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

Morteza Soltani|arXiv (Cornell University)|Oct 15, 2018

Reliability and Maintenance Optimization4 citations

TL;DR

This paper proposes a joint optimization model for predictive maintenance and multi-location spare part inventories in deteriorating systems, integrating imperfect maintenance actions and event-driven inspection scheduling. Using stochastic Monte Carlo simulation, it optimizes reliability, maintenance thresholds, and spare part order quantities to balance system availability and minimize cost rates, with a key contribution being the coordination of maintenance and logistics under imperfect actions.

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

Motivation & Objective

• To address the interdependence between spare parts logistics and maintenance planning in multi-location systems.
• To model and optimize the impact of imperfect maintenance actions on system reliability and inventory costs.
• To develop an event-driven inspection policy that reduces unnecessary inspections while maintaining system availability.
• To jointly optimize maintenance thresholds, spare part order quantities, and reliability targets under stochastic deterioration.
• To minimize the long-run cost rate while ensuring the system achieves a target availability level through opportunistic maintenance.

Proposed method

• The model uses a stochastic Monte Carlo simulation to evaluate system performance under various decision variables.
• It defines decision variables including preventive maintenance thresholds, maximum successive imperfect actions, and reordering levels based on degradation.
• An event-driven inspection policy is introduced to trigger inspections only when degradation reaches critical levels, avoiding redundant checks.
• The system's reliability is modeled as a function of maintenance actions and degradation progression.
• The cost rate function is minimized subject to a target availability constraint, using simulation-based optimization.
• The approach integrates predictive maintenance with multi-location spare part inventory control, considering both logistics and maintenance imperfections.

Experimental results

Research questions

• RQ1 How can predictive maintenance and spare part inventory be jointly optimized to minimize system cost while maintaining target availability?
• RQ2 What is the optimal inspection policy that avoids unnecessary checks while ensuring timely maintenance actions?
• RQ3 How do imperfect maintenance actions affect long-term system reliability and inventory requirements?
• RQ4 What is the impact of opportunistic maintenance on spare part ordering and overall cost efficiency?
• RQ5 How can degradation-based ordering policies improve system performance in multi-location settings?

Key findings

• The joint optimization model successfully balances system availability and cost rate, achieving the target availability level with minimal cost.
• The event-driven inspection policy significantly reduces the number of inspections compared to periodic approaches, without compromising system reliability.
• Optimal preventive maintenance thresholds and spare part order quantities are highly sensitive to the level of maintenance imperfection.
• The model demonstrates that integrating maintenance and inventory decisions leads to lower total cost rates than isolated optimization.
• The simulation results show that limiting successive imperfect actions improves long-term system reliability and reduces emergency repair frequency.
• The proposed policy achieves a 15% reduction in total cost rate compared to baseline periodic maintenance and fixed-order policies.