Bayesian Estimation for the Reuse of Mechanical Parts Using Part Agents

To realize effective reuse of mechanical parts for the development of a sustainable society, it is essential to manage individual parts over their entire life cycle. Product users have difficulties carrying out appropriate maintenance on the multitude and variety of parts in their products. Addressing these considerations, we propose a scheme whereby a part manages itself and supports user maintenance activities. In previous work, we proposed and developed an application of Bayesian estimation to a part agent system that advises a user regarding the replacement of hard disk drives (HDDs). In this study, we create a Bayesian network on the deterioration of the HDD to find the probability of an unobservable event. We also discuss the application of this method to life cycle simulation performed by part agents.