Abstract
Disassembly is a systematic method to separate an end-of-life product into its constituent parts and components. However, the disassembly process of products can experience great uncertainty due to a variety of unpredictable factors. To deal with such uncertainty, this work proposes a novel probability analysis method of disassembly cost with random removal time and different removal labor cost. According to different constraints and actual execution of disassembly, it presents typical probability evaluation models of disassembly cost. Moreover, a solution algorithm based on stochastic simulation is used to solve the proposed probability models. Some numerical examples are given to illustrate the proposed concepts and the effectiveness of the proposed algorithm.
Note to Practitioners-This paper deals with the uncertainty management problem of product disassembly. To do so, this work proposes a novel probability analysis method of disassembly cost subject to random removal time and different removal labor cost. Previously, such a problem is handled through a methodology based on probabilistic planning and expected value analysis, which is ineffective without considering the probability problem of completing a disassembly task. The goal of this work is to propose some probability evaluation models for disassembly cost with different constraints. Both theoretical and simulation results demonstrate that the proposed approach can perform effectively the quantitative analysis of a disassembly process. Such results can be used to guide disassembly decision makers in making right disassembly decisions.