首页> 外文期刊>Complexity >Optimized Configuration of Manufacturing Resources for Middle and Lower Batch Customization Enterprises in Cloud Manufacturing Environment
【24h】

Optimized Configuration of Manufacturing Resources for Middle and Lower Batch Customization Enterprises in Cloud Manufacturing Environment

机译:云制造环境中批次批量定制企业制造资源的优化配置

获取原文
       

摘要

The optimal configuration of manufacturing resources in the cloud manufacturing environment has always been the focus of research on various advanced manufacturing systems. Aiming at the problem of manufacturing resources optimization configuration for middle and lower batch customization enterprises in cloud manufacturing environment, this paper gives a bi-level programming model for manufacturing resources optimization configuration in cloud manufacturing environment which fully considers customer satisfaction and enterprise customization economic benefits. The method firstly identifies the relationship between customer demands and customer satisfaction through questionnaires and quantifies the Kano model effectively. Then, it uses Quality Function Deployment (QFD) to transform customer demand characteristics into engineering characteristics and integrates the qualitative and quantitative results of the Kano model. Next, the method establishes enterprise economic benefits function according to the factors of order quantity and input cost. Furthermore, a comprehensive nonlinear bi-level programming model is established based on cost, time, and quality constraints. The model is solved by intelligent algorithm. Finally, the validity and feasibility of the model are verified by model simulation of actual orders of an enterprise. This method effectively realizes the optimal configuration of manufacturing resources in the cloud manufacturing environment, while maximizing the interests of both suppliers and demanders.
机译:云制造环境中的制造资源的最佳配置一直是各种先进制造系统的研究焦点。针对云制造环境中批量定制企业制造资源优化配置的问题,为云制造环境中的制造资源优化配置提供了双级规划模型,充分考虑了客户满意度和企业定制经济效益。该方法首先通过调查问卷来识别客户需求和客户满意度之间的关系,并有效地量化了Kano模型。然后,它使用质量函数部署(QFD)将客户需求特征转换为工程特征,并集成了Kano模型的定性和定量结果。接下来,该方法根据订单数量和输入成本的因素建立企业经济效益。此外,基于成本,时间和质量约束来建立综合非线性双级编程模型。该模型通过智能算法解决。最后,通过模型模拟企业的模型仿真来验证模型的有效性和可行性。该方法有效地实现了云制造环境中的制造资源的最佳配置,同时最大化供应商和供应者的利益。

著录项

  • 来源
    《Complexity》 |2020年第1期|共13页
  • 作者

    Yinyun Yu; Wei Xu;

  • 作者单位
  • 收录信息
  • 原文格式 PDF
  • 正文语种
  • 中图分类
  • 关键词

  • 入库时间 2022-08-18 23:48:12

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号