Joint Optimization of Opportunistic Predictive Maintenance and Multi-location Spare Part Inventories for a Deteriorating System Considering Imperfect Actions

TL;DR

This paper introduces a comprehensive model for optimizing spare parts inventory and predictive maintenance in multi-location systems, considering imperfect actions and event-driven inspections to improve availability and reduce costs.

Contribution

It presents a novel joint optimization model integrating spare parts logistics and condition-based maintenance with an event-driven inspection policy under imperfect maintenance conditions.

Findings

Optimized policies improve system availability and reduce costs.

Event-driven inspections prevent unnecessary maintenance actions.

Monte Carlo simulation effectively evaluates the proposed model.

Abstract

Considering the close interaction between spare parts logistics and maintenance planning, this paper presents a model for joint optimization of multi-location spare parts supply chain and condition-based maintenance under predictive and opportunistic approaches. Simultaneous use of the imperfect maintenance actions and innovative policy on spare part ordering, which is defined based on the deterioration characteristic of the system, is a significant contribution to the research. This paper also proposes the method to determine the inspection time which not only considers restraints of the both maintenance and spare parts provision policies, but also uses an event-driven approach in order to prevent unnecessary inspections. Defined decision variables such reliability, upper limit for spare parts order quantity, preventive maintenance threshold, re-ordering level of degradation, and the maximum level of successive imperfect actions will be optimized via stochastic Monte-Carlo simulation. The optimization follows two objectives: (1) system should reach the expected availability which helps decision makers apply the opportunistic approach (2) and cost rate function as an objective function must be minimized. To illustrate the use of the proposed model, a numerical example and its results finally is presented. Key words: maintenance, multi-location supply chain, spare parts inventory, imperfect maintenance, predictive inspection, opportunistic approach, availability, reliability