Research on Complex System GOMS Based on Plant Simulation
With the continuous deepening of industrialization,the production capacity of the production line is gradually improved,and the types of equipment failure in the production line are also increasing.Based on this,this paper establishes an optimization model of preventive maintenance strategy based on multiple failure modes of equip-ment.The maintenance modes of the model include minor repair,periodic preventive maintenance and replacement.In addition,during periodic preventive maintenance,group maintenance can be carried out for the failure modes with ad-jacent preventive maintenance time.Plant Simulation software was used to simulate the maintenance model.Due to the uncertainty of fault occurrence time,in order to eliminate the influence of uncertainty,a large number of simulation models need to be called,which reduces the computational efficiency.In this paper,artificial neural network is used to train the agent model to improve the computational efficiency of the maintenance model.Taking the maximum total profit as the objective function,genetic algorithm was used to optimize the preventive maintenance cycle and failure threshold.Finally,the effectiveness of the preventive maintenance strategy optimization model is verified by an exam-ple.
万方数据
维普
