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In response to the increased used product disposal and scarcity of natural resources, the end-of-life (EOL) management has now becoming an important research field in manufacturing systems. The recovery operations for implementation are now more complicated than the traditional manufacturing as uncertainty of numerous sources do always exist. The process of selecting an appropriate combination of used components for a manufactured product is known as the product recovery configuration. For product recovery configuration selections, there are several possible alternatives, such as those parts and/or components to be reused, rebuilt, recycled and disposed. Each of these disposition alternatives may need to undergo various manufacturing processes in the industries. Due to the complexities of recovery operations, current recovery decision models focus mainly on the assessment in terms of cost, time, waste and quality separately. This article presents an integrated model to determine an optimal recovery plan for a manufacturer, which is to maximize its recovery value when producing a remanufactured product by considering practical constraints of the manufacturing lead-time, waste and quality as a whole. In the numerical example, the optimization model was solved using genetic algorithm. The obtained results showed that the selection of different product recovery configurations might have direct impact on the achievable recovery value of a remanufactured product for the manufacturer. Finally, the future works and contributions of this study are also briefly discussed. © 2016 The Authors.
Kuik et al. (2016) studied this question.