چكيده به لاتين
one of the important points in most organizations is to pay attention to the important category of high reliability. Further attention to the life of the equipment will increase the range of maintenance and preventive repairs, which has led to the recognition and use of optimized maintenance and preventive repairs. Weak maintenance and preventative repairs are obstacles to organizational progress. Optimizing maintenance and preventative repairs reduces programming shutdowns, reduces value-free tasks, increases targeted actions, and reduces maintenance hours. The main task of this dissertation is the net optimization system. Defects lead to equipment failures, interruptions in production, and even reduced product quality, and virtually every time production stops, it requires a high cost to restart. The aim of this dissertation is to use the Markov chain for the relationship between maintenance and repair controls in the event of equipment failure. The proposed method, with a MINLP model and its reduction, brings the repair management system to an optimal and better state. This MILP model, with its optimistic (high) estimation, also shows the balance between reliability and cost-effectiveness of the inspection and maintenance strategy in unit selection. It offers a new solution within the framework of the Markov decision-making process. For each time period, this model optimizes the set of maintenance and repair controls in different modes and achieves the optimal control policy. The proposed model has been simulated and implemented by MATLAB for a period of 12 to 72 months. And the results show the high efficiency of the proposed method compared to the existing methods.
