2026 ASEE Annual Conference & Exposition

Hands-On Predictive Maintenance Kit for Manufacturing Education: An Accessible Experiential Learning Approach

Presented at Manufacturing Division (MFG) Technical Session 3: Experiential Learning in Manufacturing Education I

Predictive maintenance (PdM) is a cornerstone of smart manufacturing systems due to its role in identifying potential machine failures before they occur, which allows strategic maintenance scheduling, maximizing operational uptime. Despite its importance in industry, traditional engineering education still lacks the tools required to give students a hands-on PdM experience. Current educational methods rely on mock PdM datasets, which disconnect students from the practical educational experiences built on sensor implementation, real-time data acquisition, and analytics using Machine Learning (ML). To bridge this gap, this research focused on the development of a low-cost educational PdM Add-On kit for FrED, a low-cost educational desktop-scale manufacturing system, developed at MIT, based on industrial fiber draw that serves as an experimental platform for data collection and analysis. The kit, consisting of a modular sensor suite and companion software, makes hands-on PdM education more accessible through realistic and interactive applications. This work aims to demonstrate that FrED, equipped with the PdM Add-On kit, provides an effective and scalable platform for data-centric PdM education. The kit was deployed in a classroom environment, where students collected process data, applied preprocessing and feature extraction methods, and developed ML models. The augmented FrED platform enabled students to engage with the full PdM workflow using a setup that mimics a real-world industrial scenario while growing their advanced analytics skill set. To validate the pedagogical effectiveness of this intervention, the study employed a mixed-methods assessment framework grounded in Self-Determination Theory (SDT). Student outcomes were evaluated using three distinct instruments: a technical Concept Inventory (CI) to measure objective learning gains, the Perceived Competence Scale (PCS) to quantify shifts in self-efficacy, and the Intrinsic Motivation Inventory (IMI) to assess student engagement and intrinsic motivation. Moreover, reflective questions were used to understand the student learning changes shown in the quantitative instruments.

Authors

Mr. Ibrahim El Khatib Massachusetts Institute of Technology [biography]

Ibrahim El Khatib is a Doctoral student in the Department of Mechanical Engineering at the Massachusetts Institute of Technology (MIT). His research interests focus on the integration of machine intelligence within manufacturing and the advancement of Industry 4.0 technologies. Prior to starting his doctoral studies, Ibrahim worked as a Packaging Module Development Engineer at Intel and an Additive Design & Manufacturing Product Application Engineer at General Motors. He holds a Master of Engineering in Advanced Manufacturing and Design from MIT , as well as a Master of Science in Business Analytics and a Bachelor of Engineering in Mechanical Engineering from the American University of Beirut.
Manuel Ivan Vea Tecnologico de Monterrey (ITESM) [biography]

Manuel Ivan Vea is an 8th-semester B.S. in Mechatronics Engineering student at Tecnologico de Monterrey, and worked as a visiting student at the FrED Factory Lab at the Massachusetts Institute of Technology (MIT). His research interests focus on mechanical design engineering, industrial automation, and the integration of data-driven predictive maintenance within manufacturing environments. Prior to his time at MIT, Manuel worked at Nemak as a Mechanical Design Engineering Intern, where he contributed to internal manufacturing solutions through mechanical design, tooling development, and maintenance planning for facilities in the US and Mexico. He has further experience in the implementation of robotics systems and automated assembly cells, specializing in PLC/HMI control and OEE optimization. Currently, his work involves developing machine learning-based educational kits for fault classification and deploying Python-based data analytics pipelines for manufacturing applications.
Marcelo Montemayor Cavazos Tecnologico de Monterrey (ITESM) [biography]

Marcelo Montemayor Cavazos is a Mechatronics Engineering student at Tecnológico de Monterrey and was a Visiting Student at MIT. He completed the 2025 FrED Factory Smart Manufacturing Research Immersion, a program focused on the complexities of scaling manufacturing operations and the integration of desktop manufacturing education kits. His research at the FrED Factory Lab involves high-fidelity digital twins and machine learning for acoustic-based predictive maintenance. Marcelo has a strong background in industrial automation, having developed fully automated assembly cells with PLC/HMI control and robotics. Additionally, he has experience in heavy-load material handling through the development of Autonomous Ground Vehicle (AGV) prototypes.
Mr. Russel Bradley http://orcid.org/0000-0002-9454-4951 Massachusetts Institute of Technology [biography]

Russel Bradley is a Ph.D. candidate in Mechanical Engineering at the Massachusetts Institute of Technology (MIT), specializing in smart manufacturing education, manufacturing systems, and additive manufacturing. He co-founded and leads the development of MIT’s learning factory, FrED Factory, which makes hands-on manufacturing education accessible and replicable across universities. Through its international deployment across multiple institutions, the FrED Factory has reached and trained over 500 students, expanding access to experiential manufacturing education beyond MIT. He also serves on the boards of startups and non-profits in artificial intelligence (AI), sustainable energy, and additive manufacturing that advance technological innovation in Indonesia. He has received multiple honors, including the MIT Graduate Teaching Award, the MIT Graduate Student of Excellence Award, and the Tulip Interfaces Golden Spade Groundbreaker Award.
Dr. Erick Ramirez-Cedillo Tecnologico de Monterrey, Escuela de Ingeniería y Ciencias, Av. Eugenio Garza Sada #2501 Sur, Monterrey, N.L., 64700, México. [biography]

Erick Ramírez-Cedillo is the Director of the Innovation and Transformation Program at the School of Engineering and Sciences, Tecnológico de Monterrey, He holds a Bachelor's in Mechatronics Engineering, a Master's in Manufacturing Systems, and a Ph.D. in Engineering Sciences from Tecnológico de Monterrey. His research focuses on Additive Manufacturing, Manufacturing Systems Automation, Robotics, Educational Innovation, Advanced Materials, and Medical Devices.
Dr. Brian W Anthony Massachusetts Institute of Technology [biography]

Brian Anthony is the Director of the Master's of Engineering in Manufacturing Program and Co-director of the Medical Electronic Device Realization Center at MIT. He has more than 20 years of product realization experience, including instrumentation and me

Note

The full paper will be available to logged in and registered conference attendees once the conference starts on June 21, 2026, and to all visitors after the conference ends on June 24, 2026

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