Keywords: product recovery, end-of-life vehicles, ELV, decision support systems, DSS, Bayesian networks, influence diagrams, EOL vehicles, vehicle components, component recovery, automotive remanufacturing, sustainable manufacturing, sustainability, product information, RFID tags, radio frequency identification, sensor networks, reusable components, disassembly
A Bayesian decision support system for vehicle component recovery
This paper presents a decision support system (DSS) whose core is based on Bayes' networks and influence diagrams that helps remanufacturers to choose the best product recovery option on the basis of the information provided by emerging technologies such as RFID tags and sensor networks. Such technologies can have significant impact on the effectiveness with which product information is generated and shared among the various actors in the product lifecycle. As an illustration, we show how such a DSS can be used to improve the effectiveness of decisions made by vehicle remanufacturers where one needs to select reusable components for disassembly before shredding an end-of-life vehicle.