• 论文 •    

基于公理设计的产品平台规划方法

程强,刘志峰,蔡力钢,张国军,顾佩华   

  1. 1.北京工业大学 精密超精密加工国家工程研究中心,北京100124;2.华中科技大学 数字制造装备与技术国家重点实验室,湖北武汉430074;3.汕头轻工装备研究院,广东汕头515021
  • 出版日期:2010-08-15 发布日期:2010-08-25

Planning method for product platform based on axiomatic design

CHENG Qiang, LIU Zhi-feng,CAI Li-gang, ZHANG Guo-jun,GU Pei-hua   

  1. 1.State Engineering Center of Precision & Ultra-Precision Machining,Beijing University of Technology, Beijing 100124, China;2.State Key Lab of Digital Manufacturing Equipment & Technology,Huazhong University of Science & Technology, Wuhan 430074, China;3.Shantou Institute of Light Industry Equipment, Shantou 515021, China
  • Online:2010-08-15 Published:2010-08-25

摘要: 针对目前可调节参数平台的设计过程中,人为指定公共平台参数存在的过多主观性,提出了一种基于公理设计和敏感设计结构矩阵的平台规划方法。基于公理设计推导出设计参数满足公共平台参数条件的数学模型;在设计结构矩阵的基础上提出了描述设计参数之间以及设计参数与功能要求之间动态敏感关系的敏感设计结构矩阵,由此识别出公共平台参数和可调节平台参数,并通过非支配排序遗传算法合理确定平台参数优化配置解。通过自动打孔装订机产品族的平台设计实例,验证了该方法的有效性。

关键词: 产品平台, 公理设计, 敏感设计结构矩阵, 模块化, 参数化, 产品设计, 遗传算法

Abstract: In view of the excessive subjectivity in most existing methods due to a priori assignment of common platform parameters by designers during the design process of scale-based platform, a planning method for product platform based on axiomatic design and Sensitivity Design Structure Matrix(SDSM)was developed. The mathematical model for design parameters satisfying common platform parameters was deduced according to axiomatic design. SDSM which could describe the dynamic sensitivity relationships among design parameters and that between design parameters and functional requirements was established on the basis of design structure matrix. Then, common platform parameters were identified with scalable platform parameters according to SDSM, followed on with the optimization of their optimum solutions with non-dominated sorting genetic algorithm. Finally, an example of automatic bookbinding machine platform design verified the effectiveness of the proposed method.

Key words: product platform, axiomatic design, sensitivity design structure matrix, modularization, parameterization, product design, genetic algorithm

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