Integrated just-in-time production and imperfect maintenance management considering random quality degradation

Modern manufacturing systems face challenges due to their unpredictable nature and limited output capacity. This paper proposes an integrated production and maintenance model to address these challenges, aiming to optimize system performance while minimizing costs. The primary aim is to develop a novel control policy that combines just-in-time (JIT) production strategies and imperfect maintenance policies. To achieve this, we develop a comprehensive model that incorporates stochastic processes, such as the Ornstein-Uhlenbeck process, to capture the random nature of defect generation. Differential equations are utilized to simulate material flow and logical processes within the production system. Through extensive numerical simulations and sensitivity analyses, we explore the influence of various cost parameters and stochastic process parameters on system behavior. Additionally, the sensitivity analysis of Ornstein-Uhlenbeck process parameters sheds light on their role in defect generation and system performance. Furthermore, the analysis highlights the economic advantages of the proposed control policy, emphasizing the importance of optimizing inventory levels. In conclusion, our study provides valuable insights into the design and optimization of integrated production and maintenance systems with stochastic dynamics.