A Joint Inspection-Based Preventive Maintenance and Spare Ordering Optimization Policy Using a Three-Stage Failure Process

Abstract

Separated decision-making for maintenance and spare ordering is unrealistic in the industry, so this paper aims to optimize them together. A joint policy of inspection-based preventive maintenance (PM) and spare ordering considering two modes of spare ordering, namely, a regular order and an emergency order, is proposed for single-unit systems using a three-stage failure process. If the system is recognized to be in the minor defective stage, the original inspection interval is shortened and a regular order is placed. However, replacement is undertaken preventively or correctively if the severe defective stage is identified or a failure occurs. Depending on the system state and the state of the regular ordered spare when replacement is needed, all possible scenarios are considered to construct optimization model I. The decision variables are the optimal inspection interval and the times of shortening the original inspection interval. Additionally, model II on the basis of an assumption that the spare is always ordered at time 0 is also developed. The results from a numerical example illustrated the applicability and the effectiveness of model compared to model II, and the irregular inspection policy is validated to be cost-saving compared to the regular inspection policy.

Joint optimization of inspection, maintenance, and spare ordering policy considering defective products loss

“…Based on this, we obtain the objective function of Model 2 and take T and θ as the decision variables. Zhao et al [26] adopted the same policy but did not take the defective items loss into consideration.…”

“…To illustrate our model, we consider the refractory lining of the blast furnace in a steel mill. According to [26], the three stages failure distribution form of the refractory lining is more appropriate to be described by the two-parameter Weibull distribution. The probability density function of the two-parameter Weibull distribution can be represented by (34), in which ε n and κ n are the scale parameter and shape parameter, respectively.…”

“…The chosen cost unit is 1 000 yuan and the chosen time unit is one day. Moreover, the failure distribution parameters, lead time parameters, and the majority of the cost parameters are adopted from literature [26]. Other parameters (see Table 3) can be obtained from historical information.…”

“…The delay-time concept was adopted by Wang [24,25] to model a joint inspection-based preventive maintenance and inventory strategy for multi-unit systems. The joint decision for a single-unit system with more than three discrete states was studied by Zhao et al [26,27], these two researches adopted an irregular inspection policy, and the two modes of spare ordering were introduced. However, the joint optimization models using a threestage failure process mentioned above did not consider the impact of system defects on product quality.…”

Joint Optimization in Condition-Based Maintenance and Inventory Policy for the Repairable System

“…But there is a regret that the system check cycle is not optimized. In reference [32], the researchers analyzed the sensitivity of the check cycle in the result analysis. However, check cycle is not included in the joint optimization calculation as one of the optimization objects.…”