Project Details

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Modular “Any Job Shop” Digital Twin Using ProModel.ai

Company: BigBear.ai

Major(s):
Primary: IE
Secondary: CMPSC

Non-Disclosure Agreement: YES

Intellectual Property: YES

BigBear.ai develops advanced simulation and digital twin solutions used across supply chain manufacturing warehousing logistics and healthcare. This project is sponsored by BigBear.ai’s Supply Chain Management team and supports the continued development of ProModel.ai a modern web based simulation platform designed to enable scalable configurable digital twins for operational decision support. The objective of this project is to design and implement a modular reusable job shop simulation digital twin using ProModel.ai. Manufacturers frequently need to evaluate throughput resource constraints routing changes and layout alternatives but building simulation models from scratch can be time consuming and expensive. Student teams will create a flexible job shop model that can be configured to represent a variety of manufacturing environments with multiple machine centers routing logic shift schedules and shared resources. The model will allow users to run scenario analysis and compare system performance across different operating conditions. Project deliverables include a working job shop simulation model built in ProModel.ai along with documentation describing model logic assumptions inputs outputs and configuration guidance. Students will conduct scenario experiments and analyze results using key performance measures such as throughput utilization work in process and cycle time. By early April the team will also produce a one to two page customer facing summary that explains the model its capabilities and example use cases using visuals from the simulation. This summary will be suitable for use at industry trade shows or conferences. The project will conclude with a final presentation report and showcase poster consistent with Learning Factory requirements. No proprietary or confidential data is required and optional virtual or on site technical discussions may be arranged during the semester.