290
Views
1
CrossRef citations to date
0
Altmetric
Articles

An integrated approach to joint production planning and reliability-based multi-level preventive maintenance scheduling optimisation for a deteriorating system considering due-date satisfaction

ORCID Icon, ORCID Icon & ORCID Icon
Pages 489-511 | Received 11 Nov 2020, Accepted 05 Jun 2021, Published online: 18 Jun 2021
 

Abstract

This paper presents a new bi-objective model to deal with an integrated production planning and reliability-based multi-level preventive maintenance (PM) scheduling problem. The production system includes a set of parallel deteriorating machines. The model aims to find the production lot sizes and the sequence and interval of PM activities over a multi-shift planning horizon. The PM activities are classified as the adjustment and replacement ones, each of which has a specific cost and effect on machines. The model serves to minimise the total cost while maximising customer satisfaction. Also, the most profitable customers are identified by applying a hybrid multi-attribute decision making (MADM) approach (BWM-TOPSIS) in order to fulfil their orders in their desirable time windows. Three efficient meta-heuristic algorithms are developed to solve the proposed model for large-scale problems. Besides, TOPSIS method is employed to select the most desirable solution among the obtained Pareto solutions. Finally, a case study is provided to show the applicability of the proposed approach.

Disclosure statement

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

Additional information

Notes on contributors

Hassan Gharoun

Hassan Gharoun received a master degree in Industrial Engineering from University of Tehran and bachelor's degree in Industrial Engineering from Kharazmi University of Tehran, Iran. He dedicated his thesis to application of datamining in condition-based maintenance, and he has published conference papers in various fields. His research interests include maintenance optimization, scheduling, simulation, and data mining.

Mahdi Hamid

Mahdi Hamid is a PhD candidate in the field of Industrial Engineering in the School of Industrial Engineering, College of Engineering, University of Tehran, Iran. He earned BSc degree from K. N. Toosi University of Technology and MSc degree from University of Tehran both in Industrial Engineering. He has published several journal and conference papers in various fields. His research interests include safety, optimization, scheduling, simulation, healthcare systems, smart logistics, and data analysis.

S. Ali Torabi

S. Ali Torabi is an Associate Professor in the School of Industrial Engineering, College of Engineering, University of Tehran, Iran. He received his PhD in Industrial Engineering in 2004 from Amirkabir University of Technology, Iran. He received his MSc and BSc in Industrial Engineering from Iran University of Science and Technology and Amirkabir University of Technology, respectively. He has published many papers in accredited journals, such as Transportation Research Part E: Logistics and Transportation Review, International Journal of Production Research, Journal of the Operational Research Society, Fuzzy Sets and Systems, Computers & Operations Research, and European Journal of Operational Research. Dr. Torabi has had different academic experiences with well-reputed universities such as Brunel Business School and DeGroote School of Business. He is now cooperating with University of Tehran as the Head of a research center on supply chain management, and Research Deputy at School of Industrial Engineering, College of Engineering, University of Tehran, Iran. His research areas also include operations research, MCDM methods, project management, and logistics.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.