• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2019, Vol. 55 ›› Issue (17): 153-161.doi: 10.3901/JME.2019.17.153

• 数字化设计与制造 • 上一篇    下一篇

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基于属性映射的产品绿色设计方案优化方法

张雷, 杨凯, 张城, 秦旭, 赵希坤   

  1. 合肥工业大学机械工程学院 合肥 230009
  • 收稿日期:2018-07-11 修回日期:2018-12-18 出版日期:2019-09-05 发布日期:2020-01-07
  • 作者简介:张雷,男,1978年出生,博士,教授,博士研究生导师。主要研究方向为产品生命周期评价、环境意识下的产品设计、绿色制造。E-mail:zhlei@hfut.edu.cn;杨凯,男,1991年出生,硕士研究生。主要研究方向为产品生命周期评价,绿色设计及制造。E-mail:yangkaiw@163.com;张城,男,1990年出生,博士研究生。主要研究方向为产品绿色设计及制造。E-mail:zhangchengchina@163.com;秦旭,男,1991年出生,硕士研究生。主要研究方向为产品绿色设计及制造。E-mail:2412104630@qq.com;赵希坤,男,1992年出生,硕士研究生。主要研究方向为产品绿色设计及制造。E-mail:zhaoxikun1992@163.com
  • 基金资助:
    国家自然科学基金资助项目(51575152)。

Optimization Method of Product Green Design Scheme Based on Attribute Mapping

ZHANG Lei, YANG Kai, ZHANG Cheng, QIN Xu, ZHAO Xikun   

  1. School of Mechanical Engineering, Hefei University of Technology, Hefei 230009
  • Received:2018-07-11 Revised:2018-12-18 Online:2019-09-05 Published:2020-01-07

摘要: 针对产品绿色设计方案受多因素耦合影响,不易对其优化的问题,提出基于属性映射的产品绿色设计方案优化方法。基于产品功能结构分解模型,建立产品模块实例库,采用正交试验设计安排样本空间,基于支持矢量回归(Support vector regression,SVR)理论,对优化变量与优化目标间的映射关系进行拟合,进而建立产品设计方案多绿色属性与多模块功能实例之间的映射关系;采用非支配排序遗传算法(Non-dominated sorting genetic algorithm II,NSGA-II),选取绿色属性最优的产品设计方案作为目标,对离散变量进行多目标优化,从众多可能解中快速、准确的寻出Pareto解集,从而生成产品绿色设计优化方案。以喷墨打印机产品绿色设计方案优化为例,验证了所提方法的可行性和有效性。

关键词: 属性映射, 绿色设计, 方案优化, NSGA-II, 支持矢量回归

Abstract: Due to the influences of multi-factors coupling on the green design of products, it is not easy to optimize the green design scheme. An optimization method of product green design scheme based on attribute mapping is proposed. By decomposing the function and structure of product, the product module instance library is established. The sample space is arranged by orthogonal experimental design. Using the support vector regression(SVR)theory to fit the mapping relationship between optimization variables and optimization objectives and establish the mapping relationship between the green attributes of products' design scheme and module function instance; Taking the optimal green attributes of products' design scheme as the goal and combining the non-dominated sorting genetic algorithm II (NSGA-II) to carry out the multi-objective optimization of discrete variables so that the Pareto solution set can be quickly and accurately found from many possible solutions and the optimized green product design schemes are obtained. Finally, the feasibility and effectiveness of the proposed method are verified by taking the green design scheme generation of a ink jet printer as the case.

Key words: attribute mapping, green design, scheme optimization, NSGA-II, support vector regression

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