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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.

Additive Manufacturing (AM) has become an enticing and rapidly growing manufacturing method for the production of components due to its unique advantages over conventional manufacturing (CM), including complex geometric capabilities and functional features. Sustainability concerns for AM products are still among the major technological challenges. A holistic sustainability analysis of such products covering the entire life cycle is lacking in the current literature. This paper presents the total life cycle sustainability analysis of AM products, through the recently established Product Sustainability Index ( ProdSI ) framework. A case study is presented with two iterations of AM product validating the ProdSI metrics for AM products.

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. For that purpose, we are developing a part agent system using network agents. This paper describes a method for a part agent to predict possible states of its corresponding part in the near future. Bayesian network is applied to estimate a failure probability of the part and a simple deterioration model is applied to evaluate properties of the part. Initial results are shown on a life cycle simulation of the developed part agent.

In order to integrate sustainability in the development of content-packaging combinations, the consequences of decisions for the entire life cycle need to be analyzed in early stages of the development process. To adequately underpin these decisions, several aspects, for example the economic and the environmental impact, need to be assessed. A so-called actor network is developed to support designers in decision making. This publication examines practical use situations of this actor network tool based on information from research partners. Scenarios are written in order to depict requirements for the actor network tool, considering different users and functionalities.