Recent Advances in Intelligent Manufacturing - First International Conference on Intelligent Manufacturing and Internet of Things and 5th International Conference on Computing for Sustainable Energy and Environment, IMIOT and ICSEE 2018, Chongqing, China, September 21-23, 2018, Proceedings, Part I

Recent Advances in Intelligent Manufacturing - First International Conference on Intelligent Manufacturing and Internet of Things and 5th International Conference on Computing for Sustainable Energy and Environment, IMIOT and ICSEE 2018, Chongqing, China, September 21-23, 2018, Proceedings, Part I
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智能制造最新进展 - 第一届智能制造和物联网国际会议暨第五届可持续能源与环境计算国际会议,IMIOT 和 ICSEE 2018,中国重庆,2018 年 9 月 21-23 日,会议记录,第一部分

DOI:
10.1007/978-981-13-2396-6_7
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发表时间:
2018
期刊:
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影响因子:
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通讯作者:
Agarwal D
Agarwal D
中科院分区:
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文献类型:
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作者:
Agarwal D

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单个零部件的优化通常与它在组件中将连接或包围的零部件隔离。这意味着,当优化的组件组装在一起时,可能会出现配合问题。本文提出了一种基于CAD的优化框架,它使用CAD模型产品装配中的相邻或周围组件施加的约束,定义被优化组件的包装空间的限制。这在工业工作流程中非常重要,因为解决不必要的干扰成本很高。提出的基于梯度的优化框架使用在基于特征的CAD模型中定义特征的参数作为设计变量。该框架的两个主要优点是:(1)优化的几何形状可作为CAD模型使用,并且可以很容易地在制造阶段使用,以及(2)所得到的制造对象应该能够在组装过程中与其他组件组装。该框架被证明是在CATIA V5中创建的2D和3D参数化模型的优化。
The optimization of an individual component usually happens in isolation of the components it will interface with or be surrounded by in an assembly. This means that when the optimized components are assembled together fit issues can occur. This paper presents a CAD-based optimization framework, which uses constraints imposed by the adjacent or surrounding components in the CAD model product assembly, to define the limits of the packaging space for the component being optimized. This is important in industrial workflows, where unwanted interference is costly to resolve. The gradient-based optimization framework presented uses the parameters defining the features in a feature-based CAD model as design variables. The two main benefits of this framework are: (1) the optimized geometry is available as a CAD model and can be easily used in the manufacturing stages, and (2) the resulting manufactured object should be able to be assembled with other components during the assembly process. The framework is demonstrated for the optimization of 2D and 3D parametric models created in CATIA V5.