Abstract
Over the past 20 years, integrated decision making for production systems has gained the interest of researchers and practitioners. Many studies have shown that integrated decision making can lead to substantial amount of savings. Yet, a few research work has been conducted on the areas of integrated maintenance, production and quality in dynamic environments. This paper provides an integrated multi-period, maintenance, production and quality-inspection scheduling model, which is formulated as a Markov decision process. The model minimizes the total expected maintenance, production and quality inspection costs. The structural properties of the proposed model are mathematically investigated and with using sensitivity analysis, practical insights are also provided. We mathematically provide conditions to guarantee that the optimal inspection policy is monotone non-decreasing in the state of the machine. Furthermore, we show that the optimal production policy decreases by one unit as the state of inventory increases by one unit. Sensitivity analysis demonstrates that the production parameters affect both, maintenance and inspection decisions. In addition, the maintenance parameters affect inspection decisions. Finally, it is found that among the inspection parameters (i.e., cost-of-inspection and inspection-errors), type-II error mainly affects maintenance decisions.
Highlights
In today’s highly competitive business environment, driven by globalization and advances in production technology, companies adapt by increasing the efficiency of their production systems
Compared to previous research work, we developed an integrated model that considers multiple maintenance actions and quality inspection
The proposed model has the advantage of enabling integrated decision making under uncertainty
Summary
In today’s highly competitive business environment, driven by globalization and advances in production technology, companies adapt by increasing the efficiency of their production systems. Advanced production systems are complex and they are usually modelled as multi-state ones [2], [3]. This paper addresses a multi-state production system, and aims at finding the optimal maintenance, production and inspection decisions in a dynamic environment. Consider a multi-state deteriorating machine that produces items with imperfect quality to satisfy a random demand, the machine’s deterioration will be assumed to follow a discrete-time Markov chain. Maintenance, followed by production, and quality inspection decisions are assumed to be taken at discrete points in time. The main scientific contribution here is the development of an integrated Markov decision process (MDP) model, which addresses the maintenance, production and inspection for multi-state systems.
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