Fixtures are extensively used in many industries such as the car industry, to locate and constrain the sheet part during the assembly stage. Fixture layout affects on deformation of sheet parts. Therefore, fixture layout optimization is crucial to the accuracy and quality of products. In addition, the number of clamps that uses in the fixture is another important factor that must be considered in fixture design. This article presents a novel fixture layout optimization method by combining multi-objective ant colony algorithm (M-ACO) and the finite element method. The proposed method optimizes the fixture layout and the number of clamps simultaneously as a multi-objective problem. An approximation of Pareto frontier is acquired by the proposed method. The fixture layout for the side reinforcement of a car is optimized using the proposed method. The results show that the proposed approach performs effectively to optimize the auto-body fixture layout.

中文翻译：

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基于蚁群算法的车身夹具布局多目标优化

夹具广泛用于许多行业，例如汽车行业，用于在装配阶段定位和约束板材。夹具布局影响薄板零件的变形。因此，夹具布局优化对产品的精度和质量至关重要。此外，夹具中使用的夹具数量是夹具设计中必须考虑的另一个重要因素。本文提出了一种结合多目标蚁群算法（M-ACO）和有限元方法的新型夹具布局优化方法。所提出的方法将夹具布局和夹具数量同时优化为一个多目标问题。通过所提出的方法获得了帕累托边界的近似值。使用所提出的方法优化了汽车侧筋的夹具布局。