0 0 0 1 0 0 0 0 0 0 0 0 0

Non-Disclosure Agreement: NO

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: NO

Images and Additional Links (if provided)

Organizations increasingly need AI-assisted learning, knowledge management, and engineering support capabilities, but many cannot use public AI services because the information involved is sensitive, proprietary, export-controlled, security-related, or otherwise restricted from external disclosure. Modern AI tools have the potential to significantly improve education, training, knowledge management, engineering analysis, and technical decision support. However, many organizations cannot utilize public AI services because their information may be sensitive, proprietary, export-controlled, security-related, privacy-protected, or otherwise restricted from external disclosure. This project seeks to develop and evaluate a locally deployed AI platform capable of supporting these activities while maintaining organizational control of data, with robust data integrity, and complying with applicable security, privacy, intellectual property, and regulatory requirements.
While this project will use representative test data, actual use cases could include:
• Critical infrastructure (e.g., nuclear facilities)
• Healthcare systems
• Defense and national security
• Export-controlled environments (ITAR/EAR)
• Proprietary industrial operations
• Research laboratories
Project deliverables can include:
• Local LLM deployment and benchmarking
• Evaluation of open-source models for different use cases
• Secure document ingestion and retrieval
• Role-based access concepts
• Local RAG architecture
• Hardware recommendations
• User experience design
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
PSU College of Medicine Flow-limiting device for emergency ventilation Pacey, Mark 1 0 0 0 0 0 0 0 0 0 0 2 0

Non-Disclosure Agreement: NO

Intellectual Property: YES

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

A bag-valve mask is a handheld medical device used to provide emergency ventilation to patients who are not breathing adequately. It consists of a self-inflating bag, a one-way valve, and a face mask, and can be connected to supplemental oxygen. In some cases the device is used too aggressively, providing too much respiratory volume or rate which can harm the patient. The purpose of this project is to design a modified bag-valve mask or add-on device that can prevent excessive ventilation. A standard bag-valve mask will be provided, and the team is asked to design, prototype, and test a device. Mentors include an emergency medicine doctor at Hershey Medical Center.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
PSU Department of Biomedical Engineering - Hayes Research Group Low-Cost Ultrasound Device for Precision Drug Delivery Pacey, Mark 1 0 0 0 0 0 2 0 0 0 0 0 0

Non-Disclosure Agreement: NO

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

Focused ultrasound (FUS) can be combined with microbubble-mediated blood-brain barrier (BBB) opening to deliver drugs precisely targeted to tumors and other specific sites. Existing devices are feature rich but are too bulky for small animal research. There is a need for a low-cost device that can be used in a small animal model that is high precision but limited in its feature set to reduce size and complexity.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
PSU Department of Communication Sciences & Disorders Development of a vocal dosimeter: Combined measure of neck vibration and total body movement Pacey, Mark 1 0 3 0 0 0 2 0 0 0 0 0 0

Non-Disclosure Agreement: NO

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

We want to create a wearable device that can measure vocal load over a period of several hours.

Vocal load can be measured by adhering an accelerometer to the front of the neck which measures vocal pitch and loudness, as well as dosage in total time spent voicing, based on the vibration of the vocal cords.

To assist with understanding our goals, you can look at these three papers:
1. This paper uses an adhesive to keep the accelerometer in place – we like this style over a necklace-type device that we currently have: https://pubmed.ncbi.nlm.nih.gov/22875236/#:~:text=DOI%3A-,10.1109/TBME.2012.2207896,-Abstract

2. This paper describes a DIY version: https://doi.org/10.1044/2023_jslhr-23-00060

3. This paper describes the one we currently have: https://doi.org/10.3390/ijerph19116491

In addition to measuring vocal load, we would like to measure overall physical activity throughout the day. Our goal is for this data to be inputted to the same instrumentation module as the dosimeter for synchrony.

The deliverable for this project is a wearable, rechargeable voice dosimeter and accelerometer that could record data for a minimum of 8 hours. The device does not need to be wireless and the person could wear some type of belt bag (fanny pack) to hold the instrumentation module.

We have an older model that is no longer functioning reliably. We can give this to you to take apart to determine how it was made (see picture of device we are currently using).

References instead of DOIs above:
Astolfi, A., Puglisi, G. E., Shtrepi, L., Tronville, P., Marval Diaz, J. A., Carullo, A., Vallan, A., Atzori, A., Ferri, A., & Dotti, F. (2022). Effects of Face Masks on Physiological Parameters and Voice Production during Cycling Activity. International Journal of Environmental Research and Public Health, 19(11), 6491. https://doi.org/10.3390/ijerph19116491

Bottalico, P., & Nudelman, C. J. (2023). Do-It-Yourself Voice Dosimeter Device: A Tutorial and Performance Results. Journal of Speech, Language, and Hearing Research, 66(7), 2149–2163. https://doi.org/10.1044/2023_JSLHR-23-00060

Mehta, D. D., Zañartu, M., Feng, S. W., Cheyne, H. A., & Hillman, R. E. (2012). Mobile Voice Health Monitoring Using a Wearable Accelerometer Sensor and a Smartphone Platform. IEEE Transactions on Biomedical Engineering, 59(11), 3090–3096. https://doi.org/10.1109/TBME.2012.2207896
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
PSU Department of Computer Science and Engineering Penn State AI Advisor: Phase II Verbanac, Alan 0 0 0 1 0 0 0 0 0 0 0 0 0

Non-Disclosure Agreement: NO

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: NO

Images and Additional Links (if provided)

This project continues the Penn State EECS AI Advisor piloted in Spring 2026 (you can read about it here: https://sites.psu.edu/lfshowcasesp26/2026/04/29/eecs-ai-advisor/) and aligns with Penn State’s strategic priorities in student success, digital transformation, and responsible AI integration. Its design continues to be guided by feedback from Computer Science and Engineering academic advisers, pre-major advisers, and the study abroad office.

Background: What Phase I Delivered (Spring 2026)
In Spring 2026, a senior capstone team built and validated the EECS AI Advisor (V1), a document-grounded advising assistant configured in Microsoft Copilot Studio on top of a Penn State SharePoint knowledge base of advisor-approved PowerPoint modules. The agent reliably answers common questions across EECS, pre-major, and study abroad advising, including course substitution, grade forgiveness, AI violations, course repeats, major and minor pairings, and late adds. Guardrails restrict responses to approved content and redirect students to a human adviser when a question falls outside the knowledge base. Advisers can update the SharePoint modules directly, with changes automatically reflected in the agent, and by final testing the agent answered scenario-based questions consistently with minimal hallucinations. The system is currently in an adviser review cycle prior to student release.

Main Objective
To move the AI Advisor from a validated prototype to a deployed, measurable student service: complete adviser review, release the agent to students through Microsoft Teams, expand its knowledge coverage, and build the evaluation and analytics layer needed to demonstrate impact on adviser workload and student outcomes.
Specific Aims for Fall 2026
• Deployment: Close out the adviser review cycle, resolve remaining inaccuracies, and publish the agent to Microsoft Teams and other Penn State Microsoft 365 channels students already use, with clear onboarding materials.
• Knowledge expansion: Extend the advisor-validated knowledge base beyond EECS, pre-major, and study abroad to additional engineering departments, following the same stakeholder review workflow established in Phase I.
• Evaluation and analytics: Instrument the agent with usage tracking, accuracy auditing, and student and adviser feedback collection to measure deflected routine inquiries, response quality, and after-hours usage.
• Responsible enhancement: Prototype multilingual support and explore FERPA-aligned personalization using enrollment data, with human-in-the-loop oversight and governance review before any student data integration.
What Students on This Project Will Do and Learn

The Fall 2026 capstone team will work directly with academic advisers and the faculty sponsor in weekly working sessions, gaining hands-on experience in AI agent configuration and grounding (Microsoft Copilot Studio), knowledge engineering and content governance (SharePoint), prompt and guardrail design, deployment within an enterprise Microsoft 365 environment, and evaluation of a live AI system with real users. This is a rare opportunity to ship an AI product to thousands of fellow students while learning how responsible, policy-compliant AI is actually built inside a large institution.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
PSU Department of Entomology - Grozinger Lab LumiFlor: an adaptive, autonomous, control system for real-time bee detection and monitoring Cubanski, Dave 0 0 2 3 0 0 1 0 0 0 0 3 0

Non-Disclosure Agreement: NO

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

Bees are essential for global agriculture and ecosystems, yet traditional monitoring relies on slow, labor-intensive manual sampling and observation. To address this, we are engineering LumiFlor, an autonomous Cyber-Physical System designed to actively track, behaviorally evaluate, and identify bee species in real time.
1. Active LED Attraction: Transitioning from passive traps to active monitoring, LumiFlor utilizes programmable, custom-built LED arrays tailored to bee visual biology, emitting specific wavelengths to safely attract them.
2. Array Design: Fabricated entirely in-house using a desktop PCB printer, four interchangeable artificial "flowers" dynamically switch sizes and precise UV, blue, and green wavelength combinations to support rapid behavioral studies.
3. Camera Monitoring System: A stereoscopic pair of high-speed cameras (over 500 fps) quantitatively tracks complex 3D foraging behaviors. Simultaneously, it extracts synchronized image bursts for automated, real-time species classification.
4. Power Systems and Autonomous Operation: To ensure long-term field autonomy, a solar-harvesting suite employs "graceful degradation," dynamically cutting power to non-essential peripherals during low-energy states to maintain core sensing functions.
5. Edge Computing Integration: Adapting our existing YOLO-based AI pipeline, the onboard system processes rapid motion detection and object tracking, instantly modifying the data output for deep scientific analysis.
By merging dynamic floral mimicry with edge AI, LumiFlor delivers an unprecedented, labor-reducing hardware platform for real-time conservation and agricultural research.

1. LumiFlor Physical Prototype: A fully assembled, weather-resistant field unit that combines the calibrated stereoscopic high-speed camera rig with the programmable LED arrays.
2. LED Arrays, Files, & Firmware: Fully fabricated UV/blue/green PCB boards, accompanied by the control firmware for floral patterns and printable hardware design files (ECAD/Gerber).
3. Protocols & Datasets: Standardized experimental assay protocols, a field validation dataset, and an ethological database linking species classifications with complex 3D behavioral metrics.
4. Power Management Unit (PMU): An integrated solar harvesting and battery system.
5. Edge-Computing & AI Pipeline: A ruggedized hardware module running the integrated classification software to extract synchronized images and identify species in real time.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
PSU Department of Industrial Engineering Development of an Immersive VR Platform to Study Social Influence in Pedestrian–Automated Vehicle Interactions Zajac, Brian 0 0 3 2 0 0 0 0 0 1 0 0 0

Non-Disclosure Agreement: NO

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

Problem Statement:
As automated vehicles become increasingly present in public road environments, pedestrian interactions with these vehicles remain uncertain and potentially unsafe. Pedestrians traditionally rely on vehicle movement, eye contact, driver gestures, and the behavior of nearby pedestrians to determine whether it is safe to cross. Automated vehicles remove many familiar driver-based communication cues, creating ambiguity about whether the vehicle has detected the pedestrian and intends to yield. In group settings, pedestrians may also rely on social information by following others, even when those actions are unsafe or conflict with vehicle behavior. Although eHMIs have been proposed to communicate automated-vehicle intent, limited research has examined how eHMI information interacts with social influence during pedestrian crossing decisions.

How the Project Addresses the Gap:
This project will conduct a focused literature review and develop a fully functioning immersive VR environment to examine pedestrian decision-making around automated vehicles. The VR scenarios will systematically vary eHMI availability, group size, and the behavior of surrounding pedestrians. Conditions will include crossing alone, observing one or multiple pedestrians cross, watching others remain at the curb, and encountering conflicting or unsafe group behavior. By controlling vehicle speed, yielding behavior, pedestrian actions, and communication cues, the VR platform will provide a realistic and repeatable environment for studying how pedestrians prioritize vehicle movement, eHMI signals, and social information.

Expected Outcomes:
The project is expected to produce a comprehensive literature review, a fully functional set of VR pedestrian-crossing scenarios, and detailed documentation of the experimental conditions and outcome measures. The developed platform will be ready for pilot testing and future human-subject studies. It is expected to support the measurement of crossing initiation time, waiting duration, accepted gaps, unsafe crossings, and attention to vehicles, eHMIs, and other pedestrians. The project will also establish a foundation for understanding when social influence supports or undermines safe crossing decisions and how eHMIs can be designed to improve communication between automated vehicles and pedestrians.

Deliverables:
1. A structured literature review identifying current findings and research gaps.
2. A fully functioning set of VR pedestrian-crossing scenarios.
3. Scenario documentation describing vehicle behavior, eHMI conditions, group behavior, and outcome measures.
4. A pilot-ready VR platform for future human-subject experiments.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
PSU Department of Mechanical Engineering 1 Designing an AI Tutor for Thermodynamics: Student Needs Assessment and Prototype Wang, Qian 0 0 0 0 0 0 0 0 0 0 0 1 0

Non-Disclosure Agreement: NO

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

Undergraduate engineering students increasingly turn to AI tools for help with their coursework, but instructors and curriculum designers still know very little about how, when, and why students use AI to support their learning, especially in challenging technical courses like Thermodynamics. This project, sponsored by three faculty members in Mechanical Engineering with support from the Leonhard Center, invites a capstone team to help fill that gap through student-facing needs assessment, design thinking, and low fidelity prototyping.

The team will take on three connected charges. First, the team will use AI tools extensively throughout their own capstone work and document how they use them, what works, what does not, and where AI helps or hinders their design process. These reflections will inform faculty guidance on effective AI use in project-based engineering courses across the college. Second, the team will conduct a needs assessment with undergraduate students who are currently taking Thermodynamics. Using interviews, surveys, and observational methods, the team will identify where students struggle, when and how they currently use AI for support, and what a well-designed AI tutor could offer that existing tools do not. Third, based on what they learn, the team will design and build a low fidelity prototype of a personalized AI-supported Thermodynamics tutor and test it with a small group of student users.

This project is well suited to students interested in user research, design thinking, and human-centered design. Prior experience with undergraduate Thermodynamics is welcome but not required. This project is part of a Penn State research study on AI in engineering education. Students who join this team will (a) conduct human-subjects research and will receive the required human-subjects research training to do so, and (b) also participate as subjects in the study by sharing their own reflections on their AI use throughout the capstone project. No work beyond the normal expectations of the capstone project will be required. By joining this project, students indicate their consent to participate. Participation as a research subject can be withdrawn at any time. Full details will be shared at the project kickoff, and questions are welcome to the research PI: Dr. Andrea Gregg, axg251@psu.edu.

Deliverables:
1. A structured reflection report on the team's own use of AI throughout the capstone project, including recommendations for other project-based course instructors.
2. A needs assessment report summarizing findings from Thermodynamics students, including personas, key user needs, and design implications.
3. A low fidelity prototype of a personalized AI-supported Thermodynamics tutor, tested with a small group of student users.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
PSU Department of Mechanical Engineering 2 ASME e-Human-Powered Vehicle Lewis, Alfred 0 0 0 0 0 0 2 0 0 0 0 1 0

Non-Disclosure Agreement: NO

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

The goal of this project is to design and build a vehicle for entry into the ASME human-powered vehicle competition. For the first time in 2022, the competition rules were significantly altered to allow electric pedal-assist vehicles. The capstone team is responsible for either significantly altering the previous year's vehicle platform or designing and building their own vehicle from the ground up. Deliverables include an operable vehicle, a description of the innovation over previous team's designs, and video demonstrations of several safety tests. Safety tests include roll over, turning, and breaking distance.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
PSU Department of Nuclear Engineering 1 Portable Hardware-in-the-Loop OT Training Kit for Global Nuclear Cybersecurity Education Sudharsan, Supraja 0 0 3 2 0 0 3 3 0 0 0 0 1

Non-Disclosure Agreement: YES

Intellectual Property: YES

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

Project Motivation
Cybersecurity professionals increasingly need hands-on experience with Operational Technology (OT) systems and Industrial Control Systems (ICS). While simulator-based environments such as ARCADE and ANS2.0 provide realistic cyber-physical training environments, students often lack exposure to the physical devices, sensors, actuators, and controller interactions that exist in real-world facilities. The goal of this project is to develop an inexpensive, portable, and easily replicated Hardware-in-the-Loop (HiL) Learning Kit that integrates with either the ARCADE or ANS2.0 simulation environments. The kit should provide a tangible physical component that allows students and trainees to observe, control, and secure a cyber-physical process while interacting with the simulator. The long-term vision is to support nuclear cybersecurity education worldwide by enabling institutions with limited resources to deploy affordable training systems that use commonly available components and open manufacturing techniques.

Project Objectives
The student team will design, prototype, test, and document a cyber-physical learning kit that:
• Interfaces with ARCADE or ANS2.0 simulator environments.
• Functions with either local laptop deployments or Virtual Desktop Infrastructure (VDI) deployments.
• Emulates one or more industrial control system devices within the simulation environment.
• Demonstrates a measurable/observable physical response to simulator actions.
• Supports cybersecurity, networking, and control-system learning objectives.
• Can be replicated using commercially available components and basic fabrication methods such as consumer-grade 3D printing.

Technical Requirements
The proposed solution should:
• Use low-cost and globally available hardware.
• Support simple deployment in classroom, workshop, or remote-learning environments.
• Include at least one physical process representation (examples may include valves, pumps, tank levels, indicators, motors, lights, gauges, or other actuator-driven systems).
• Incorporate a controller capable of emulating industrial PLC behavior.
• Exchange data with simulator environments using appropriate industrial communication methods.
• Be safe for classroom use.
• Be transportable and durable.

Expected Deliverables
The student team should provide:
• Functional prototype learning kit.
• CAD models and design files.
• 3D-printable component files.
• Bill of materials with sourcing information.
• Assembly guide.
• Instructor guide.
• Student laboratory exercises.
• Testing and validation report.
• Recommendations for future scalability and enhancements.

Desired Outcomes
The resulting kit should enable students anywhere in the world to:
• Experience the interaction between cyber systems and physical processes.
• Understand Operational Technology concepts.
• Explore industrial communications and control architectures.
• Conduct cybersecurity-focused exercises in a safe environment.
• Learn the fundamentals of Hardware-in-the-Loop testing and cyber-physical systems.

Project Variants for Four Teams
The final design should support multiple deployment configurations:
1. ARCADE on Laptop
2. ARCADE on VDI
3. ANS2.0 on Laptop
4. ANS2.0 on VDI
A common hardware architecture should be used wherever possible to minimize cost and maximize portability.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
PSU Department of Nuclear Engineering 2 Portable Hardware-in-the-Loop OT Training Kit for Global Nuclear Cybersecurity Education Sudharsan, Supraja 0 0 3 2 0 0 3 3 0 0 0 0 1

Non-Disclosure Agreement: YES

Intellectual Property: YES

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

Project Motivation
Cybersecurity professionals increasingly need hands-on experience with Operational Technology (OT) systems and Industrial Control Systems (ICS). While simulator-based environments such as ARCADE and ANS2.0 provide realistic cyber-physical training environments, students often lack exposure to the physical devices, sensors, actuators, and controller interactions that exist in real-world facilities. The goal of this project is to develop an inexpensive, portable, and easily replicated Hardware-in-the-Loop (HiL) Learning Kit that integrates with either the ARCADE or ANS2.0 simulation environments. The kit should provide a tangible physical component that allows students and trainees to observe, control, and secure a cyber-physical process while interacting with the simulator. The long-term vision is to support nuclear cybersecurity education worldwide by enabling institutions with limited resources to deploy affordable training systems that use commonly available components and open manufacturing techniques.

Project Objectives
The student team will design, prototype, test, and document a cyber-physical learning kit that:
• Interfaces with ARCADE or ANS2.0 simulator environments.
• Functions with either local laptop deployments or Virtual Desktop Infrastructure (VDI) deployments.
• Emulates one or more industrial control system devices within the simulation environment.
• Demonstrates a measurable/observable physical response to simulator actions.
• Supports cybersecurity, networking, and control-system learning objectives.
• Can be replicated using commercially available components and basic fabrication methods such as consumer-grade 3D printing.

Technical Requirements
The proposed solution should:
• Use low-cost and globally available hardware.
• Support simple deployment in classroom, workshop, or remote-learning environments.
• Include at least one physical process representation (examples may include valves, pumps, tank levels, indicators, motors, lights, gauges, or other actuator-driven systems).
• Incorporate a controller capable of emulating industrial PLC behavior.
• Exchange data with simulator environments using appropriate industrial communication methods.
• Be safe for classroom use.
• Be transportable and durable.

Expected Deliverables
The student team should provide:
• Functional prototype learning kit.
• CAD models and design files.
• 3D-printable component files.
• Bill of materials with sourcing information.
• Assembly guide.
• Instructor guide.
• Student laboratory exercises.
• Testing and validation report.
• Recommendations for future scalability and enhancements.

Desired Outcomes
The resulting kit should enable students anywhere in the world to:
• Experience the interaction between cyber systems and physical processes.
• Understand Operational Technology concepts.
• Explore industrial communications and control architectures.
• Conduct cybersecurity-focused exercises in a safe environment.
• Learn the fundamentals of Hardware-in-the-Loop testing and cyber-physical systems.

Project Variants for Four Teams
The final design should support multiple deployment configurations:
1. ARCADE on Laptop
2. ARCADE on VDI
3. ANS2.0 on Laptop
4. ANS2.0 on VDI
A common hardware architecture should be used wherever possible to minimize cost and maximize portability.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
PSU Engineering Leadership Development Wireless Presentation Moderator Cubanski, Dave 0 0 2 3 0 0 1 0 0 0 0 3 0

Non-Disclosure Agreement: NO

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

This project will use a series of portable, small scale, off-the-shelf electronics to create a wireless display that allows a moderator to discretely communicate with a presenter. The primary goal will be to display a simple clock and other visual aids to assist presenters in keeping on task.

The system should be compact and self-sufficient, meaning it should not rely on external power, WiFi, etc. The moderator should be able to control the presenter display wirelessly within a large conference room. The presenter display should be compact such that it is discretely placed where it will not distract the audience, but be easily seen by the presenter.

The entire system should also be sufficiently packaged for portable use and easily transported. Charging or other maintenance-related tasks should be easily completed without the use of tools.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
PSU Health AI-Assisted Hospital Safety Event Triage, Case Linkage, and Trend Discovery Platform Verbanac, Alan 2 0 0 1 0 0 0 0 0 3 0 0 0

Non-Disclosure Agreement: NO

Intellectual Property: YES

Physical Prototype or On-Campus Equipment: NO

Images and Additional Links (if provided)

Hospitals collect patient safety event reports that contain valuable information about errors, near misses, contributing factors, and opportunities for improvement. However, these reports are often reviewed through labor-intensive manual workflows, and it can be difficult to identify related events or recognize themes that emerge across many reports over time.

The goal of this project is to design and build an integrated prototype platform that uses artificial intelligence and modern software engineering to support the review and analysis of hospital safety events. This is not solely an artificial intelligence modeling project. Students will design a broader software ecosystem that connects data ingestion, artificial intelligence models, secure data handling, storage, workflow management, and an intuitive user interface.

The prototype should ingest narrative safety reports and generate structured information that can assist with initial triage and organization. It should identify and link similar historical reports so users can easily explore related cases, recurring contributing factors, and potential patterns. The platform should also group reports into broader themes and display how those themes change over time.

A major emphasis will be placed on user experience. Students should develop an interface that makes safety events discoverable, allows users to move easily between related cases, explains why cases were linked, and presents trends in a clear and actionable manner. Creativity in the interface, visualizations, search functions, and methods of exploring relationships among events is encouraged.

The project should establish a privacy-conscious technical approach for developing, training, testing, and evaluating artificial intelligence components in a healthcare environment. The sponsor plans to provide the student team with fully synthetic safety-event data generated locally from the structure and general characteristics of real institutional event reports. The synthetic dataset will be designed to support realistic development and testing without exposing identifiable patient information or confidential event narratives.

The sponsor also maintains access to the underlying institutional safety-event data within the secure hospital environment. Students should therefore design the software and models so they can be packaged in a portable, containerized format. The sponsor can run the container internally against institutional data and return aggregate performance results, error examples, and other non-identifiable feedback to support iterative evaluation. Institutional data will remain within the sponsor’s environment and will not be transferred to the student team.

The proposed architecture should also address access control, data minimization, audit logging, separation of development and evaluation datasets, model versioning, reproducibility, and protection of sensitive information.

An additional advanced objective is to explore a prototype method for reviewing clinical records to identify possible safety events that were not submitted through the voluntary reporting system. The system may generate draft MIDAS-style event summaries for human review and inclusion in broader trend analyses. This component should focus on feasibility, architecture, representative workflows, and proof-of-concept methods using public, de-identified, or synthetic clinical data.

Expected deliverables include the following:
• An integrated prototype platform with a functional front-end and back-end for ingesting safety reports, reviewing individual events, navigating linked cases, and exploring themes and trends over time.
• Artificial intelligence models or model interfaces for report triage, structured information extraction, similar-case retrieval, and thematic grouping. The sponsor has developed preliminary models to address these functions, which may be used as baselines. Students will be encouraged to evaluate alternative approaches and refine or replace components when they can demonstrate improved accuracy, efficiency, interpretability, or usability.
• A documented and reproducible data and system architecture, including pipelines for ingesting and validating sponsor-provided synthetic data, privacy-conscious development practices, access controls, auditability, and separation of development and evaluation data.
• A containerized version of the models and supporting software that the sponsor can run within its secure institutional environment to evaluate performance using real safety-event data without transferring those data to the student team.
• An evaluation framework covering model performance, retrieval relevance, usability, reliability, interpretability, failure modes, and appropriate human review.
• Complete project documentation and handoff materials, including source code, system diagrams, setup and testing instructions, recommendations for future development, a final technical report, a demonstration, a poster, and a one-page summary.

The following is a "stretch goal" that we hope the team can achieve:
• A feasibility assessment and, if achievable within the project scope, a proof-of-concept method for identifying potentially unreported safety events from clinical records and generating draft safety-event summaries for human review.


The overall emphasis should be on integrating these components into a coherent, creative, and usable end-to-end prototype rather than simply reproducing the sponsor’s existing preliminary models.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
PSU Huck Plant Institute and Indoor Plant Physiology Lab Autonomous Vertical Farming system Sudharsan, Supraja 0 0 3 2 0 0 3 0 0 3 0 1 0

Non-Disclosure Agreement: NO

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

One of the biggest challenge of the 21st century is how to grow food with limited inputs while maximizing outputs. Hydroponic vertical farms have demonstrated their capacity to target some of these pressing issues but can sometimes be limited by over engineering or lack of innovation. This project, is building up on the very successful Spring 2026 Capstone project on Sustainable Plant Factory system, to improve or create an autonomous robot capable of sensing its environment, report data on plant growth, autonomously able to move around the farm and recharge itself. The proof of concept used a small 10 inch by 10 inch tray motorized. We will modify this robot and add a series of sensors, RFID and other detection system, so it can interact with its environment and communication with the farm operator. The final goal would be to have a finish product and grow plants to present the entire project at the Showcase.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
PSU Indoor Plant Physiology Lab Next generation Desktop Hydroponic Choi, Kyusun 0 0 0 1 0 0 2 0 0 3 0 3 0

Non-Disclosure Agreement: NO

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

One of the biggest challenge of the 21st century is how to grow food with limited inputs while maximizing outputs. Hydroponic vertical farms have demonstrated their capacity to target some of these pressing issues but can sometimes be limited by over engineering or lack of innovation. This project will transform an existing desktop hydroponic system sold by CropKing and turn it into a high tech system capable of growing greens and herbs while controlling all the environmental parameters and sensing its own environment. The project will involve many environmental sensors that will have to be installed, calibrated and connected to an electronic board (Arduino and/or Raspberry Pi) capable of sending information online. The final goal would be to have an app where growing parameters are recorded and where user can choose growth recipe and control the environment.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
PSU Learning Factory 1 AI-Powered Penn State Engineering Engagement Navigator Verbanac, Alan 0 0 0 1 0 0 0 0 0 0 0 0 0

Non-Disclosure Agreement: NO

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: NO

Images and Additional Links (if provided)

Companies and external organizations interested in working with Penn State's College of Engineering often have difficulty identifying the right person or office to contact. Whether they want to recruit students, sponsor capstone projects, conduct research, collaborate with faculty, engage with student organizations, or support events, Penn State's large and complex organizational structure can make finding the right connection challenging.
This challenge is especially relevant as the College of Engineering's Senior Director of Corporate Engagement transitions out of the university, potentially creating an additional barrier for external groups seeking to engage with the College.
We envision a student capstone team developing an AI-powered tool that helps external organizations navigate Penn State Engineering and identify the most relevant contacts, departments, faculty, student organizations, and programs based on their goals.
The project could involve building a searchable knowledge base of College of Engineering departments, faculty research areas, student organizations, academic programs, capstone opportunities, research centers, and other resources. An AI-powered interface would allow users to describe what they are trying to accomplish and receive recommendations for relevant Penn State contacts and resources.
For example, a company could ask:
"We are interested in recruiting computer engineering students, sponsoring an AI-focused capstone project, and connecting with faculty conducting research in autonomous systems. Who should we talk to?"
The tool could recommend relevant contacts, departments, faculty, programs, and next steps.
Potential Capstone Deliverables:
• Develop a structured database or knowledge base of relevant Penn State Engineering contacts and resources.
• Create an AI-powered natural-language interface for external organizations.
• Develop an AI recommendation system to identify relevant contacts and engagement opportunities.
• Build a prototype web-based interface.
• Develop a process for keeping information current as contacts and organizational structures change.
• Test the system using real-world external engagement scenarios.
The goal is to create a "front door" for companies and external organizations seeking to connect with Penn State Engineering—making it easier to find the right people and opportunities while helping the College facilitate external engagement more effectively.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
PSU Learning Factory 2 AI-Powered Penn State Engineering Engagement Navigator Verbanac, Alan 0 0 0 1 0 0 0 0 0 0 0 0 0

Non-Disclosure Agreement: NO

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: NO

Images and Additional Links (if provided)

Companies and external organizations interested in working with Penn State's College of Engineering often have difficulty identifying the right person or office to contact. Whether they want to recruit students, sponsor capstone projects, conduct research, collaborate with faculty, engage with student organizations, or support events, Penn State's large and complex organizational structure can make finding the right connection challenging.
This challenge is especially relevant as the College of Engineering's Senior Director of Corporate Engagement transitions out of the university, potentially creating an additional barrier for external groups seeking to engage with the College.
We envision a student capstone team developing an AI-powered tool that helps external organizations navigate Penn State Engineering and identify the most relevant contacts, departments, faculty, student organizations, and programs based on their goals.
The project could involve building a searchable knowledge base of College of Engineering departments, faculty research areas, student organizations, academic programs, capstone opportunities, research centers, and other resources. An AI-powered interface would allow users to describe what they are trying to accomplish and receive recommendations for relevant Penn State contacts and resources.
For example, a company could ask:
"We are interested in recruiting computer engineering students, sponsoring an AI-focused capstone project, and connecting with faculty conducting research in autonomous systems. Who should we talk to?"
The tool could recommend relevant contacts, departments, faculty, programs, and next steps.
Potential Capstone Deliverables:
• Develop a structured database or knowledge base of relevant Penn State Engineering contacts and resources.
• Create an AI-powered natural-language interface for external organizations.
• Develop an AI recommendation system to identify relevant contacts and engagement opportunities.
• Build a prototype web-based interface.
• Develop a process for keeping information current as contacts and organizational structures change.
• Test the system using real-world external engagement scenarios.
The goal is to create a "front door" for companies and external organizations seeking to connect with Penn State Engineering—making it easier to find the right people and opportunities while helping the College facilitate external engagement more effectively.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
PSU School of Engineering Design and Innovation Humidification of Hollow-bodied Wooden Instruments: prototype development through mechanical and electrical design Cubanski, Dave 0 0 0 0 0 0 1 0 0 0 0 2 0

Non-Disclosure Agreement: NO

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

Hollow-bodied wooden instruments worth thousands of dollars can crack in a single dry winter. This project builds on a patented technology to humidify these instruments, and the team's mission is to move it from initial design to a refined prototype that professional musicians will use and evaluate on their own instruments. The prototype must demonstrate all core functionality and survive real-world use.
The team will begin by identifying the core functions the product must perform, such as vapor generation, air transport, humidity monitoring, and instrument interface. For each core function, students will build and test small-scale prototypes of multiple candidate approaches, drawing primarily on commercially available components. The results of these prototype tests, not assumptions, will drive the design decisions: the team will select which approach to carry forward for each function based on their own experimental data. The selected approaches will then be synthesized into a complete, fully functional system-level prototype, allowing musicians to evaluate how well the chosen mechanisms serve their needs.
Two engineering skill areas are essential to this project. First, circuit and microcontroller experience: the final prototype will integrate a microcontroller, vapor generation, power management with charging, and simple wireless connectivity such as Bluetooth or WiFi onto a printed circuit board, so basic PCB layout skills are required. Second, mechanical design of physical structures: the team will design and 3D print housings that contain the electronics, direct the flow of humid air, and incorporate a water reservoir, among other functions. Students with an interest in hands-on prototyping, data-driven design decisions, and taking a product from concept to working hardware will find this project a strong fit.
Deliverables:
1. Functional decomposition identifying the core functions of the product
2. Micro-prototypes and test results evaluating multiple approaches for each core function
3. Documented trade studies justifying the selected approach for each function
4. A fully functional system-level prototype suitable for evaluation by musicians
5. Complete design files, including PCB layouts, firmware source code, and CAD models, delivered in editable formats
6. Final report, poster, and project summary per Capstone requirements
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
Rathithi Polytechnic Vehicle Controller Unit (VCU) Design for Retrofitted Farm Transport Vehicles. Spencer, Maria 0 0 0 3 0 0 1 0 0 0 0 2 0

Non-Disclosure Agreement: NO

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

This project aims to design Vehicle Controller Units (VCU) for use in retrofitted tuktuks.

Tuktuks are three wheeler Internal Combustion Engine Vehicles (ICEV). In Kenya, out-of-service tuktuks can be acquired cheaply locally and retrofitted into Electric Vehicles (EV) lowering the cost of acquisition and cost of operation within the context of farm transport.

To further lower the cost of acquisition, increase mean uptime and reduce the cost of repair, this project aims to design a VCU that can be manufactured and repaired locally (in Kenya).

The design goals are: reliability; the ability to manufacture and repair the VCU locally (in Kenya), and; modularity to allow module swapping as a means of repair

The expected deliverables are: one prototype of the VCU (hardware), accompanying software for the VCU supporting sensored Field Oriented Control (FOC), and; well defined VCU failure modes, which give feedback to the driver/technician, and an accompanying troubleshooting manual/checklist isolating the failed module/subsystem.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
Seco Tools Automated 3D Scanning and Digital Reconstruction of Small-Diameter Carbide End Mills Mittan, Paul 0 0 1 3 0 0 0 0 0 0 0 2 0

Non-Disclosure Agreement: NO

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

Project Description:

Precision cutting tools such as carbide end mills contain complex geometric features that are difficult to capture with conventional low-cost 3D scanning systems. This project will develop and validate an enhanced OpenScan3-based scanning platform (https://openscan.eu/blogs/news/openscan3-beta-whats-new ) capable of accurately digitizing a 10 mm solid carbide end mill for reverse engineering, geometry analysis, and digital manufacturing applications. OpenScan3 provides a flexible open-source foundation with automated motion control, high-resolution imaging support, and photogrammetry integration.

The student team will investigate methods for improving the scanning of highly reflective carbide surfaces through optimized fixturing, lighting, imaging, and photogrammetry techniques. The resulting system will be evaluated for its ability to generate accurate 3D models suitable for engineering analysis and comparison with known tool geometries.

Project Deliverables:

-Design and build a modified OpenScan3 scanning system optimized for small cutting tools.
-Develop a precision fixture and positioning system for scanning 10 mm carbide end mills.
-Evaluate and implement appropriate imaging, lighting, and surface treatment strategies to improve scan quality.
-Generate accurate 3D digital models of scanned cutting tools.
-Validate scan accuracy through comparison with measured tool dimensions.
-Create complete documentation including system design, bill of materials, operating procedures, and recommended improvements.
-Deliver a final technical report and presentation summarizing the system performance, accuracy, limitations, and future development opportunities.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
Seco Tools AB Steam Delivery System for Cutting Tools Zajac, Brian 0 0 3 0 0 0 2 0 0 1 0 3 0

Non-Disclosure Agreement: YES

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

Background: The steam-cleaning step is the final process for cutting tools before coating and is critical for tool performance. Currently, this process is fully manual and guided by basic rules, but variations and inconsistencies between operators and tools have been observed. Additionally, steam-cleaning is one of the most time-consuming preparation steps, making it a major bottleneck in the coating workflow.

Project Scope: For this second iteration of the Capstone project, the main objective will be to design and build a functional steam delivery system that could be used in a large-scale production setting.

Objectives:
1. Review the current process and define the key parameters required for a standardized and controlled steam delivery operation.
2. Design a prototype that securely delivers steam to tools of 4 mm to 15 mm diameter.
3. Build the prototype with a user-friendly setup for ease of operation.

Deliveries:
1. Fully functional steam delivery system.
2. Technical documentation and system architecture.
3. User manual for operation and maintenance.

Project Benefits:
1. Improved Process Control: Standardization of critical parameters ensures consistent cleaning quality and reduces variability between operators and tools.
2. Reduced Labor Time: Automating key steps minimizes manual intervention, shortens preparation time, and alleviates one of the major bottlenecks in the coating process.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
Shawn Mankamyer Designing a Mechanical Sweet Corn Harvester Spencer, Maria 0 0 0 0 0 0 2 0 3 0 0 1 0

Non-Disclosure Agreement: NO

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

Background
Farms have two options for harvesting sweet corn. Some farms pick their corn by hand, and others use mechanical harvesters. The issue is that with rising labor costs, many small farms want to use faster mechanical harvesters, but no options exist withing the price range these farms need. Because of this, small sweet corn farms are struggling to compete with the larger farms than can afford large harvesters.

To address this issue and help so many farms in need of functional, low cost equipment, a pending start-up called Bluebird Agriculture is developing a small mechanical sweet corn harvester. This machine is designed to pick corn quickly and efficiently while staying as low cost as possible and is designed with all the needs of a small farm in mind.

What Can Be Expected
In this project, students will work with a prototype harvester to engineer new components, build what they designed, and test their work with an in-field harvest trial. The end goal of this project is to push this harvester from a concept prototype to a feasible harvesting machine fit for the needs of small farms. This project will be guided by the abilities of each student, but work with both mechanical systems such as belt drives and conveyors as well as electro-mechanical systems can be expected. Because of this, students from many different engineering backgrounds will be able to design and build a revolutionary harvesting machine and ultimately close a gap in harvesting technology that will help countless small farms.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
Shell 1 Shell Eco-marathon Neal, Gary 0 0 0 0 0 0 2 0 0 0 0 1 0

Non-Disclosure Agreement: NO

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

Shell Eco-marathon (https://www.shellecomarathon.com/) is a global student engineering competition focused on automotive energy optimization. The goal is to design and build a fuel-efficient vehicle that meets all the competition rules and then compete against nearly 100 other North and South American schools. The competition will be held at the Indianapolis Motor Speedway, and winners in our category routinely achieve > 500 mpg. Penn State’s Ecomarathon club (https://sites.psu.edu/pennstateecomarathon/) has performed well for over 20 years, and we’re now leveling up our game. In collaboration with the PSU student club, these capstone teams will integrate recent competition lessons learned into the ground up design of a brand-new vehicle. This project will design, build, and test that vehicle, first at our Penn State Test Track and ultimately at the Shell Ecomarathon competition. Yes, we actually drive our car on the Indianapolis Motor Speedway track! Some cool things you may do to create our winning car include mechanical design using CAD modeling, finite element analysis, and computational fluid dynamic aero analysis; automotive electrical system design and construction; steel tubing and aluminum sheet metal cutting, bending, and welding; carbon fiber fabrication; small displacement engine powertrain implementation and optimization; and many other things. If you want a hands-on experience where you will design and build a real car; have a competitive spirit and want to see Penn State win; are into sustainable automotive technologies; or want the chance to compete on the Indianapolis Motor Speedway, then this is the project for you!
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
Shell 2 Shell Eco-marathon Neal, Gary 0 0 0 0 0 0 2 0 0 0 0 1 0

Non-Disclosure Agreement: NO

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

Shell Eco-marathon (https://www.shellecomarathon.com/) is a global student engineering competition focused on automotive energy optimization. The goal is to design and build a fuel-efficient vehicle that meets all the competition rules and then compete against nearly 100 other North and South American schools. The competition will be held at the Indianapolis Motor Speedway, and winners in our category routinely achieve > 500 mpg. Penn State’s Ecomarathon club (https://sites.psu.edu/pennstateecomarathon/) has performed well for over 20 years, and we’re now leveling up our game. In collaboration with the PSU student club, these capstone teams will integrate recent competition lessons learned into the ground up design of a brand-new vehicle. This project will design, build, and test that vehicle, first at our Penn State Test Track and ultimately at the Shell Ecomarathon competition. Yes, we actually drive our car on the Indianapolis Motor Speedway track! Some cool things you may do to create our winning car include mechanical design using CAD modeling, finite element analysis, and computational fluid dynamic aero analysis; automotive electrical system design and construction; steel tubing and aluminum sheet metal cutting, bending, and welding; carbon fiber fabrication; small displacement engine powertrain implementation and optimization; and many other things. If you want a hands-on experience where you will design and build a real car; have a competitive spirit and want to see Penn State win; are into sustainable automotive technologies; or want the chance to compete on the Indianapolis Motor Speedway, then this is the project for you!
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
SignaHz Acoustic Energy Harvesting for Self-Powered Wireless Devices: Design, Characterization, and Validation of a Resonant Piezoelectric Power Module Cubanski, Dave 0 0 0 0 0 0 1 3 0 0 0 2 0

Non-Disclosure Agreement: YES

Intellectual Property: YES

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

Overview:
Energy harvesting is the practice of capturing small amounts of ambient energy from the environment and converting it into usable electrical power. As wireless sensors and connected devices become more widespread, there is growing demand for power sources that reduce or eliminate the need for batteries, which are costly to replace, generate waste, and limit where devices can be placed. This project explores acoustic energy harvesting, in which acoustic pressure waves are converted into electrical energy using a piezoelectric transducer.
The central engineering challenge is that raw acoustic energy is low in magnitude and must be captured efficiently and then conditioned into a stable, usable electrical output. To capture energy efficiently, the system uses an acoustic resonator, a tuned mechanical structure that amplifies acoustic pressure at a target frequency and couples it to a piezoelectric element. The harvested electrical output is then conditioned and stored so it can power a low energy electronic load.
This project is part of an active product development effort that has received grant support from Autodesk and intellectual property counsel from the University of Pennsylvania Carey Law School Detkin Intellectual Property and Technology Legal Clinic, and continues to work with the Penn State Law Intellectual Property Clinic. The student team will design, build, and validate a working bench prototype of the harvesting system. The sponsor will provide commercial evaluation hardware, a materials budget supported by the Autodesk grant, access to Autodesk design software such as Fusion 360 for modeling and fabrication, and ongoing technical mentorship.
Deliverables:
1. Background review and design targets: summarize acoustic energy harvesting, resonant coupling, and piezoelectric transduction, and define quantitative, testable performance targets for the system in coordination with the sponsor.
2. Resonator design and fabrication: design a tuned acoustic resonator in CAD, fabricate it using 3D printing or comparable methods, and iterate the geometry to maximize coupling with the provided piezoelectric transducer at the target frequency.
3. Harvester characterization: measure electrical output across a range of acoustic input conditions, including steady and intermittent inputs, using provided instrumentation, and report voltage, current, power, and an estimate of acoustic to electrical conversion efficiency.
4. Power conditioning and energy management: convert the harvested output into a stable regulated voltage using the provided power management hardware, and size energy storage so the system can accumulate intermittent harvested energy and support duty cycled operation of the load.
5. Battery free demonstration: demonstrate the complete system operating with no external power source, in which harvested energy powers a representative low energy wireless sensing event, such as waking a microcontroller, taking a sensor reading, and transmitting or logging the result.
6. Final report and dataset: document the design, measured performance against the defined targets, conversion efficiency, limitations, and recommendations for future optimization, with the full test dataset.
Optional stretch goal: explore resonator variants to broaden usable bandwidth, or benchmark an alternative geometry against the baseline.
The ideal outcome is a documented, working hardware platform that reliably converts acoustic input into usable electrical power and demonstrates the feasibility of self powered wireless sensing. The module is intended to integrate into a larger wireless sensing network.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
SME Solutions, Inc FPGA Data Bus for Real Time Robotic Communications Choi, Kyusun 0 0 1 2 0 0 3 0 0 0 0 3 0

Non-Disclosure Agreement: NO

Intellectual Property: YES

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

Student team will design and implement a simple message packet switching network on an FPGA chip for deterministic data communication among IoT sensors and a central controller in a robot. An inexpensive robot consists of multiple sensors and a central processing unit responsible for decision making and control algorithms. Sensor data will be transmitted through the FPGA data bus to the central processor, where it will be analyzed and used to generate commands for the robot. The project will focus on reducing communication latency, limiting timing variation, prioritizing critical sensor data messages, and maintaining predictable performance during periods of high data traffic.

Possible sensors may include distance, position, force, proximity, light, color, or safety sensors. The final demonstration should show how sensor information is received, processed, and used to control the robot system through the FPGA data bus. An FPGA development board Kria KV250 board will be provided, which will be integrated into an inexpensive robo-car with arm to demonstrate both fast real-time data communication and robotic operations.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
TE CONNECTIVITY CORPORATION, a TE Connectivity Ltd. company Smart Solar Farm Monitoring Mittan, Paul 0 0 2 3 0 0 1 3 3 0 0 3 0

Non-Disclosure Agreement: YES

Intellectual Property: YES

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

Can powerline communications provide a reliable data backbone for utility-scale solar farms? In this capstone project, students will design and build a battery-powered research platform that communicates over solar-farm DC cabling while logging environmental and electrical conditions. The system will use a Raspberry Pi or similar host with a PLC modem to measure channel behaviour, including signal attenuation versus frequency, and correlate performance with changing solar-farm conditions. Deliverables will include working hardware, embedded and analysis software, datasets and a technical report, with the potential for a small-scale trial on a university-operated solar farm.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
The Boeing Company Modular Autonomous Payload Deployment System for Rotorcraft Mittan, Paul 0 0 2 3 0 0 3 0 3 0 0 1 0

Non-Disclosure Agreement: NO

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

Overview:
Develop a scalable, Modular Open Systems Architecture (MOSA)-compliant subsystem capable of autonomously deploying and recovering small unmanned aerial vehicle (UAV) payloads—commonly called Launched Effects—from a rotorcraft platform. The project will include mechanical design of the deployment/recovery mechanism, development of control and autonomy software, and integration with a modular interface enabling future enhancements or payload swaps.

Expected Deliverables:
1. Mechanical Prototype: Scaled functional deployment mechanism (e.g., launcher and payload cradle) demonstrating physical release and recovery actions.
2. Embedded Control System: MOSA-enabled hardware controller programmed for autonomous sequencing, sensor data handling, and communication.
3. Autonomy Software Module: Algorithms for pre-launch checks, safe payload release, and recovery sequencing simulated in software or run on prototype hardware.
4. MOSA Interface Documentation: Specifications and example implementation for modular hardware/software integration and communication.
5. Test Plan and Validation Results: Test cases demonstrating deployment reliability, autonomy operation, and system integration on physical or simulated hardware.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
The Manitowoc Company, Inc. Evaluation of Manufacturing Temperature Effects on the Mechanical Properties of TMCP and Discrete Plate Steels Kimel, Allen 0 0 0 0 0 0 0 0 0 0 1 2 0

Non-Disclosure Agreement: YES

Intellectual Property: YES

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

Project Background:
Steel manufacturers utilize different processing routes to achieve the required balance of strength, toughness, ductility, and weldability. Two common production methods are:

1.Thermo-Mechanically Controlled Processed (TMCP) Steel: achieves strength and toughness through controlled rolling temperatures and accelerated cooling, relies on grain refinement and microstructural control rather than high alloy content, and the mechanical properties can be sensitive to subsequent thermal exposure.

2. Discrete Plate Steel: properties are developed through traditional rolling followed by heat treatment such as normalizing and/or quench and tempering. Performance is generally less dependent on the precise thermal history during rolling.

Understanding how manufacturing temperatures influence each material type is critical for welding, forming, stress relieving, and fabrication operations.

Problem Statement:
Manufacturing and fabrication processes frequently expose steel plates to elevated temperatures through welding, stress relief, thermal cutting, and forming operations. These thermal cycles may alter the microstructure and resulting mechanical properties of TMCP and discrete plate steels differently.

The industry requires quantitative data to understand:
1. How strength changes with thermal exposure.
2. How toughness degrades at elevated temperatures.
3. Which material is more resistant to thermal damage.
4. Whether current fabrication temperature limits adequately preserve mechanical performance.

Overall, we need to determine how exposure to various manufacturing temperatures affects the mechanical properties and the microstructure of TMPC steel compared to discrete plate steel.

Research Questions
1. How do yield strength and tensile strength change with increasing temperature exposure?
2. How does impact toughness change after thermal cycling?
3. Does TMCP steel experience greater degradation than discrete plate steel?
4. What microstructural changes occur at different temperature ranges?
5. What temperature threshold begins to significantly affect mechanical performance?
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
TMP Manufacturing Company, Inc. Walk-In Cooler Door Gasket Inventory Optimization Wang, Qian 0 0 0 0 0 0 0 0 0 2 0 1 0

Non-Disclosure Agreement: NO

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

TAFCO is a central Pennsylvania manufacturer with over 65 years of experience producing walk-in coolers, freezers, and modular insulated panels for food service, pharmaceutical, government, and military customers. Because TAFCO builds highly customized products to client specifications, their door configurations require hundreds of unique perimeter gaskets. These gaskets come in U-shaped, L-shaped, and four-sided profiles, in right- and left-handed variants, across multiple materials. All of them must be stocked, protected from damage, and reliably located at the time of assembly. Current storage practices result in significant gasket damage and waste, and simply finding the right gasket when needed is a recurring challenge.

This project has two connected goals: reduce inventory complexity and improve gasket storage. On the inventory side, students will evaluate one baseline solution: stocking a smaller number of oversized gaskets and trimming them to size at assembly. Gasket material affects whether this modification is feasible, so students will need to account for this constraint. Students will also identify and compare other SKU-reduction strategies and develop SOPs for any recommended process changes. On the storage side, students will gather requirements, survey commercial solutions, and, if none are adequate, design and prototype a custom system that prevents damage and supports easy retrieval. Students have freedom to explore and justify their own approaches to both problems, and they will deliver a comparative analysis with a clear recommendation, supporting SOPs, and a prototype or design concept as warranted.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
University of Dayton Research Institute Vehicle Adaptable Multipurpose Energy Bank Mittan, Paul 0 0 0 0 0 3 1 3 0 0 0 2 0

Non-Disclosure Agreement: NO

Intellectual Property: YES

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

INTRODUCTION:
Modern teams operating in remote and off-grid environments—from scienti?c researchers in the ?eld to disaster response units—rely on a growing number of electronic devices. Communications gear, sensors, laptops, and diagnostic tools are essential, but their effectiveness is limited by the availability of power. In austere settings, the ability to sustainably power and recharge this diverse equipment from a single, reliable source becomes a critical logistical challenge.

THE CHALLENGE:
Your challenge is to design a single, portable, and versatile power station that derives its energy from a vehicle source and serves as a centralized energy hub for a small team in the ?eld. The vehicle source may be anything from a commercial vehicle to an ATV. The solution must be a "one-stop-shop" for portable power, capable of charging a wide array of electronic devices simultaneously and being recharged from multiple vehicle sources and may incorporate other renewable energy sources, such as solar.

CORE PROBLEM TO SOLVE:
Develop a rugged, high-capacity, portable power bank that provides sustained, quiet, and reliable electricity for a diverse suite of electronic equipment. Innovation focus should be placed on the method of extracting /transforming vehicle energy into electrical energy. The system must be easily transportable, air-travel compliant, and capable of supporting a team during multi-day operations away from any traditional power grid, with only access to a vehicle of undetermined type without requiring any permanent modifications to the vehicle, such as changing major engine parts or components.


DELIVERABLES:
PDR presentation, CDR Presentation, Final Presentation, Final Report, Final demonstration and associated Product Videos.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
Vistra Corporation 1 Nuclear Cooling Tower Pump House Ventilation Damper Re-Design Banyay, Gregory 0 0 0 0 0 0 2 0 0 0 3 1 0

Non-Disclosure Agreement: YES

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

Cooling Tower Pump House Damper Replacement Engineering Evaluation Report

The report would include:

1. Existing Conditions Assessment
- Document the current damper configuration.
- Develop a damper inventory including:
- Location
- Dimensions
- Material construction
- Actuation method (manual, pneumatic, electric)
- Service environment
- Identify signs of degradation, corrosion, accessibility issues, and maintenance
concerns.
- Produce a photographic walkdown package.

This would offer an opportunity for Vistra Engineering to give a tour to the students performing this project.

2. Functional Requirements Document

Develop a clear list of functional requirements for replacement dampers, including:
- Airflow requirements
- Environmental operating conditions
- Weather resistance
- Corrosion resistance
- Reliability and maintainability objectives
- Interface requirements with existing structures and equipment

3. Market Research and Technology Evaluation
Evaluate commercially available damper solutions and compare:
- Materials
- Actuation options
- Maintenance requirements
- Expected service life
- Cost considerations

The team would develop a recommendation matrix identifying preferred replacement options.

4. Conceptual Design Package
Develop:
- Conceptual replacement sketches
- Preliminary installation concepts
- Identification of potential interferences
- Access considerations for maintenance
- Develop a high-level implementation strategy.

5. Cost and Schedule Estimate
Provide:
- Preliminary material cost estimate
- Installation labor estimate
- Recommended project execution schedule

Expected Final Products:

The team would deliver:
1. Engineering Evaluation Report
2. Damper Asset Inventory Database
3. Photographic Walkdown Package
4. Conceptual Drawings and Layouts
5. Preliminary Cost Estimate
6. Executive Summary Presentation
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
Vistra Corporation 2 Nuclear Cooling Tower Filter Screen Cleaning Banyay, Gregory 0 0 0 0 0 0 2 0 0 0 3 1 0

Non-Disclosure Agreement: YES

Intellectual Property: NO

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

At Beaver Valley Unit 1, we have issues with the cooling tower filter screens for the water exiting the cooling tower to the condenser clogging. This issue causes thermal performance to lag and as it degrades and can impact cooling tower pump performance which could lead to reducing power output of the power station. The past few years we have been bringing in divers to clean the screens. This is a risky situation that we would like to discontinue for personal safety reasons. What they have been finding is cooling tower fill stuck on the screen along with algae growth at certain times of the year.

What we are looking for is a design that can automatically clean the screens so that we can control build-up. The feature would have to be capable of removing materials as well as cleaning the algae build-up.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
Westinghouse Electric Company 1 Emissivity Improvement on Tube for Optical Pyrometer Temperature Readings Kimel, Allen 0 0 0 0 0 0 0 0 0 0 1 2 0

Non-Disclosure Agreement: YES

Intellectual Property: YES

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

As part of the research and development efforts of the eVinci™ Microreactor, high temperature heat pipes are being constructed and tested. During testing, the heat pipe temperature is a critical measurement. One method of temperature measurement employes an optical pyrometer to perform contactless measurements of the surface temperature of a heat pipe. Surface condition and emissivity have been shown to have significant effects on these surface temperature measurements of tested heat pipes.

The goal of this design team will develop a method to improve the emissivity of the heat pipe tube material. The method developed for application to the heat pipe tube should result in a uniform high emissivity surface of the tube and survive exposure to high temperatures.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
Westinghouse Electric Company 2 Thermocouple Jig for Surface Temperature Measurement on Outside Diameter of Tubing Manogharan,Guhaprasanna 0 0 0 0 0 0 0 0 0 2 0 1 0

Non-Disclosure Agreement: YES

Intellectual Property: YES

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

As part of the research and development efforts of the eVinci™ Microreactor, high temperature heat pipes are being constructed and tested. During functional testing of the heat pipes, the heat pipe temperature is a critical measurement and needs to be accurately measured. The primary instrumentation temperature measurement method uses thermocouples and is affixed to the outside diameter of the heat pipe. The importance of this project is to improve on temperature measuring accuracy and repeatability of the heat pipe surface temperature over current methods ultimately improving the quality of the heat pipe testing and test results.

Primary objective: Improved Thermocouple Mounting

The goal of this design team will be to design a thermocouple mounting method that ensures the most accurate surface temperature reading of the heat pipe. The process of installing and removing thermocouples needs to be repeatable and allow for achieving repeatable temperature readings. The maximum design temperature for the thermocouple and thermocouple fixture needs to be considered in the design along with maximum clamping force allowed to be applied to the heat pipe.

Stretch goal: Distributed Thermocouple Mounting

The goal of this design team will be to design a mounting jig for multiple thermocouples along the length of a heat pipe to allow for axial distributed temperature measurements that are accurate and repeatable for measurements and for installation. The process of installing and removing thermocouples as well as high temperature and maximum clamping force will need to be accounted for in this design.
Company Name Project Title Faculty Contact BME CHE CMPEN CMPSC DS ED EE EGEE ESC IE MATSE ME NUCE
WSSC Water Adaptive Fire Hydrant Flusher Sudharsan, Supraja 0 0 0 0 0 0 0 0 0 2 3 1 0

Non-Disclosure Agreement: NO

Intellectual Property: YES

Physical Prototype or On-Campus Equipment: YES

Images and Additional Links (if provided)

The WSSC Water is a bi-county, public water/wastewater utility in Maryland that was established in 1918. For over 100 years, WSSC Water has served the communities of Prince George’s and Montgomery counties providing life-sustaining water and water resource recovery services to individuals, families and businesses. WSSC Water maintains and repairs approximately 60,000 fire hydrants and several dozen facilities to provide water services to its community. WSSC Water provides life saving fire water to approximately 2 million!
Fire hydrants require regular maintenance to operate correctly. One critical activity that WSSC Water performs on fire hydrants is a flush and test process. This test requires flowing a large amount of water from the hydrant to and, at the same time, take critical measurement from the hydrant. An all-in-one tool to perform this process is needed.
The PSU teams will design, develop, and prototype a devise that would meet all the above requirement and incorporate ergonomics aspects to make the process of using the devise the most comfortable for a field Technician. The devise will need to be durable, portable and as light weight as possible.
The PSU team will have freedom to develop concepts of solutions starting at day 1 of the project. A site visit in the first few weeks will also highlight actual working conditions. The student team will need to quickly move through design and prototype so that they can work with a WSSC Water partner foundry to have several copies of the tool fabricated, assembled and ready for field use by the end of the semester.
 
 

About

The Learning Factory is the maker space for Penn State’s College of Engineering. We support the capstone engineering design course, a variety of other students projects, and provide a university-industry partnership where student design projects benefit real-world clients.

The Learning Factory

The Pennsylvania State University

University Park, PA 16802