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Abstract: This paper investigates the problem of parallel disassembly with the consideration of fuzziness. A novel approach is proposed based on optimized dispatching for parallel disassembly in which disassembly time is characterized by the fuzzy sets due to inevitable uncertainties. The proposed approach consists of three parts: in the first part, the fuzzy time-based dispatching disassembly process model is established; in the second part, the boundary conditions of the fuzzy time and the disassembly are derived, and the components’ disassembly order and available stations are encoded together to find the optimal disassembly path; in the final part, the approach is optimized by using genetic algorithm (GA) to minimize the total time and cost, and the solution is compared with other algorithms. Finally, a case study for a hydraulic press disassembly is presented to verify the effectiveness and feasibility of the proposed approach.

The work investigates an interesting disassembly problem with the two objectives: minimizing disassembly time and minimizing disassembly cost. A GA algorithm is proposed to solve this problem. A real case study is conducted to evaluate the proposed algorithm.

一种基于混合模糊模型的新型并行拆卸设计 方法

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