Taking complexity into account: A structured literature review on multi-component systems in the context of predictive maintenance

Abstract

One of the most prominent use cases of a digitized industry is predictive maintenance. Advances in sensor and data technology enable continuous condition monitoring, thus, extending the opportunities for predictive maintenance. However, so far, most approaches stick to a simplistic paradigm viewing industrial systems as a single-component system (SCS), assuming independence or partially neglecting interdependencies between components. However, in practice, multiple components are coupled which interact with each other; thus, leading to a multi-component system (MCS) view. Implementing the MCS is challenging, but promises many advantages for predictive maintenance. We conduct a structured literature review to investigate the current state of research about MCS and how this can be transferred to data-driven predictive maintenance. We investigate the characteristics of MCS, the promises in contrast to SCS, the challenges of its implementation, and current application areas. Finally, we discuss future work on MCS in the context of predictive maintenance.