Smart Manufacturing Course: Proposed and Executed Curriculum Integrating Modern Digital Tools into Chemical Engineering Education

The paradigm shift into an era of Industry 4.0, also referred to as the fourth Industrial Revolution, has emphasized the need for intelligent networking between process equipment and industrial processes themselves. This has brought on an age of research and framework development for smart manufacturing in the name of Industry 4.0 [1]. While the physical and digital advancements towards smart manufacturing integration are substantial the inclusion of engineers themselves amongst this shift is often less considered [2]. There are educational efforts in Europe to create and implement smart manufacturing curriculum for non-traditional or adult learners already integrated in the workforce, but attention is also needed on a next generation smart manufacturing curriculum for pre-career students [3]. We, the teaching team of CHE 554: Smart Manufacturing at Purdue University, developed and implemented a curriculum geared towards the training of undergraduate, graduate, and non-traditional students in methods of smart manufacturing as they apply directly to industrial scenarios. Through this elective course, taught primarily through the context of chemical engineering but enrolling students from other disciplines, we introduce concepts not covered in its entirety by the core engineering curriculum. Our course includes but is not limited to material on data reconciliation, machine learning, chemometrics, data-driven fault detection, digital twin development, and process optimization. Further, these concepts are executed through the context of open-source Python packages, enabling the accessible and practical application of smart manufacturing in the form of assignments and in the context of professional application in the future [4,5]. The integration of modern tools and Python libraries connects academic solutions to industrial challenges with industrial practice becoming evident for students who would otherwise be unaware of these resources. With the creation and implementation of the Purdue University Smart Manufacturing elective course, we help develop a uniquely prepared and technologically educated generation of engineering students capable of bringing Smart Manufacturing capabilities to industry. This helps catalyze smart manufacturing knowledge transfer where all enrolled students are given the tools to apply their knowledge mastery to their specific engineering discipline and industrial application.

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Publication Details

Journal
Systems and Control Transactions
Published
2025-06-30
DOI
https://doi.org/10.69997/sct.199586
Primary Topic
Experimental Learning in Engineering
Type
article
Field-Weighted Citation Impact
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article

Smart Manufacturing Course: Proposed and Executed Curriculum Integrating Modern Digital Tools into Chemical Engineering Education

Gintaras V. Reklaitis, Joseph F. Pekny, Zoltan K. Nagy, Montgomery D. Laky
Systems and Control Transactions
Experimental Learning in Engineering
article

Smart Manufacturing Course: Proposed and Executed Curriculum Integrating Modern Digital Tools into Chemical Engineering Education

Gintaras V. Reklaitis, Joseph F. Pekny, Zoltan K. Nagy, Montgomery D. Laky
article en

Abstract

The paradigm shift into an era of Industry 4.0, also referred to as the fourth Industrial Revolution, has emphasized the need for intelligent networking between process equipment and industrial processes themselves. This has brought on an age of research and framework development for smart manufacturing in the name of Industry 4.0 [1]. While the physical and digital advancements towards smart manufacturing integration are substantial the inclusion of engineers themselves amongst this shift is often less considered [2]. There are educational efforts in Europe to create and implement smart manufacturing curriculum for non-traditional or adult learners already integrated in the workforce, but attention is also needed on a next generation smart manufacturing curriculum for pre-career students [3]. We, the teaching team of CHE 554: Smart Manufacturing at Purdue University, developed and implemented a curriculum geared towards the training of undergraduate, graduate, and non-traditional students in methods of smart manufacturing as they apply directly to industrial scenarios. Through this elective course, taught primarily through the context of chemical engineering but enrolling students from other disciplines, we introduce concepts not covered in its entirety by the core engineering curriculum. Our course includes but is not limited to material on data reconciliation, machine learning, chemometrics, data-driven fault detection, digital twin development, and process optimization. Further, these concepts are executed through the context of open-source Python packages, enabling the accessible and practical application of smart manufacturing in the form of assignments and in the context of professional application in the future [4,5]. The integration of modern tools and Python libraries connects academic solutions to industrial challenges with industrial practice becoming evident for students who would otherwise be unaware of these resources. With the creation and implementation of the Purdue University Smart Manufacturing elective course, we help develop a uniquely prepared and technologically educated generation of engineering students capable of bringing Smart Manufacturing capabilities to industry. This helps catalyze smart manufacturing knowledge transfer where all enrolled students are given the tools to apply their knowledge mastery to their specific engineering discipline and industrial application.

Systems and Control TransactionsVol. 4
Purdue University West Lafayette (US)
Openalex Percentile: Top 79%
Experimental Learning in Engineering
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