Generalized stationary models for scheduling single and multiple preventive maintenance routines

This paper is concerned with the development and application of stationary models for scheduling single and multiple preventive maintenance (PM) situations focusing on issues of model implementation. The first part of the paper deals with the practical implementation of the basic single PM scheduling model based on the renewal process. The main practical difficulty is lifetime-distribution selection for small data sets which is typical in PM situations. Thus a sensitivity analysis of optimal PM interval to selected life distributions following PM and failures (corrective maintenance) is carried out. It has been found that the selected pair of distributions using AIC criteria as well as the Weibull–Weibull fitted pair have the smallest availability loss in estimating the optimal PM interval. The second part of this paper is concerned with modelling multi-PM situations – something which has received very little attention in the literature despite its frequent implementation in real life. A multi-PM model based on the renewal process is discussed. The model assumes a multi-PM interval which is an integer multiple of the single PM intervals and different renewal functions following each type of PM. The procedure of model implementation is discussed through numerical example.