A multi-agent negotiation-based decision framework for extensible product life cycle
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Extensible product life cycle (EPLC) strategy is proposed and studied in this dissertation. This could provide an answer to the problem of electronic waste (E-Waste) and help to lower product costs and improve environmental performance. The EPLC strategy is to reincarnate a product at component level through component sharing, thus formulating a product chain that extends and continues the life of an otherwise "obsolete" product in different industrial applications. Implementation of this strategy requires the manufacturers to schedule a product's extended life cycle early in the design phase, and optimize the design parameters considering the requirements of the manufacturers who will share the component in its extended life span. The research studied decision tasks and decision models of these tasks required by EPLC strategy. Multi-attribute utility analysis (MAUA) method is used in this research, since the decision problems generally have multiple attributes and are subject to uncertainty. Product design as well as other activities in manufacturing, reverse manufacturing and reverse logistics are modeled by MAUA method. An embedded life cycle assessment (LC A) approach is also developed in order to integrate environment concerns into the decision processes. To solve these interrelated and distributed decision problems in EPLC strategy, a distributed negotiation based decision framework is developed to locate the Pareto optimal set of the decision problem. This research focuses on the cooperative negotiation process with imperfect information among participating manufacturers associated with the extended life cycle, since it is the only way to obtain the optimal solution for the decision problems. The research provides a robust negotiation algorithm guided by a fuzzy inference engine. Decision noise in the negotiation process is also considered and modeled by mapping the decision process to a nonlinear dynamic system. A Dual Kalman filter is then used to filter the decision noise, improve the negotiation quality, and elicit preference structure of the decision agents. Examples of the decision framework are presented in the research to validate the developed system. Sensitivity analysis of the negotiation algorithm is also provided. In order to test the decision framework for EPLC, a case study of modular design of a PCB module used in a personal computer is discussed. Conclusions and directions for further research in EPLC are presented at the end of the dissertation. This research proposed a unique and innovative business model that addresses the problems in sustainable development and environmental hazards that challenge many of today's industries. It will provide a test bed for brainstorming in research in product design, manufacturing, and other industrial activities. It can also influence business infrastructures by providing directions in supply chain management, product design, and manufacturing. Successful implementation of the EPLC strategy will help industry deliver a more cost-saving and environmentally benign products and services to the market.
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