A data deficiency based parameter estimating problem and case study in delay time PM modeling

Abstract This paper describes a modeling study of preventive maintenance (PM) policy of production plant in a local company with a view to improving current practice. The model developed is based upon the delay time concept where because of an absence of PM data, the process parameters and the delay time distribution were estimated from failure data only using the method of maximum likelihood. Particular attention is paid to the problem arising during the parameter estimating process because of the inadequate recording of PM data and the implied correlation between model parameters. An objective estimation process has been adopted here as far as possible. The case of data deficiency explored in the study is important because it is a relatively general situation in practice. An inspection model is finally proposed to identify the best inspection policy based upon the estimated model parameters and the delay time distribution. It is concluded that the company has other problems to attend to before the inspection problem is finally solved, and a structured review of maintenance engineering practice is recommended.