2023 ASEE Annual Conference & Exposition

Exploring Systems Performance Using Modeling and Simulation – Project-based Study and Teaching

Presented at Project-Based and Experiential Learning in Manufacturing

Modeling and Simulation (M&S) provides a risk-free environment allowing the users to experiment in a computer-generated virtual platform and analyze the what-if scenarios for effective decision support systems. Due to its pervasive usefulness, the concept of M&S is widely used across many sectors, including manufacturing, warehouse operations, supply chain, logistics, transportation, mining, and many more. The field of M&S requires computer-intensive and software-based training, which is very different from teaching in a regular classroom setting. Hence, we develop a three-stage (mimic-guide-scaffold) project-based teaching strategy to enhance students learning experience in M&S education. Here, students first follow the instructor to understand basics of simulation and become familiar with AnyLogic software. Second, the students work on a group project under the passive supervision of the instructor to enhance their problem-solving capability. In the third step, students work independently on a similar but extensive project to scaffold their knowledge. The project was designed to answer three high-level key research questions for a hospital system including systems throughput, resource utilization, and patients’ length of stay reduction. We performed a thorough evaluation using an anonymous survey, where thirty-one students participated to provide their feedback. This paper provides a detailed description of the projects including problem statements, learning objectives, evaluation rubrics, data collection criteria, and evaluation outcomes with detailed discussion.

Authors

Dr. Md Fashiar Rahman http://orcid.org/0000-0002-0437-2587 The University of Texas at El Paso [biography]

Dr. Md Fashiar Rahman is an Assistant Professor of the Industrial, Manufacturing and Systems Engineering (IMSE) Department at The University of Texas at El Paso. He holds a Ph.D. degree in Computational Science Program. He has years of research experience in different projects in the field of image data mining, machine learning, deep learning, and Computer Simulation for industrial and healthcare applications. In addition, Dr. Rahman has taught various engineering courses in industrial and manufacturing engineering. His research covers advanced quality technology, AI applications in smart manufacturing, health care applications, and computational intelligence/data analytics.
Dr. Aditya Akundi http://orcid.org/0000-0002-8656-7002 The University of Texas Rio Grande Valley [biography]

ADITYA AKUNDI is an assistant professor in the department of Informatics and Engineering
Systems at theUniversity of Texas Rio Grande Valley (UTRGV). Dr. Akundi received hisPhDat the University of Texas at El Paso (UTEP) in 2016. In his doctoral thesis, he investigated the use of information theory to understand and assess complex socio-technical systems. Before joining UTRGV, he worked as a research assistant professor in the Industrial Manufacturing and Systems Engineering department at UTEP for a period of three years from 2016 to 2019. Dr. Akundi published several papers in the field of systems modeling, systems testing, assessing INCOSE Handbook, model-based systems engineering, and engineering education. His research has received funding from the National Science Foundation (NSF) and is currently an I-DREAM4D Department of Defense (D0D) Fellow at
UTRGV.He is a member of INCOSE and ASEE. He received the outstanding junior faculty award from the ASEE Manufacturing division in 2017 and 2018 and currently serves as the program chair of the ASEE manufacturing division.
Jakia Sultana University of Texas at El Paso [biography]

Jakia Sultana, currently a Ph.D. candidate in Teaching, Learning, and Culture with a focus on STEM education, is also serving as a Research Associate dedicated to enhancing the educational journey of minority students in engineering fields. Her research is centered on developing and integrating effective methodologies within engineering education to improve teaching and learning practices, particularly for minorities. By identifying and implementing innovative strategies, she aims to seamlessly incorporate engineering education into curricula, thus elevating the academic experience for minority students in diverse settings. Jakia's work is characterized by a unique blend of passion and insight, drawing from her academic and research background to enrich the engineering education discourse. Her commitment lies in pushing the boundaries of traditional education to foster a more inclusive and understanding environment for minority students in engineering disciplines across U.S. universities.
Prof. Tzu-Liang Bill Tseng University of Texas at El Paso [biography]

Dr. Bill Tseng is a Professor and Chair of Department of Industrial, Manufacturing and Systems Engineering at the UTEP. He is also a Director of Research Institute for Manufacturing & Engineering Systems, the host institute of Texas Manufacturing Assistance Center at UTEP. He received his two MSIE degrees (MFG & DS/OR) from the University of Wisconsin at Madison and Ph.D. in Industrial Engineering from the University of Iowa. Dr. Tseng is also a Certified Manufacturing Engineer from Society of Manufacturing Engineers. Dr. Tseng’s research area cover emergency management, systems engineering, computational intelligence/data analytics and cyber engineering technology. Over the years, he has served more than 10 million dollars as principle investigators sponsored by NSF, NIST, USDT, DoEd, KSEF and industry like LMCO, GM and Tyco Inc. Dr. Tseng delivered research results to many refereed journals such as IEEE Transactions, IIE Transactions, International Journal of Production Research, Journal of Manufacturing Systems, Expert Systems with Applications and other conferences (over 260 refereed publications). He is currently serving as an editor of Journal of Computer Standards & Interfaces (CSI) and editor boards of International Journal of Data Mining, Modeling and Management (JDMMM) and American Journal of Industrial and Business Management (AJIBM). He is currently a Senior Member of Institute of Industrial Engineers, Society of Manufacturing Engineers and the Division Chair of Manufacturing Division of American Society of Engineering Education (ASEE). He is also actively involved in several consortia activities.
Dr. Amit J. Lopes [biography]

Dr. Lopes' research interests focus on additive manufacturing and its applications. His research also includes Service Systems Engineering applications to additive manufacturing, healthcare, and energy systems. He is also interested in the application of
Sergio Luna http://orcid.org/0000-0003-3058-410X University of Texas at El Paso

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