Transactions on Data Analysis in Social Science

Transactions on Data Analysis in Social Science

Integration of Production Planning and Non-Cyclic Preventive Maintenance Scheduling for Multi-State Systems

Document Type : Original Article

Authors
M. Haghdoust Komayi
S. I. Seyyedi
Payame Noor University, Kish Branch, Kish, Iran
10.47176/TDASS.2024.198
Abstract
In various levels of manufacturing sectors, it is commonly assumed that preventive maintenance (PM) directly affects production scheduling and machine availability (i.e., reducing downtime). Surprisingly, however, the interaction between these factors is often overlooked. Maintenance planning is generally classified into cyclic and non-cyclic approaches. Among these, non-cyclic strategies provide more realistic and effective plans. The core principles of maintenance management advocate for implementing non-cyclic preventive actions in processes while minimizing corrective repairs and component replacements. This perspective simultaneously enables informed decision-making regarding both preventive maintenance and the corresponding production schedules. The integrated strategy of monitoring and preventive maintenance aims to fulfill production plans while minimizing the total associated costs including those related to maintenance (both preventive and corrective), setup, support, and production. This study proposes the integration of non-cyclic preventive maintenance scheduling with production planning in a multi-component system environment. An integrated model is developed to optimize decisions related to both maintenance and production scheduling. To efficiently solve the model and achieve high-quality solutions within a reasonable computation time, the Simulated Annealing (SA) metaheuristic algorithm is employed.
Keywords
Non-Cyclic Preventive Maintenance Planning
Production Planning and Scheduling
Metaheuristic Algorithms
Simulated Annealing Algorithm
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Transactions on Data Analysis in Social Science
Volume 6, Issue 3
Summer 2024
Pages 198-210

  • Receive Date 01 July 2024
  • Revise Date 29 August 2024
  • Accept Date 27 September 2024