Assembly process is widely used in the manufacturing processes. Fabrication processes such as machining, casting and metal forming are not perfect and introduce variation in the components. Variations of components and tools accumulate and cause the assembly variation. In this paper, after reviewing the literature and presenting sheet metal assembly variation analysis, an optimization method is used to minimize the assembly variation by optimizing the location of joints and fixtures. The model is constructed in ANSYS with three fixtures and two joints. When a black-box function calculated numerically in software is used as the objective function, using deterministic methods for optimization is not suitable because the deterministic methods need knowledge of the objective functions. Also, using stochastic methods such as genetic algorithm is not suitable because of the large number of function evaluations they normally need. In this paper, an optimization algorithm based on mode-pursuing sampling (MPS) method is used to minimize the assembly variation. The optimization method is explained and after implementing the method, results are presented. It is learned that, in addition to the number of fixtures, the constraints on neighboring fixture locations also affect the optimal fixture layout, as well as the final assembly stiffness and spring-back.
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