Robust Design for Fixture Layout in Multistation Assembly Systems Using Sequential Space Filling Methods
Robust Design for Fixture Layout in Multistation Assembly Systems Using Sequential Space Filling Methods
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DOI：
10.1115/1.3503880
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发表时间：
2010-12
期刊：
影响因子：
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通讯作者：
Wenzhen Huang;Z. Kong;Abishek Chennamaraju
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文献类型：
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作者：
Wenzhen Huang;Z. Kong;Abishek Chennamaraju
多工位制造系统夹具布局稳健设计的目标是使产品的尺寸变化对制造过程中工艺变量的变化不敏感。鲁棒设计是一个高维复杂的全局优化问题。最新进展的变化流建模技术，使有效的制定在系统级的优化问题。然而，在高维、非凸和不连续的设计空间中搜索最优设计参数存在计算复杂性的挑战。这使得许多可用的算法无效甚至无效。本文提出了一种交替顺序空间填充策略，采用抽样方法搜索最优设计。为了提高计算效率，先对搜索空间进行逐步缩减，生成一系列子空间，并设计一种方法保证这些子空间在原可行空间中的完全覆盖。为了验证该方法的有效性，以某汽车车身装配过程中的底盘总成为例进行了建模，并利用所提出的方法进行了夹具稳健设计。为了验证所提方法的有效性，本文还将遗传算法和序列二次规划算法应用于算例中进行了比较。
Fixture layout robust design of multistation manufacturing systems aims for an optimal design that enables the dimensional variation of a product insensitive to the variations of process variables in the manufacturing process. The robust design involves a high dimension and complex global optimization problem. Recent advances in stream of variation modeling techniques enable effective formulation of the optimization problem at the system level. However, there is a challenge of computation complexity in terms of searching optimal design parameters in a high dimension, nonconvex, and discontinuous design space. This makes many available algorithms ineffective or even invalid. In this paper, an alternative sequential space filling strategy is proposed, which adopts sampling approaches to search optimal designs. To improve computation efficiency, the search space is sequentially reduced to generate a series of subspaces, and a method is designed to ensure a complete coverage of these subspaces in the original feasible space. In order to validate the proposed method, a floor pan assembly from an automotive body assembly process is modeled, and then the fixture robust design is conducted with the developed methods. To show the effectiveness of the proposed method, genetic algorithm and sequential quadratic programming are also applied in the case study for comparison.