A method for identification and sequence optimisation of geometry spot welds in a digital twin context

Abstract

Geometrical variation is the main cause of the aesthetic and functional problems in the product geometry. Variation and disturbances are caused by several sources during the manufacturing process. In the automotive industry, one of the main sources of variation is the spot welding sequence. Optimising this sequence is of combinatorial Nondeterministic Polynomial (NP)-hard problems. In a typical automotive sheet metal assembly, there are a large number of spot welds. Today, if the number of spot welds in a sub-assembly is more than 10, the sequence optimisation will be a challenging and time-consuming task. Therefore, industry is mainly dependent on the experiential approach or simultaneous welding simulations for predicting the geometrical outcome. In this paper, a method is introduced to identify the geometry weld points to reduce the optimisation problem size in a geometry assurance digital twin context. This method is then applied to three automotive body-in-white assemblies and optimisation is performed. The results show that reducing the size of the problem by the proposed approach can help to save a considerable amount of time while getting geometrical outcomes within the satisfactory error levels.