北京航空航天大学学报 ›› 2013, Vol. 39 ›› Issue (8): 1004-1010.

• 论文 • 上一篇    下一篇

直觉模糊制造知识驱动的公差稳健优化设计

谭昌柏1, 侯东旭1, 卫炜1, 付睿2   

  1. 1. 南京航空航天大学 机电学院, 南京 210016;
    2. 哈尔滨飞机工业集团有限责任公司 产品支援部, 哈尔滨 150066
  • 收稿日期:2012-08-17 修回日期:2012-11-29 出版日期:2013-08-30 发布日期:2013-09-03
  • 基金资助:
    国家自然科学基金资助项目(50905084);航空科学基金资助项目(2010ZE52054)

Intuitionistic fuzzy manufacture knowledge-driven robust tolerance design

Tan Changbai1, Hou Dongxu1, Wei Wei1, Fu Rui2   

  1. 1. School of Mechanical and Electrical Engineering, Nanjing University of Aeronautics & Astronautics, Nanjing 210016, China;
    2. Department of Product Support, Harbin Aircraft Industries Group, Harbin 150066, China
  • Received:2012-08-17 Revised:2012-11-29 Online:2013-08-30 Published:2013-09-03

摘要: 鉴于各类制造因素在表述方式、度量方法及其与成本的关系等方面均存在一定的模糊性和可变性,基于直觉模糊集理论和稳健设计原理,提出了直觉模糊制造知识驱动的公差稳健设计方法.首先,从工艺装备价值、零件可加工性、加工工艺属性、产品属性、人员技术水平等5个方面建立直觉模糊制造知识集,研究了知识元素构成和元素水平划分;然后,建立了包含目标层、准则层和知识层的制造成本评估指标体系,采用多级直觉模糊综合评判法计算制造成本因子φ,与传统模糊综合评判相比,更符合真实评判逻辑;最后,结合成本-公差模型和装配模糊质量损失函数,建立了公差的模糊稳健优化模型.该方法符合面向制造的设计理念,综合考虑了各类制造知识对公差设计的影响,航空油箱装配的实例分析表明了该方法可行,且具有好的灵活性和鲁棒性等优点.

Abstract: Motivated by fuzziness and uncertainty of manufacture factors in their expression, measurement and effects on the production cost, a methodology of intuitionistic fuzzy manufacture knowledge-driven robust tolerance design was developed systematically based on the intuitionistic fuzzy set and robust design theories. An intuitionistic fuzzy manufacture knowledge set was established according to such five aspects as the values of equipments, the machinabilities of product, the process features, the product features and the technical skills of worker. The constitution and level division of every knowledge subset was also discussed. A system of evaluating goals of manufacturing cost involving the target layer, the rule layer and the knowledge layer was developed, and an intuitionistic fuzzy comprehensive evaluation algorithm was used to calculate the manufacture cost factor φ. This method is more comply with the human logic compared with the traditional fuzzy evaluation. A fuzzy robust tolerance optimization model was established combining a cost-tolerance model with a proposed fuzzy quality loss function. Complying with the DFM concept, this methodology considers a comprehensive effect of various manufacturing factors on tolerance design. A case study on the tolerance optimization of certain aerospace fuel tank illustrates the feasibility, flexibility and robustness of the proposed approach.

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