A Sustainable Decision-Making Framework for Production System Resilience: Optimizing Maintenance, Repair, and Replacement Policies

Articles in Press

Document Type : Original Article

Author
Omid Zolfaghar Beigy
School of Industrial Engineering, K. N. Toosi University of Technology (KNTU), Tehran, Iran.
10.22034/he.2026.589044.1240
Abstract
With the increasing complexity of manufacturing systems and the growing emphasis on sustainable development, optimizing production and maintenance policies has become essential for improving equipment reliability, reducing operational costs, and enhancing resource efficiency. This study develops an optimal control model based on a Semi-Markov Decision Process (SMDP) to jointly determine production, maintenance, repair, overhaul, preventive maintenance, and production outsourcing policies in a deteriorating manufacturing system. The proposed model explicitly incorporates the effects of equipment deterioration on production quality, system reliability, defective products, inventory level, and operational costs. An instantaneous cost function and a value function are formulated to derive optimal control policies that minimize the expected long-term discounted cost of the system. A simulation framework is also implemented to evaluate the model under different operational conditions and maintenance scenarios. The findings indicate that integrating production and maintenance decisions improves system reliability, reduces defective production, minimizes resource waste, and enhances lifecycle cost efficiency. Furthermore, the coordinated use of preventive maintenance, overhaul, and production outsourcing helps maintain production capacity while ensuring an efficient response to demand under equipment deterioration. From a human ecology perspective, the proposed framework promotes sustainable manufacturing through more efficient resource utilization, extended equipment service life, reduced industrial waste, and improved operational resilience. Consequently, the proposed model provides an effective decision-support tool for managers seeking to balance economic performance with the long-term sustainability of manufacturing systems.
Keywords
Stochastic Dynamic Programming
Sustainable production Systems
Industrial Ecology
Resource Efficiency
System Resilience
Subjects
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Human Ecology

Articles in Press, Accepted Manuscript
Available Online from 08 July 2026