A Condition-Based Maintenance Policy (CBM) Of Multi-Component Deteriorating Systems Based On Quality Information

The problems in the maintenance field are the key factors affecting the development of military,industrial,aviation,etc.Effective maintenance management not only ensures timely maintenance of equipment maintenance activities,but also reduces inventory capital occupation and improves economic efficiency.It is very important to develop maintenance control strategies reasonably and effectively to improve maintenance efficiency.With the development of computers and related information technology,the traditional single maintenance mode has gradually exposed its shortcomings,causing a series of adverse consequences in actual work.On the one hand,over-maintenance leads to a reduction in the effective use of equipment,and the human,material,and financial resources are relatively wasteful,and frequent maintenance is more likely to cause failure.On the other hand,maintenance is insufficient.Due to the limitations of the maintenance plan,machines must be operated with diseases.Maintenance costs and unnecessary accidental loss due to fault degradation are sometimes increased.Therefore,the analysis of condition-based maintenance decision-making has always been one of the hot spots in the field of maintenance.This paper studies the maintenance strategy of parallel production system,assuming that the product failure rate is obtained through continuous monitoring,and the degree of degradation of the machine is indirectly characterized by the failure rate.The maintenance strategy proposed in this paper involves two thresholds l_m and l_a that trigger different maintenance behaviors.And the genetic algorithm determines the optimal threshold corresponding to the minimum expected total cost.The specific content and conclusions are as follows:(1)Based on the continuous monitoring system,a condition-based maintenance strategy involving two thresholds l_m and l_a is proposed.When the failure rate exceeds a certain threshold,the corresponding maintenance behavior is implemented.It can be seen that the threshold is closely related to the implementation type and frequency of maintenance behavior.It also introduces the maintenance model of the single-component non-repairable system,and then extends the single component to the multi-component repairable system to establish the expected total cost model through analysis and probability calculation.The cost model,which considers the cost mainly includes downtime costs,failure costs,and component costs.(2)Based on the established maintenance model and cost model,the numerical example of single component system is introduced.The numerical simulation is carried out using MATLAB,and the genetic algorithm is used to optimize,the sensitivity of the cost to determine the operating cost parameter.Then consider the two-component parallel system and multi-component parallel system.Because different maintenance costs vary greatly during actual maintenance,optimization calculations are carried out under different maintenance costs,and the results are analyzed rationally.(3)A strategy combining maintenance and spare parts replacement is proposed to jointly optimize condition-based maintenance and spare parts management.The stochastic system is randomly degraded and continuously monitored.The spare parts supply uses the(S-1,S)type inventory strategy.According to the proposed strategy,the replacement of the components is determined according to the actual degree of degradation.The replacement of spare parts occurs according to the requirements of the spare parts.And using the Monte Carlo simulation method to simulate the proposed maintenance and spare parts replacement strategy.As a result,spare parts inventory management and condition-based maintenance replacement of components can be optimized.A numerical example is used to illustrate this model.