首页> 外文期刊>International Journal of Production Research >Research on resources optimisation deployment model and algorithm for collaborative manufacturing process
【24h】

Research on resources optimisation deployment model and algorithm for collaborative manufacturing process

机译:协同制造过程资源优化部署模型与算法研究

获取原文
获取原文并翻译 | 示例
       

摘要

Agility is the competitive advantage in the global manufacturing environment. It is believed that agility can be realised by networked manufacturing resource optimisation deployment. However, this is a challenge to us now. To solve this question, logical manufacturing unit and logical manufacturing process are proposed to decompose and model the networked manufacturing task, and networked manufacturing resources are organised and modelled based on physical manufacturing unit. During the deployment of manufacturing resources to the task, many factors should be taken into consideration. Of these, manufacturing cost, time and quality are the most important factors. In this paper, before these factors are considered, networked manufacturing resources pre-deployment is carried out to find the candidate manufacturing resources on the basis of manufacturing abilities. Then, resources optimisation deployment is modelled as a multi-objectives optimisation. This optimisation problem is solved based on genetic algorithm after transforming the multi-objectives optimisation problem to a single objectives optimisation problem. Although we may not find the optimal solution for the problem by genetic algorithm, the better and feasible solution is produced. Thus, this algorithm is efficient and can be applicable to practical problem. At last, an illustrative example is presented to show the application of the proposed algorithm.
机译:敏捷性是全球制造环境中的竞争优势。相信可以通过网络化制造资源优化部署来实现敏捷性。但是,这对我们现在是一个挑战。为解决这一问题,提出了逻辑制造单元和逻辑制造过程,对网络化制造任务进行分解和建模,并基于物理制造单元对网络化制造资源进行组织和建模。在为任务分配制造资源的过程中,应考虑许多因素。其中,制造成本,时间和质量是最重要的因素。本文在考虑这些因素之前,先进行网络化制造资源预部署,以便根据制造能力找到候选制造资源。然后,将资源优化部署建模为多目标优化。将多目标优化问题转化为单目标优化问题后,基于遗传算法解决了该优化问题。尽管我们可能无法通过遗传算法找到该问题的最佳解决方案,但是却产生了更好且可行的解决方案。因此,该算法是有效的并且可以应用于实际问题。最后,给出了一个说明性例子,说明了该算法的应用。

著录项

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