Maintenance is the activity applied over the longest period within the product lifecycle, requiring maintenance service providers to manage business strategies over extended durations. The service provider must decide type of maintenance method, IT technologies and create workforce design which meet business targets within acceptable risk. Maintenance has evolved with a primary focus on reliability and cost. However, in recent years, stakeholders have increasingly demanded diverse values from maintenance, such as contributions to environmental and social goals. Simultaneously, the growing uncertainty in business and asset operation environment may cause changes in objectives throughout the lifecycle. Furthermore, advancements in technologies such as AI and the accumulation of asset knowledge through the maintenance activity also drives changes in applicable maintenance method within the lifetime. Under these circumstances, there is a need to establish maintenance strategies planning method which flexibly adapts to changes in business environments during the lifecycle to consistently meet stakeholder demands. This study examines the framework for adaptive maintenance consulting methods aimed at promoting the growth of maintenance businesses throughout the product lifecycle. We aim to support the development of maintenance strategy with a maturity model for realizing the change by introducing guidance based on expert knowledge into co-operative workshops through a maintenance service menu. Additionally, we introduce AI-assisted reliability knowledge generation and maintenance KPI simulation to enable the formulation of feasible and validated maintenance strategies that reflect the characteristics of equipment and maintenance operation.
Kono et al. (Thu,) studied this question.