Model-Based System Engineering Applied to Designing Engineering Labs to Dynamically Adapt to Industry Trends - Case in Point: The Mechatronics, Robotics and Control Lab
- Conference
- Location
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Portland, Oregon
- Publication Date
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June 23, 2024
- Start Date
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June 23, 2024
- End Date
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July 12, 2024
- Conference Session
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Multidisciplinary Engineering Division (MULTI) Technical Session 1
- Tagged Division
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Multidisciplinary Engineering Division (MULTI)
- Tagged Topic
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Diversity
- Permanent URL
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https://peer.asee.org/47782
Paper Authors
Pallavi Singh University of South Florida
Pallavi Singh received a bachelor’s degree in Electronics and Communication Engineering from Guru Nanak Dev Engineering College (GNDEC), Bidar, in 2016 and a master’s degree in Electrical Engineering from University of South Florida, Tampa, FL, USA, in 2019.
Pallavi worked as a data science engineer, embedded system engineer, computer vision engineer, system engineer, project manager, and systems engineer, In addition, Pallavi, has also served as a teaching and research assistant at the University of South Florida, along with for various electrical engineering courses.
Pallavi is currently a Ph.D. candidate and working toward her Ph.D. degree in Electrical Engineering from University of South Florida. Her main areas of research center around Machine Learning applications for Engineering Education, with the goal of enhancing students’ performance and learning. This includes Digital Engineering, Model-Based Systems Engineering (MBSE), and Educational Data Mining. In addition, She is interested in research application of Machine Learning across diverse sectors like automotive, healthcare, education, and manufacturing.
Luis Miguel Quevedo
IEEE Educational Activities
orcid.org/0009-0006-0018-792X
Grisselle Centeno Florida Southern College
Dr. Grisselle Centeno is the Lyons Endowed Chair in Logistics and Professor of Supply Chain and Analytics at Florida Southern College. She holds a bachelor's degree in industrial engineering from UPR in Mayagüez and a master's and Ph.D. from the University of Central Florida. Dr. Centeno’s research and teaching focus on optimization-based modeling in service industries including healthcare, education, transportation, and entertainment. She has been recognized for her innovation in teaching and her efforts to promote women and ethics in STEM. In 2022, she was inducted as an IISE Fellow, which recognizes outstanding leaders that have made significant, nationally recognized contributions to industrial engineering profession.
Wilfrido A. Moreno P.E. University of South Florida
Wilfrido A. Moreno received his M.S.E.E & Ph.D. degrees in Electrical Engineering from the University of South Florida (USF), Tampa - Florida in 1985 and 1993 respectively. He is currently a Professor in the Electrical Engineering Department at the University of South Florida
Liliana M. Villavicencio University of South Florida
Abstract
This paper presents a comprehensive approach to designing a Mechatronics, Robotics, and Control (MRC) Lab, using Model-Based System Engineering (MBSE). This work is mainly motivated by the apparent need to train and develop a qualified workforce for the semiconductor industry as highlighted by the CHIPS Act. This work contributes to the enhancement of engineering education by employing MBSE tools that consider the complexity of the system and dynamically adapt to the needs of this, ever-evolving, field.
The paper demonstrates the use of No Magic Cameo Systems Modeler™ software to simulate and evaluate learning objectives and skills under various educational scenarios. These scenarios explore multiple practices for IoT and semiconductor manufacturing and focus on hands-on skills. This work leverages the partnership between academia and industry to ensure that the curriculum stays relevant and dynamically evolves by considering the latest trends in the field. This alignment is critical to equip talent that can immediately contribute to the new Smart Factories driven by Industry 5.0.
The paper summarizes the history and evolution of the CHIPS Act, highlighting significant government investment and the rapid growth in the ecosystem around these new technologies. A review of the current demands and challenges faced by the semiconductor industry is also included. More importantly, this work provides a roadmap for academic institutions, to establish laboratories and curricula that are not only in sync with current industry requirements but are also adaptive enough to accommodate future advancements.
Adoption and implementation of the presented tools will ensure that the next generation of STEM workers displays a blend of technical skills, soft skills, and digital capabilities needed due to rapid technological advancements and constantly changing work environments of the semiconductor industry.
Singh, P., & Quevedo, L. M., & Centeno, G., & Moreno, W. A., & Villavicencio, L. M. (2024, June), Model-Based System Engineering Applied to Designing Engineering Labs to Dynamically Adapt to Industry Trends - Case in Point: The Mechatronics, Robotics and Control Lab Paper presented at 2024 ASEE Annual Conference & Exposition, Portland, Oregon. https://peer.asee.org/47782
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