New Information-Based Replacement Policies for Heterogeneous Populations of ‘Aging’ and ‘Non-Aging’ Items

It is well-known that preventive maintenance can be effective only for aging (e.g., with increasing failure rate) items. Counter-intuitively, we show that it is not the case in heterogeneous populations consisting of subpopulations of items with constant and even decreasing failure rates. However, the focus of the paper is on the case with increasing failure rates of items and a new multi-stage procedure with periodic replacements is proposed. Between consecutive periodic replacements, the failures are minimally repaired and the information on the numbers of minimal repairs in relevant intervals of time becomes a decision parameter in the corresponding optimization problems. For instance, for the 2-stage policy, an item is replaced at the optimally obtained time if the number of minimal repairs at this time is larger than the optimally obtained value. Otherwise, the replacement is postponed until the optimally obtained time. The proposed maintenance policy can be effective because the large number of minimal repairs indicates that the corresponding failure rate is relatively large and vice versa. Theoretical results and numerical illustrations justify the proposed approach. It will be shown that the application of the proposed maintenance policy can decrease the long-run average cost rate compared with the conventional replacement policy when the population is heterogeneous.