基于虚拟正交试验和改进QFD的产品平台规划方法

doi:10.16183/j.cnki.jsjtu.2018.08.008

摘要/Abstract

摘要： 敏感度分析是考虑设计参数对性能的影响进行产品平台规划的方法，而对于性能参数与设计参数之间不存在明确数学函数的产品，目前的敏感度分析方法难以适用.针对这一不足，提出了基于虚拟正交试验的敏感度分析方法，并结合改进QFD进行产品平台规划.首先，基于正交试验设计法确定虚拟试验方案；其次利用内置软件搭建虚拟试验环境，设置不同取值的设计参数并实时记录性能参数的变化，以两种参数的变化量之比为基础计算设计参数敏感度，构建敏感度矩阵，代替传统QFD质量屋中的关联关系矩阵衡量设计参数与性能参数间的关联程度，降低传统QFD方法的主观性；最后利用改进QFD方法识别产品平台参数，验证了该方法的有效性.

关键词: 产品平台规划, 虚拟正文试验, 改进QFD, 敏感度分析

Abstract: Sensitivity analysis is a method of product platform planning considering the influence of design parameters on performance. However, the current sensitivity analysis method is difficult to apply to products where there is no clear mathematical function between the performance parameters and design parameters. In view of this deficiency, a sensitivity analysis method based on virtual orthogonal test is proposed, and the product platform planning is carried out in combination with improved QFD. Firstly, the virtual test scheme is determined based on the orthogonal experiment design method. Secondly, a virtual test environment is built by built-in software, in which the design parameters is set of different values and the performance parameters’ change is recorded in real-time. And the sensitivity of the design parameters is calculated based on the ratio of the two parameters. Then the sensitivity matrix is constructed and used to replace the traditional correlation matrix in the QFD house to measure the degree of correlation between the design parameters and the performance parameters so as to reduce the subjectivity of the traditional QFD method. Finally, the improved QFD method is used to identify the product platform parameters, and the effectiveness of the method is verified.

Key words: product platform planning, virtual orthogonal test, improved QFD, sensitivity analysis

中图分类号:

TB 472

袁振龙，褚学宁，张磊. 基于虚拟正交试验和改进QFD的产品平台规划方法[J]. 上海交通大学学报（自然版）, 2018, 52(8): 930-937.

YUAN Zhenlong,CHU Xuening,ZHANG Lei. Product Platform Planning Method Based on Virtual Orthogonal Test and Improved QFD[J]. Journal of Shanghai Jiaotong University, 2018, 52(8): 930-937.

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