Optimal design of clamping sequence in sheet metal assembly based on genetic algorithm

The sequence in which the clamps are applied has a significant influence on the location error and dimensional variability for non-rigid parts assembly. This paper presents a novel clamping sequence optimization methodology applicable for deformed parts assembly with the main objective of minimizing the part-to-part gap. The methodology combines finite element modelling and genetic algorithm to realize the generation of an optimal clamping sequence for compliant parts. Finite element models are developed to simulate the transformation of geometry under the constraints of clamps and the computation of part-to-part gaps is achieved by updating the geometry along the clamping sequences. A genetic algorithm is applied to automatically search for the optimal clamping sequence. In the genetic algorithm, a coarse mesh is used to solve the time-consuming problem and a fine mesh is used to test the results. The methodology is demonstrated and validated using the results of a case study, which obtains an accurate part-to-part gap with a 90% reduction in computation time to identify the optimal clamping sequence.