Applications of delay time theory to maintenance practice of complex plant

This thesis is concerned with investigating and understanding the role and consequence of different modelling options and parameter estimation options for modelling a complex plant. As systems become more complicated and required new technologies and methodologies, more sophisticated maintenance models and control policies are need to solve the maintenance problems. The initial chapter introduces the review of previous work on a single component system and multi-component system. Although in recent years there has been a shift in the maintenance literature from consideration of single items to systems composed of several components, so far only a few papers have tackled the modelling of actual multi-component plant. In the third chapter, delay time concept and analysis technique have been presented. Of particularly importance are parameter estimation methods, namely the objective method and the subjective methods. In the fourth chapter the component PM model and the system PM model for downtimes and costs based upon various PM policies are discussed. The key options within maintenance modelling are to determine regular Minspection periods for the system modelled as a whole, and to determine the periods for the plant as a set of separate component models. An extension to the downtime model is presented for the case when the downtime due to failures within system is not small, and impacts upon the estimate of the number of failures arising over a specified time zone. In the following chapter, we address parameter estimation methods using simulated data, and assess the ability of estimation techniques to capture the true parameter values. Particular attention is paid to the problem arising during the parameter estimating process because of the inadequate recording of PM data and implied correlation between model parameters. Finally, a case study is presented of maintenance modelling of production plant in a local company with view to improving current practice. The model developed is based upon the delay time concept where because of an absence of PM data, using the results of earlier chapters, the process parameters and the delay time distribution were estimated from failure data only using the method of maximum likelihood. The modelling was repeated based upon subjective assessmentosf parameter,a nd considerablec onsistencyw ith the objectively based case obtained. For the plant study, modelling indicated the current PM inspection program was ineffective. A snap-shot approach is then applied to assess other ways of reducing the downtime, and the possibility of improving the PM inspection practice. This leads to readily adapted improvements.