中国机械工程 ›› 2015, Vol. 26 ›› Issue (10): 1330-1336,1344.

• 智能制造 • 上一篇    下一篇

基于AHP与IFS的单件生产模式下制造需求与资源匹配算法

毕克克1,2;牛占文1;赵楠3;彭巍1;仝克宁1   

  1. 1.天津大学,天津,300072
    2.天津大学仁爱学院,天津,300072
    3.天津职业技术师范大学,天津,300222
  • 出版日期:2015-05-25 发布日期:2015-05-26
  • 基金资助:
    国家自然科学基金资助项目(71171145);国家高技术研究发展计划(863计划)资助项目(2013AA040605)

Algorithm of Manufacturing Demands and Resource Matching under Piece Production Model Based on Analytic Hierarchy Process(AHP)  and IFS

Bi Keke1,2;Niu Zhanwen1;Zhao Nan3;Peng Wei1;Tong Kening1   

  1. 1.Tianjin University,Tianjin,300072
    2.Ren'ai College,Tianjin University,Tianjin,300072
    3.Tianjin University of Technology and Education,Tianjin,300222
  • Online:2015-05-25 Published:2015-05-26
  • Supported by:
    National Natural Science Foundation of China(No. 71171145);National High-tech R&D Program of China (863 Program) (No. 2013AA040605)

摘要:

针对复杂大型装备的单件生产模式产品规格繁多、结构复杂且个性化强、工艺变更频繁且难以标准化、工艺编制难度大、加工周期长、对资源能力依赖严重等特点,以及制造服务提供企业在订单阶段难以对客户需求与当前制造能力的匹配度进行正确、快速预判等问题,提出了基于零件特征的单件生产制造需求和制造资源能力模型。引入基于层次分析法与直觉模糊集的特征工序矩阵与设备资源能力矩阵匹配算法,计算零件需求和资源的匹配度,实现订单阶段的用户需求和制造资源的快速匹配,最后通过企业实例验证了该方法的有效性。研究结果有助于提高单件制造企业的订单评估质量,降低接单风险,增强企业的竞争力。

关键词: 单件制造, 制造需求, 设备能力矩阵, 直觉模糊集, 匹配模型

Abstract:

Piece production model of large and complex equipment has the features as: vast amount of product specifications, complex and personalized structures, frequent changes of crafts, difficult process planning, long production lifetime, severe dependence on resources. Manufacturing companies could not predict the matching degree of customer demands and its own ability in the order stage. According to existing problems, this paper proposed the production demand and resource model based on part features, introduced the algorithm of featured process matrix and resource ability matrix matching based on AHP and IFS to calculate the matching degree. Finally the effectiveness of this method was verified using company examples. The results contribute to improve the quality of order evaluation in piece manufacturing company, to reduce the risk of orders and strengthen the competitiveness.

Key words: piece production, manufacturing demand, equipment capability matrix, intuitionistic fuzzy sets (IFS), matching model

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