A Meta-Model-Based Life Consumption Monitoring Method for Efficient Decision-Making of PSSs

• Main Authors: Huang, Chao, Bu, Siqi, Kong, Shu Wa, Lee, Hiu Hung
• Format: Conference Proceeding
• Language: English
• Subjects: Decision making; life consumption monitoring; Maintenance; meta-models; Predictive models; product-service systems; Real-time systems; Reliability engineering; Uncertainty; Warranties
• ISSN: 2166-5656
• DOI: 10.1109/ICPHM61352.2024.10626818

Product-service systems (PSSs) represent innovative business models for manufacturers, providing customers with an integrated bundle of products and services. In the context of PSSs, manufacturers are required to embrace prognostics and health management (PHM) technology to effectively maximize product performance and net profit. The industry holds a preference for life consumption monitoring (LCM) as a PHM method due to its physical interpretability and its ability to be applied in situations where field run-to-failure data may be unavailable. Nevertheless, the utilization of LCM entails conducting time-consuming simulations to account for uncertainty, thereby impeding the decision-making efficiency of the PSS. Meta-models, which can approximate the behavior of complex models efficiently, facilitating faster prediction, optimization, or exploration of the solution space. To enhance the decision-making efficiency of the PSS, this study introduces a meta-model-based LCM (MM-LCM) method by incorporating meta-models into the existing LCM method. By harnessing the efficient assessment capability of the MM-LCM, the decision-making regarding product material selection and warranty services can be effectively determined during the pre-service phase. Furthermore, leveraging the realtime damage monitoring capability of the MM-LCM, field maintenance actions can be arranged. The feasibility of the method is substantiated through numerical experiments.