Efficacy of Project Based Learning Approach in Upskilling Manufacturing Professionals in Industry 4.0 Technologies

Prakruthi Hareesh; Arunkarthik Thangaraj

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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: Manufacturing Division (MFG) Technical Session 8
Tagged Division: Manufacturing Division (MFG)
Page Count: 12
Permanent URL: https://peer.asee.org/56324

Paper Authors

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Prakruthi Hareesh Birla Institute of Technology and Science

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Dr. Prakruthi Hareesh is an Assistant Professor at BITS Pilani, Work Integrated Learning Programs. She has a Ph.D. in Mechanical Engineering from the University of Maryland, College Park, USA. Dr. Hareesh is the program lead for Smart Manufacturing at BITS Pilani, WILP and works closely with leading manufacturing industries in the country. She has designed several programs in this area through close interaction with the industry. She is a strong advocate of project-based learning and emphasizes the practical implementation of theoretical concepts in the workplace. Consequently, her labs are state-of-the-art. She has mentored over 35 digitalization projects in the manufacturing sector.

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Arunkarthik Thangaraj Birla Institute of Technology and Science

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Abstract

This paper discusses the application of project-based learning (PjBL) within the context of Industry 4.0 to solve digital transformation challenges in manufacturing. Although PjBL is beginning to be recognized more widely in academic circles as the method that supports active learning through the practical application of theoretical knowledge, its effectiveness in higher education, particularly within the manufacturing sector, is underexplored. This paper fills this gap by assessing the impact of a 6-month certification program, offered to one of the world's largest steel manufacturers by a prestigious university in the country, aimed at developing critical Industry 4.0 competences for experienced manufacturing professionals lacking knowledge in digital technologies.

The curriculum for the program was developed in collaboration with industry leaders, informed by insights from on-site visits to manufacturing plants where areas of existing process pain points were identified, which guided customizable learning modules in technologies such as mechatronics, IoT, big data analytics, machine learning, and cybersecurity. It was divided into two phases of training. The foundation knowledge, through the first three months, was combined with hands-on labs and industry-relevant applications. In doing so, participants could gain actual understanding of digital technologies.

The second phase of the program transitioned participants to real-time projects from industries such as defect detection using computer vision, energy optimization, material property prediction, and IoT-based predictive maintenance. Throughout this phase, training was specialized to further assist participants in implementing projects to meet organizational requirements identified during earlier research.

The technical quality of the solutions as well as its impact on organizational performance were the technical criteria by which the program assessed participants' ability to translate theoretical knowledge into practical solutions with measurable impact. Concretely, this resulted in less machine downtime and cost savings for each project, some close to $3.5 million annually, which will be detailed in the full paper. The PjBL methodology, with its emphasis on real-time problem-solving and immediate feedback, accelerated the participants’ acquisition of digital skills and facilitated meaningful, hands-on learning experiences.

This study provides clear evidence for PjBL, particularly by the fact that critical issues facing professionals who had no prior experience with digital systems were overcome successfully through critical thinking, problem-solving, and teamwork. The authors look forward to sharing valuable insights from this study, for academic and industrial stakeholders seeking to develop workforce skills in Industry 4.0 technologies, at the ASEE 2025 conference.

Citation
Format

Hareesh, P., & Thangaraj, A. (2025, June), Efficacy of Project Based Learning Approach in Upskilling Manufacturing Professionals in Industry 4.0 Technologies Paper presented at 2025 ASEE Annual Conference & Exposition , Montreal, Quebec, Canada . https://peer.asee.org/56324

TY  - CPAPER
AB  - This paper discusses the application of project-based learning (PjBL) within the context of Industry 4.0 to solve digital transformation challenges in manufacturing. Although PjBL is beginning to be recognized more widely in academic circles as the method that supports active learning through the practical application of theoretical knowledge, its effectiveness in higher education, particularly within the manufacturing sector, is underexplored. This paper fills this gap by assessing the impact of a 6-month certification program, offered to one of the world&#39;s largest steel manufacturers by a prestigious university in the country, aimed at developing critical Industry 4.0 competences for experienced manufacturing professionals lacking knowledge in digital technologies.

The curriculum for the program was developed in collaboration with industry leaders, informed by insights from on-site visits to manufacturing plants where areas of existing process pain points were identified, which guided customizable learning modules in technologies such as mechatronics, IoT, big data analytics, machine learning, and cybersecurity. It was divided into two phases of training. The foundation knowledge, through the first three months, was combined with hands-on labs and industry-relevant applications. In doing so, participants could gain actual understanding of digital technologies.

The second phase of the program transitioned participants to real-time projects from industries such as defect detection using computer vision, energy optimization, material property prediction, and IoT-based predictive maintenance. Throughout this phase, training was specialized to further assist participants in implementing projects to meet organizational requirements identified during earlier research. 

The technical quality of the solutions as well as its impact on organizational performance were the technical criteria by which the program assessed participants&#39; ability to translate theoretical knowledge into practical solutions with measurable impact. Concretely, this resulted in less machine downtime and cost savings for each project, some close to $3.5 million annually, which will be detailed in the full paper. The PjBL methodology, with its emphasis on real-time problem-solving and immediate feedback, accelerated the participants’ acquisition of digital skills and facilitated meaningful, hands-on learning experiences.

This study provides clear evidence for PjBL, particularly by the fact that critical issues facing professionals who had no prior experience with digital systems were overcome successfully through critical thinking, problem-solving, and teamwork. The authors look forward to sharing valuable insights from this study, for academic and industrial stakeholders seeking to develop workforce skills in Industry 4.0 technologies, at the ASEE 2025 conference.

AU  - Prakruthi Hareesh
AU  - Arunkarthik Thangaraj
CY  - Montreal, Quebec, Canada 
DA  - 2025/06/22
PB  - ASEE Conferences
TI  - Efficacy of Project Based Learning Approach in Upskilling Manufacturing Professionals in Industry 4.0 Technologies
UR  - https://peer.asee.org/56324
ER  -