Life Cycle Simulation of Mechanical Parts with Part Agents Considering User Behavior

To realize the effective reuse of mechanical parts for the development of a sustainable society, it is essential to effectively manage individual parts over their entire life cycle. For this purpose, we are developing a part agent system using network agents. A part agent manages all information about a part throughout its life cycle and predicts possible states of the part in the near future in order to generate appropriate recommendations for their maintenance. User behavior is important for this prediction because, in the life cycle of a part, its states are affected by the user behavior. The behavior of users is modeled using prospect theory in order to simulate its nature so as to avoid the risk of failure. This paper compares the decisions for maintenance actions in the simulations with and without applying prospect theory. The initial results are presented in a life cycle simulation of the developed part agents.