This paper adresses the problem of disassembly process planning taking into account the quality or states of the product to be disassembled. We propose an approach which is able to return the best disassembly level for a product considering the disassembly cost and the state of the product and/or the states of its subassemblies or components. The state of the product is represented using the concept of " Potentiel d'Utilisation Résiduel (PUR) " which is assumed to be a Gaussian random variable with known truncated distribution. A stochastic program is proposed to model the problem with the objective of maximizing the disassembly process profit. The latter is calculated as the difference between the positive revenue generated by recovered parts and the costs of the disassembly tasks. The revenue of a recovered part is a function of PUR. The developed approach is tested on two example case studies from the literature to analyze the impact of uncertain product quality on its disassembly process planning.
disassembly, partial disassembly, product quality, uncertainty
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