Abstract

The purpose of this work is to efficiently design a disassembly line, as disassembly system, handling variability of End-of-Life (EoL) product quality as well as uncertainty of disassembly process operations and provides an optimal revenue of such a system. The main finding of this work is the development of a decision tool that allows decision-makers to choose the best disassembly process and disassembly depth, while assigning the corresponding tasks to the line workstations under precedence and cycle time constraints. Task times are assumed to be random variables with known normal probability distributions. Presence of hazardous material is considered and line cycle time constraints are to be jointly satisfied with at least a certain service (probability) level set by the decision-maker. The revenue of a product part depends explicitly on its EoL state or quality. Industrial applicability is shown using an industrial case focused on remanufacturing of mechatronic parts in the automotive industry.

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