Robust facility layout design for flexible manufacturing: a doe-based heuristic

Abstract

Flexible manufacturing systems (FMS) should be able to respond to changing manufacturing requirements and environments. From the layout point of view, FMS need to be rearranged to fit the new requirements. However, rearranging the layout is often undesirable due to its unpredicted high costs and production disruption. This paper proposes a practical approach to mitigate the effects and repercussions of changing environments and avoid rearranging the layout. A robust layout approach is presented, where changes in product demand and mix are absorbed by altering product routes and not rearranging the layout. In this approach, the problem is decomposed into two sub-problems: sub-problem 1 (SP1) where a robust layout is constructed, and sub-problem 2 (SP2) to obtain the best routes of products. To solve SP1, design of experiments is used to find a critical period, which is the period most affected under demand changes. Then, the layout for the critical period is determined using a hybridized genetic-tabu search algorithm. Then SP2 is solved by a branch and cut algorithm to obtain the optimal routes of the products in each period. The performance of the proposed methodology is illustrated using a case study and is benchmarked against rival ones from the literature.

KEYWORDS:

• Facilities layout
• flexible manufacturing
• robust design
• design of experiments
• metaheuristics

Disclosure statement

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

Additional information

Funding

This work was partially supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) under Discovery Grant RGPIN/06897-2017 awarded to the fourth author.

Notes on contributors

Hani Pourvaziri

Hani Pourvaziri received his B.Sc. and M.Sc. degrees in industrial engineering from QIAU University. In 2017, he started his Ph.D. program in computer science at Sigma Institute of the University of Clermont Auvergne and in 2021 he received his Ph.D. degree. His main research interests include facility layout-location problems, supply chain management, healthcare, mathematical modelling, optimization algorithms and simulation.

Saeideh Salimpour

Saeideh Salimpour received her B.Sc. degree in Electrical Engineering from Azad University-Central Tehran Branch in 2011, her M.Sc. degree in Industrial Engineering from Iran University of Science and Technology in 2014, and her Ph.D. degree in Industrial and Manufacturing Systems Engineering from University of Windsor in 2021. She was one of two graduate students in Ontario who was awarded the 2017 Ontario Society of Professional Engineers scholarship. She was also one of three female international students in Ontario, one of seven all Canada wide, in 2018 to receive the Delta Kappa Gamma Society International World Fellowship. On top of that, she has also received the University of Windsor Alumni Association award for International Students, Graduate Student Society Scholarship, and the International Student Society Bursary award. Saeideh was the recipient of the best presentation award at the 19th International Conference on Procurement, Logistics, and Supply Chain Management 2017 in Boston, USA. Her current research interests include Facility Layout Problems, Supply Chain Management, Production Planning and Scheduling, and Operations Research.

Seyed Taghi Akhavan Niaki

Seyed Taghi Akhavan Niaki is a distinguished Professor of Industrial Engineering at the Sharif University of Technology. His research interests are Quality Engineering, Applied Statistics, Simulation Modeling and Analysis, and Operations Research. He received his BSc in Industrial Engineering from the Sharif University of Technology in 1979, his Master’s and Ph.D. degrees in Industrial Engineering from West Virginia University in 1989 and 1992. He is the Editor-In-Chief of Scientia Iranica, the Editor of Scientia Iranica - Transactions E, the Editor-In-Chief of Sharif Journal of Industrial Engineering and Management (in Persian), the Board Member of several international journals, and a member of Alpha-Pi-Mu.

Ahmed Azab

Ahmed Azab, Ph.D., received his bachelor's and master's from the University of Cairo in Production Engineering; he earned his doctorate in Industrial & Manufacturing Systems Engineering from the University of Windsor. He is the Director of the Production & Operations Management Research Lab and Professor at the Department of Mechanical, Automotive, and Materials Engineering. He has been a recipient and nominee for international and national research awards. Dr. Azab’s research has been sponsored by National and Provincial granting agencies as well as direct industrial research funds. Dr. Azab is a registered Professional Engineer in the province of Ontario.