Abstract 

Providing appropriate maintenance policies for degrading products can help sustain good performance within the specified operating time without incurring overwhelming cost burdens. In practice, many manufacturers perceive upgrade as a strategic alternative to enhance product reliability and minimize maintenance costs. In this paper, we propose a maintenance strategy framework that integrates upgrade for stochastically degrading products. We consider two different scenarios that adapt to various manufacturer’s decision-making preferences. In the first scenario, the preventive maintenance (PM) target is fixed as a constant. In the second, the PM target is variable, which allows manufacturer to find the optimal policy via more flexible repair operations. In both scenarios, we establish maintenance models under a finite time horizon using a Markov decision process and study the structural properties of the optimal policy. We conclude that the optimal decision lies in employing a control limit policy among upgrade, PM and doing nothing. Numerical examples are then provided to illustrate the proposed methods. We find that with a variable PM target, the manufacturer is afforded greater flexibility, significantly reducing the expected cost. Additionally, when the target shifts from constant to variable, the trade-off among the three decisions of upgrade, PM, and doing nothing changes considerably