当前位置: X-MOL 学术J. Intell. Manuf. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
A data-driven method of selective disassembly planning at end-of-life under uncertainty
Journal of Intelligent Manufacturing ( IF 8.3 ) Pub Date : 2021-07-28 , DOI: 10.1007/s10845-021-01812-0
Yicong Gao 1 , Shanhe Lou 1 , Jianrong Tan 1 , Hao Zheng 2
Affiliation  

Selective disassembly is a systematic method to remove target components or high-valuable components from an EOL product for reuse, recycling and remanufacturing as quick and feasible as possible, which plays a key role for the effective application of circular economy. However, in practice, the process of selective disassembly is usually characterized by various unpredictable factors of EOL products. It is very difficult to identify a feasible disassembly sequence for getting the target components before taking actions due to the uncertainty. In this paper, a data-driven method of selective disassembly planning for EOL products under uncertainty is proposed, in which disassemblability is regarded as the degree of difficulty in removing components under uncertainty. Taxonomy of uncertainty metrics that represents uncertain characteristics of components and disassembly transitions of selective disassembly is established. Random and fuzzy assessment data of uncertainty is converted into qualitative values and aggregated to fit a prediction model based on the trapezium cloud model. The turning time of disassemblability is predicted for a given set of certainty degree. Further, the disassemblability values are applied to determine the best selective disassembly sequence in order to get target component with tradeoff between minimum number of disassembly operations and maximum feasibility. The effectiveness of the proposed method is illustrated by a numerical example. Moreover, by comparing to selective disassembly planning without considering uncertainty, the proposed method turns selective disassembly of EOL products more realistic than 11% and provide insights on how to design product to facilitate disassembly operations.



中文翻译:

一种数据驱动的不确定性下寿命结束时的选择性拆卸计划方法

选择性拆解是一种系统化的方法,将EOL产品中的目标部件或高价值部件尽可能快速、可行地进行再利用、回收和再制造,对循环经济的有效应用具有关键作用。然而,在实践中,选择性拆解的过程通常会受到EOL产品的各种不可预测因素的影响。由于不确定性,很难在采取行动之前确定可行的拆卸顺序以获得目标组件。本文提出了一种数据驱动的不确定条件下EOL产品的选择性拆卸规划方法,其中将可拆卸性视为不确定条件下拆卸组件的难易程度。建立了代表部件的不确定特性和选择性拆卸的拆卸转换的不确定性度量的分类。不确定性的随机和模糊评估数据被转换为定性值并聚合以拟合基于梯形云模型的预测模型。对于给定的一组确定性,可预测可拆卸性的转向时间。此外,可拆卸性值用于确定最佳选择性拆卸顺序,以便在最少拆卸操作次数和最大可行性之间进行权衡来获得目标组件。通过数值例子说明了所提出方法的有效性。此外,通过与不考虑不确定性的选择性拆卸计划相比,

更新日期:2021-07-28
down
wechat
bug