Research On Integrated Preventive Maintenance And Scheduling Optimization With Machine Deterioration

In the new production mode produced by modern manufacturing system,preventive maintenance and production scheduling can be jointly decided.So effectively integrating preventive maintenance and production scheduling has an important impact on the economic efficiency and market competitiveness of enterprises.In the actual manufacturing system,machine failure is a major factor affecting the normal execution of the production plan.How to solve the coupling contradiction between equipment maintenance plan and production plan,and construct effective integration optimization strategy and method,is becoming a hot issue concerned by academic circles and business circles.In a single machine manufacturing system with deteriorating effect,the actual processing time of the operation will be greatly increased due to the continuous deterioration of the machine state and random failure.In the event of a machine failure,the system performs minimal repair(MR).In order to reduce the level of deterioration and the risk of failure,the system performs regular preventive maintenance(PM).Based on the assumption that the machine failure obeys the Weibull distribution and the linear deterioration of the machine state,by analyzing the influence of the above factors on the production efficiency of the system,the problem of integrated optimization of preventive maintenance and production scheduling with the goal of minimizing the total expected cost of maintenance and production is studied.The main research work includes the following aspects:1.The problem of independent decision-making for PM and production scheduling is studied.Firstly,according to the relevant parameters of the machine fault Weibull function and the time of executing MR and PM,the optimal PM cycle is derived.Then the optimal job scheduling sequence is developed according to the fixed PM period.2.Research on the integration optimization problem of reliability-based PM and production scheduling.This thesis takes the scheduling sequence of PM and job as decision variables,and establishes a mathematical model with minimizing MR,PM and E/T costs as the objective function.And we design a solution algorithm based on genetic algorithm.3.Based on the above research work,a flexible PM strategy is proposed,which allows the execution interval of two PM to change within a certain time range.Thus,a usability-based PM and production scheduling integration optimization model is established to solve this problem.An improved genetic algorithm is designed to solve this model.Through a series of simulation examples of different scales,this thesis validates the validity of the above models and algorithms,and summarizes the advantages and disadvantages of the three models.