Research On Equipment Key Component Maintenance Decision-making Based On Reliability Simulation Analysis

With the advent of the "Intelligent Manufacturing Era" and the "Made in China 2025 Plan" proposed,manufactures have increasing demand for higher reliability of equipment.Therefore,in the context of increasing complex equipment structures,how to ensure longterm stable and reliable operation of equipment to increase productivity and reduce production costs has become a problem that plagues manufacturing companies.The reliability evaluation and maintenance decision-making for equipment and its key components are two important aspects of equipment health management,and also have significance for restoring equipment reliability and extending equipment life.Using scientific techniques to evaluate the reliability of key components of equipment and use it as a basis to formulate a proper maintenance strategy is an effective method to improve the reliability of the equipment and its key components.This paper starts with the reliability evaluation and maintenance decision-making of equipment key components.It establishes a reliability simulation model based on fault tree analysis to evaluate the reliability of equipment key components,and then establishes a maintenance cost model that considers reliability to determine the optimal maintenance time and maintenance object.This research aims at improving the reliability of equipment key components and minimizing the maintenance cost in the long-term operation process.There are academic research value and practical significance in this research.The main research content of this paper includes the following aspects.(1)Using Monte Carlo method,the fault tree analysis of key components of the equipment to be the simulation logic in order to perform the reliability simulation analysis of the key components composed of multiple parts,including the establishment of simulation models and the calculation of reliability indicators.Then,based on the Bayesian-Monte Carlo method,the failure distribution of each failure mode is finally determined through performing the goodness-of-fit test on the small-sample failure data,calculating the prior distribution and the posterior distribution of the parameters.(2)The key components consisting of multiple parts,and each part has multiple failure modes during its service life,and some failures have multiple states.So,based on the reliability simulation results of key components,considering that there is a correlation between the maintenance of the various faults in the same part,each time one or more faults are repaired by referring to the idea of opportunity maintenance,an optimization model for maintenance decision-making with the goal of minimizing the maintenance cost rate is established,and the maintenance threshold of each fault is optimized through a genetic algorithm in order to get the minimum maintenance cost rate of key components within the specified operating time.The model can finally give the optimal maintenance time point and maintenance object the validity and feasibility of the model are verified through the case.