Quantifying and exhibiting the congruence of process choice criteria with traditional and additive manufacturing systems

Abstract

A well-determined manufacturing system helps organisations achieve a desired competitive advantage. So, the manufacturing system selection concerns the critical decision of manufacturing strategy deployment. In the present era of industry 4.0, there exist four traditional manufacturing systems (TMS) (i.e. job-shop, batch-shop, mass, and continuous) and additive manufacturing system (AMS). Different process choice criteria (PCC) are responsible for selecting the best-suited system from five or a hybrid (AMS + TMS) configuration. This research formulates a two-stage framework comprising Delphi and Voting analytical hierarchy process (VAHP) techniques for quantifying the congruence between PCC and manufacturing systems. Initially, extant literature is reviewed to identify the critical PCC and further validated by industry experts through Delphi. This results in retaining thirty-six PCC. The relative importance of an individual criterion concerning a particular manufacturing system is computed using VAHP in the second stage to understand the alignment of PCC in different manufacturing systems for exhibiting the congruence between PCC and manufacturing system (TPS and AMS). The findings offer critical insights about the different PCC and their level-of-fit in TMS and AMS, which can assist researchers and practitioners in evaluating a suitable manufacturing system for an organisation using identified PCC.

Keywords:

• Manufacturing systems
• manufacturing strategy
• congruence
• process choice criteria
• Delphi
• voting AHP

Acknowledgements

The authors acknowledge the support provided by the Digital Manufacturing Lab (DML), National Institute of Industrial Engineering (NITIE), Mumbai, to conduct this work. The authors express their sincere gratitude to the anonymous reviewers for their fruitful comments that helped enhance the quality of the manuscript. Finally, the authors are sincerely grateful to all the 100 experts for providing their valuable insights and responses to conduct this study.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The authors confirm that the data supporting the findings of this study are available within the article and its supplementary materials.

Additional information

Notes on contributors

Vishwas Dohale

Vishwas Dohale is currently working as a Business Consultant at the renowned Goldratt Consulting India Pvt Ltd. He received the Doctoral Research Fellowship (Ph.D.) in Operations and Supply Chain Management (O&SCM) from the National Institute of Industrial Engineering (NITIE), Mumbai, India. He is a recipient of the Best Thesis Award (Doctoral Dissertation Competition) from the renowned IEOM society conference, Dhaka Chapter (IMEOM – 2022). He completed his M.E. in CAD/CAM and Robotics from the University of Mumbai. His research interest is in areas like Manufacturing Strategy, Production System Management, Supply Chain Strategy and Risk Management, Industrial Engineering, Optimizations, Simulations and Modelling, Multi-Criteria Decision Making, Machine Learning. He has published his research in the journals of repute, namely International Journal of Production Economics, International Journal of Production Research, Annals of Operations Research, International Journal of Physical Distribution and Logistics Management, Industrial Management & Data Systems, Computers & Industrial Engineering, International Journal of Logistics Management, Benchmarking and many reputed national and international conferences such as POMS, NCIETM, ISDSI, SOM, ICIE, IAMOT, IEEM, ICAME, and IEOM.

Milind Akarte

Dr. Milind Akarte is a Professor of Industrial Engineering at the NITIE, Mumbai, India. He has earned his master’s degree in IEOR and Ph.D. in Mechanical Engineering from IIT, Bombay. His research areas include Manufacturing Strategy, Additive Manufacturing, Smart Manufacturing, and Operations and Supply Chain Management. He is a recipient of a research grant from the SERC, DST for the project ‘Benchmarking of hybrid tooling methods (Rapid Prototyping and Tooling) for metal casting’. He has published more than 40 technical papers and guided 6 Ph.D. candidates and over 50+ master’s students. He has also carried out industry consulting and executive training programs.

Angappa Gunasekaran

Dr. Angappa Gunasekaran is a Director and Professor of the School of Business Administration at the Penn State Harrisburg, PA, USA. Prior to this, he served as the Special Assistant to the Provost for Academic Affairs and Student Success and served as Dean of the School of Business and Public Administration from 2017 to 2021 at California State University, Bakersfield. He was the Dean of the Charlton College of Business from 2013 to 2017, Chairperson of the Department of Decision and Information Sciences from 2006 to 2012, and the founding Director of Business Innovation Research Centre (BIRC) from 2006 to 2017 at the University of Massachusetts, Dartmouth. He has over 400 articles published in peer-reviewed journals. He has presented and published 50 articles in conferences and given several invited talks in many countries. He is on the Editorial Board of over 30 peer-reviewed journals. He has organised several international workshops and conferences in the popular areas of operations management.

Priyanka Verma

Dr. Priyanka Verma is a Faculty Member in Operations and Supply Chain Management area of the National Institute of Industrial Engineering (NITIE), Mumbai. Her teaching and research interest includes Logistics and Supply Chain Management, Optimisation, Facility Planning, Project Resilience and Manufacturing Strategy modelling. She has published in journals of repute like International Journal of Production Economics, International Journal of Production Research, Computers and Industrial Engineering, International Journal of Physical Distribution & Logistics Management, Production Planning and Control, to name a few. She has presented her research in National and International conferences organised by PMI, POMS, IEEE, ISDSI, IEOM, ORSI, SOM, etc.