Minneapolis, MN
August 23, 2022
June 26, 2022
June 29, 2022
8
10.18260/1-2--41835
https://peer.asee.org/41835
462
IVAN A. RENTERIA-MARQUEZ is a Research Assistant Professor of industrial applied research at The University of Texas at El Paso Department of Industrial, Systems and Manufacturing. He holds a PhD in simulation of piezoelectric travelling wave rotary ultrasonic motor. His research interests include simulation and modeling of actuators, simulation and modeling of manufacturing systems with discrete events and fabrication of piezoelectric devices. His email address is iarenteria@utep.edu.
Dr. Md Fashiar Rahman is a Research Assistant Professor of industrial applied research at The University of Texas at El Paso Department of Industrial, Systems and Manufacturing. He holds a PhD degree in Computational Science Program. He has years of research experience in different projects in the field of image data mining, machine learning and deep learning for industrial and healthcare applications. In addition, Dr. Rahman has taught many different engineering courses in industrial and manufacturing engineering. His research area covers advanced quality technology, AI application in smart manufacturing, health care applications, and computational intelligence/data analytics.
The digitization of machines, tools, and other elements of manufacturing systems presents substantial benefits, but there is a need to overcome technical and workforce skills gap regarding Smart Manufacturing (SM) technologies and processes, especially for underserved small and medium manufacturers (SMMs). Increasing representation of minority workforce demographics with knowledge of advanced manufacturing technologies is required for effective SM technology adoption and implementation, to sustain regional manufacturing superiority. This effort demonstrates a strategy to create a SM curriculum and certificate program that promotes SM concepts in underserved SMMs and upskilling an underrepresented (Hispanic) workforce, by developing industry-relevant training materials and research laboratory practices. Existing academic, industry, workforce, and economic development partnerships were leveraged to capture and address the diverse learning needs across the entire regional SM pipeline. The key tasks conducted to fulfill the project goals included the development of a SM curriculum and SM focused laboratories at UTEP, approval of the SM certificate program to engage and increase SM knowledge in underserved regional manufacturers, and development of industry relevant use cases in SM related areas. The resulting infrastructure provides an underrepresented workforce demographic with access to a state-of-the-art SM research facility, hands-on experience developing case studies, and interdisciplinary knowledge in SM engineering. The SM framework is expected to increase the number of SM trained engineers, increase industry deployment and adoption through development and implementation of SM specific use cases, and increase the SM supply chain through economic development partnerships. The strategy presented in the paper provides an approach to increase SM adoption in historically underserved communities.
Lopes, A., & Renteria Marquez, I., & Tseng, T., & Rahman, M. F., & Luna, S. (2022, August), Smart Manufacturing for Underserved Workforce Development Paper presented at 2022 ASEE Annual Conference & Exposition, Minneapolis, MN. 10.18260/1-2--41835
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