Generative Artificial Intelligence in Industrial Engineering: Industry Applications and Educational Prospects

Nadiye O. Erdil

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Conference: 2025 ASEE Annual Conference & Exposition
Location: Montreal, Quebec, Canada
Publication Date: June 22, 2025
Start Date: June 22, 2025
End Date: August 15, 2025
Conference Session: Generative AI and Its Role in Industrial Engineering
Tagged Division: Industrial Engineering Division (IED)
Page Count: 14
Permanent URL: https://peer.asee.org/56643

Paper Authors

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Nadiye O. Erdil University of New Haven

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Nadiye O. Erdil is an associate professor of Industrial and Systems Engineering and Engineering and Operations Management at the University of New Haven. She teaches at the undergraduate and graduate level and has held various academic positions including administrative appointments. Her expertise spans engineering education, quality and productivity improvement through statistical tools, lean methods and application of information technology in operations management. Her research primarily focuses on manufacturing and healthcare delivery operations. Additionally, she has practical experience as a process engineer in the sheet metal manufacturing and pipe fabrication industry, where she worked for several years. She holds a Ph.D. in Industrial and Systems Engineering and M.S. in Industrial Engineering from Binghamton University (SUNY); and a Bachelor’s degree in Computer Engineering from Bogazici University.

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Abstract

First, online teaching took educators by storm due to the restrictions imposed by COVID-19. Now, Artificial Intelligence (AI), particularly generative AI (GAI), is prompting us to rethink our teaching pedagogies. Technological tools are being integrated into every aspect of our lives at lighting speed, and these tools are readily available to learners at their fingertips. The instructional approaches through which we were educated -and which most of us have been employing in our teaching- must be critically examined and updated to ensure effective teaching and learning in this new era. Beyond the clear need for AI integration in education, the growing influence of AI in industry is a significant driving force behind this necessity as it is essential to equip students with the knowledge and skills matching industry expectations.

GAI, as defined by ChatGPT -a conversational AI model developed by OpenAI-, “refers to a class of artificial intelligence models designed to create new content, such as text, image, audio, or video, that resembles human-generated data. These models "generate" content by learning patterns from large datasets during their training process”. Given its capabilities and rapid adoption across industries, integrating GAI into technical training may become essential for preparing students for the workforce.

With this in mind, this research aims to identify Industrial Engineering (IE) areas with significant GAI activity and use these insights to explore how IE education can be enhanced to better equip graduates for the evolving job market. As part of this study, this paper examined GAI applications in IE fields through a literature review guided by the PRISMA method. The findings highlighted GAI practices in both industry and education. In education, the use of ChatGPT as supportive instructional tool, particularly for course assessment, has emerged as a prominent trend, while in industry supply chain has stood out as a leading area for GAI adoption. To illustrate practical applications, hypothetical use cases were developed using ChatGPT and compiled in areas experiencing significant GAI growth. These cases were used as a basis for discussing opportunities to integrate GAI into IE education, with a focus on enhancing students’ technical skills. Additionally, the paper provides terminology, definitions and descriptions of commonly used GAI tools.

Citation
Format

Erdil, N. O. (2025, June), Generative Artificial Intelligence in Industrial Engineering: Industry Applications and Educational Prospects Paper presented at 2025 ASEE Annual Conference & Exposition , Montreal, Quebec, Canada . https://peer.asee.org/56643

TY - CPAPER
AB - First, online teaching took educators by storm due to the restrictions imposed by COVID-19. Now, Artificial Intelligence (AI), particularly generative AI (GAI), is prompting us to rethink our teaching pedagogies. Technological tools are being integrated into every aspect of our lives at lighting speed, and these tools are readily available to learners at their fingertips. The instructional approaches through which we were educated -and which most of us have been employing in our teaching- must be critically examined and updated to ensure effective teaching and learning in this new era. Beyond the clear need for AI integration in education, the growing influence of AI in industry is a significant driving force behind this necessity as it is essential to equip students with the knowledge and skills matching industry expectations.

GAI, as defined by ChatGPT -a conversational AI model developed by OpenAI-, “refers to a class of artificial intelligence models designed to create new content, such as text, image, audio, or video, that resembles human-generated data. These models &quot;generate&quot; content by learning patterns from large datasets during their training process”. Given its capabilities and rapid adoption across industries, integrating GAI into technical training may become essential for preparing students for the workforce.

With this in mind, this research aims to identify Industrial Engineering (IE) areas with significant GAI activity and use these insights to explore how IE education can be enhanced to better equip graduates for the evolving job market. As part of this study, this paper examined GAI applications in IE fields through a literature review guided by the PRISMA method. The findings highlighted GAI practices in both industry and education. In education, the use of ChatGPT as supportive instructional tool, particularly for course assessment, has emerged as a prominent trend, while in industry supply chain has stood out as a leading area for GAI adoption. To illustrate practical applications, hypothetical use cases were developed using ChatGPT and compiled in areas experiencing significant GAI growth. These cases were used as a basis for discussing opportunities to integrate GAI into IE education, with a focus on enhancing students’ technical skills. Additionally, the paper provides terminology, definitions and descriptions of commonly used GAI tools.

AU - Nadiye O. Erdil
CY - Montreal, Quebec, Canada
DA - 2025/06/22
PB - ASEE Conferences
TI - Generative Artificial Intelligence in Industrial Engineering: Industry Applications and Educational Prospects
UR - https://peer.asee.org/56643
ER -