Unequal area facility layout problem-solving: a real case study on an air-conditioner production shop floor

Abstract

Solving facility layout problems aims at identifying the optimal plan for placing a number of facilities or departments on a shop floor considering multiple optimisation criteria and constraints. Recently, the unequal area facility layout problem (UA-FLP) has drawn more attention as it is closer to real industrial scenarios. To address this problem, the typical UA-FLP in an air-conditioner production shop floor is analysed, and then a modified non-dominated sorting genetic algorithm (NSGA-II) is developed to identify the optimal layout plan considering the material handling cost (MHC) and the closeness rating score (CRS). NSGA-II is a stable algorithm for engineering applications and has an encoding structure of chromosomes that can express facility layout expediently. Besides that, the two objectives (MHC and CRS) that are conflicting might be another reason for adopting NSGA-II. During the process, the crossover and mutation operators of NSGA-II are modified based on the non-overlapping method, which reduces the time cost for eliminating unsuitable layout plans. The modified NSGA-II is compared with two related algorithms, and the results show that it has better performance on the UA-FLP with a large number of departments.

KEYWORDS:

• Unequal area facility layout problem
• multi-objective optimisation
• NSGA-II
• air-conditioner production shop floor
• case study

Disclosure statement

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

Data availability statement

The authors confirm that the primary data supporting the findings of this study are available within the article. Some irrelevant details are eliminated because of the commercial restrictions, but the details do not affect the layout solutions.

Additional information

Funding

This research is supported by the Natural Science Foundation of Shaanxi Province [grant number 2021JQ-037] and the National Science Foundation of China [grant number 51975464].

Notes on contributors

Wei Guo

Wei Guo is currently working as an Assistant Professor at the State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University. He received his Ph.D. degree in Xi’an Jiaotong University in 2019. His research interests include social manufacturing, product–service system, Lean Production, operations research, etc.

Pingyu Jiang

Pingyu Jiang currently works as a Professor at the State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University. Jiang does research in Mechanical Engineering and Industrial Engineering. His Research Areas are manufacturing and service systems engineering, including social manufacturing, service-oriented MES, iPSS, Lean Production, RFID-based cyber-physical-social systems, product collaborative design, production process quality control, e-manufacturing, etc.

Maolin Yang

Maolin Yang received the B.S. degree in Mechanical Engineering from Tongji University in 2012, and M.S. degree in Industrial Engineering from Shanghai University of Engineering Science in 2015. Currently, he is pursuing the Ph.D. degree in the School of Mechanical Engineering at Xi’an Jiaotong University, China. His research interests include knowledge engineering, optimisation algorithm, social manufacturing, etc.