Layout optimization of injection process by considering integrated resilience engineering: a fuzzy-DEA approach

ABSTRACT

According to the impact of the layout design on the performance of high volumes production line, a single-row facility layout problem is considered in a process diagnosed as a bottleneck. In this regard, a discrete-event-simulation method is employed for modeling all possible layouts of an injection process. The results of the fuzzy simulation are imported to the output-oriented fuzzy data envelopment analysis (F-DEA) to rank different layouts as decision-making units. Then, the optimum layout is selected by considering the average waiting time and utility of resource as traditional key performance indicators, in addition to fault-tolerant, flexibility, and teamwork as resilience engineering (RE) factors. Also, the results are validated and verified by using some statistical tests. The sensitivity analysis is performed to find the most influential factor and weight of each factor. This is the first study to model the RE factors in the injection molding process by using the F-DEA method. Herein, a unique fuzzy mathematical-simulation model is tailored. Finally, the solution quality is pointed by a real case study in a refrigerator injection process of a home appliances company.

KEYWORDS:

• Injection molding process
• facility layout problem
• fuzzy simulation
• resilience engineering
• fuzzy data envelopment analysis

Acknowledgments

We would like to thank the blessed memory Professor Ali Azadeh (RIP), a brilliant guide, who provided insight and expertise that greatly assisted the research while doing this study.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

Fatemeh Navazi

Fatemeh Navazi is an Industrial Engineer. She obtained her B.Sc. and M.Sc degrees in Industrial Engineering from Alzahra University (2016) and at University of Tehran (2018), respectively. She has been a top rank student in her all grades. Her current research interests include mathematical modelling, location-routing problem, supply chain management, sustainability, simulation, IoT, DEA and data mining. She is really interested in fuzzy, possibilistic and robust solving methods, besides hybrid meta-heuristic algorithms.

[email protected]; Orcid: 0000-0001-7246-0303

Reza Tavakkoli-Moghaddam

Reza Tavakkoli-Moghaddam is a Professor of Industrial Engineering at the College of Engineering, University of Tehran in Iran. He obtained his Ph.D., M.Sc. and B.Sc. degrees in Industrial Engineering from Swinburne University of Technology in Melbourne (1998), University of Melbourne in Melbourne (1994), and Iran University of Science and Technology in Tehran (1989), respectively. He serves as the Editor-in-Chief of Journal of Industrial Engineering published by the University of Tehran and the Editorial Board member of nine reputable academic journals. He is the recipient of the 2009 and 2011 Distinguished Researcher Awards and the 2010 and 2014 Distinguished Applied Research Awards at University of Tehran, Iran. He has been selected as the National Iranian Distinguished Researcher in 2008 and 2010 by the MSRT (Ministry of Science, Research, and Technology) in Iran. He obtained the outstanding rank as the top 1% scientist and researcher in the world elite group. He has published 4 books, 20 book chapters, and more than 1000 journal and conference papers.

[email protected]; Orcid: 0000-0002-6757-926X

Pedram Memari

Pedram Memari is an Industrial Engineering. He obtained his B.Sc. and M.Sc. degree in Industrial Engineering from Urmia University of Tehnology (2016) and University of Tehran (2019), respectively. His research interests are scheduling, supply chain and inventory optimization problems in deterministic and stochastic cases, besides simulation, data mining and smart grids.

[email protected]; Orcid: 0000-0002-2916-2092