• CN:11-2187/TH
  • ISSN:0577-6686

›› 2007, Vol. 43 ›› Issue (6): 205-209.

• 论文 • 上一篇    下一篇

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基于成本聚类的产品设计早期阶段成本估算模型

姜少飞;鲁聪达;卢纯福;潘双夏   

  1. 浙江工业大学机械制造及自动化省部共建教育部重点实验室;浙江大学CAD&CG国家重点实验室
  • 发布日期:2007-06-15

PRODUCT COST ESTIMATION MODEL IN EARLY DESIGN PHASE BASED ON COST CLUSTER

JIANG Shaofei;LU Congda;LU Chunfu;PAN Shuangxia   

  1. Key Laboratory for Mechanical Manufacture & Automation of Ministry of Education, Zhejiang University of Technology State Key Laboratory of CAD&CG,Zhejiang University
  • Published:2007-06-15

摘要: 针对产品适应性设计或变型设计早期阶段难以进行精确成本估算的特点,提出大样本条件下基于“成本聚类”的成本估算模型。通过计算参考样本和待估算产品的欧氏距离考察二者的相似度,以欧氏距离集为初始数据分别构造差异矩阵、距离矩阵和相似矩阵,实现对样本的成本聚类分析过程,最终筛选出与待估算产品最相关的样本集合,得到待估算产品成本可能落入的区间。以液压盘式制动器的制动盘零件为实例,验证方法的有效性。试验结果表明,该模型能够有效区分估算样本的相对优劣。

关键词: 成本聚类, 成本区间, 灰色模糊聚类, 欧氏距离

Abstract: A cost estimation model based on cost cluster is presented with big samples in early product design phase because precise cost estimation in early adptive or derivative product design phase is very difficult. Euclidean distance between samples and estimating product are calculated to express their similarity. Difference matrix, distance matrix and similarity matrix are built base on euclidean distance sets between samples and indeterminate estimation product, then most correlated sample sets are selected to get interval of estimated cost based on cost cluster analysis. An example of brake disc shows invalidity of the cost cluster model. The result of experiment proved that cost cluster model was able to separate relative order of qulity of the samples.

Key words: Cost cluster, Cost interval, Euclidean distance, Gray fuzzy cluster

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