Reliability Analysis And Maintenance Decision-making Method Of Multi-machine For Failure Process

The stabilization of enterprise manufacturing system is one of the key problems to restrict the quality of production and the rapid response to market. The stabilization of equipment is the basis of manufacturing system's stabilization, and its two key factors are the reliable analysis of operational reliability of equipment and the suitable maintenance plan of equipment. Based on the failure data of machine, a unified framework for reliability analysis and maintenance-decision of multi-machine is proposed firstly by this dissertation. Firstly, this thesis provides a systematic literature review on the theories, methods and research situations for reliability analysis and maintenance decision model about single machine and manufacturing system and its related fields. Then, several new methods addressing how to make the reliability analysis and maintenance-decision of multi-machine are implemented as follows:(1)The characteristic of machine failure data is illuminated, which is similar to the characteristic of repeated measurement data and recurrent event data. GLMM model used widely in medical and biological field are proposed. Unlike the classical single machine reliability model, this model has ability to handle the heterogeneity of same type equipment and the self-correlation of repeated measurement. Furthermore, the theory and computational method of parameter estimation and a new method of goodness-of-fit are discussed in detail. In general, this model can provide the reliability changing trend for both the population and each individual machine.(2)Similar to the above linear model, reliability analysis model for multiple machine is built based on proportion intensity model and nonlinear mixed-effects model, which takes account of the influence to the reliability of machine caused by the maintenance effect and deterioration level. Furthermore, the theory and computational method of parameter estimation are discussed in detail. Specially, related engineering information of equipment is considered by this model; Not only quantitative assessment of maintenance effect but also analytical solution of related reliability index for both the population and each individual machine is provided by this model.(3)It is brought forward that selective maintenance decision model has the advantage of solving the production line maintenance decision-making problem in engineering. ARI₁ and ARI_∞model, two kinds of arithmetic reduction of intensity model, are combined with selective maintenance method for the first time. The influence on machine failure intensity by different maintenance actions (PM, minimal repair, overhaul) is described. Furthermore, a maintenance decision-making model for multi-machine system is built based on constraint programming and a resolution algorithm is provided by combining the greedy heuristic rules with genetic algorithm. Finally, a case study is provided.(4)The computational method of mixed failure rate base on age reduction factor and hazard rate increase factor is discussed. The mixed failure rate model is combined with selective maintenance optimizing method for the first time.Then, the influence on machine failure rate by different maintenance actions (PM, minimal repair, overhaul) is provided. Furthermore, a maintenance decision-making model for mutil-machine system is built based on constraint programming and a resolution algorithm is provided by combining the heuristic rules with tabu search. Finally, a case study is provided.(5)A maintenance decision-making analysis system of machining line in car engine plant is designed and developed based on the research founding above. Industrial Ethernet network is the hardware base of this system, and popular architecture is adopted as the software architecture of this system. The popular architecture makes it has good extension and across platform. Its Ethernet network, software architecture, function modules and some running case are presented in detail.Finally, a conclusion is drawn and the trend on maintenance decision-making model of manufacturing system is anticipated.