Digital process planning of joining by numerical models in the automotive industry
Abstract: The automotive industry is striving towards reduction of greenhouse gas emission by reducing product weight and improving fuel efficiency of their products. The introduction of lightweight materials have imposed greater pressure not only on the product development but also on manufacturing systems. One integral aspect of manufacturing systems, which is meeting these challenges is joining technology. In order to achieve successful joining of new automotive products, joining process planning must be equally successful.This research aims at improving process planning of joining by introducing digital tools into the process planning work method. The digital tools are designed to reduce lead times and increase accuracy of the process planning to realize more advanced, complex and environmentally friendly product solutions in the vehicles of the future.The research has two main focuses. Firstly, the joining process planning structure and organization have been analysed. The analysis has identified specific instances where digital tools can be introduced to improve the process planning and make it more efficient. Digital tools, such as numerical models for prediction and databases for re-use of knowledge, have been suggested for the process planning. An assessment of the impact of the introduction of these tools in an industrial test case has been performed to show the possible reduction in lead times.Secondly, geometrical distortions due to laser beam welding have been investigated, both by experimental trials and numerical modelling. The influences of design and process parameters on the distribution and magnitude of geometrical distortions have been established. Numerical models of different modelling detail and complexity have been developed and evaluated in order to find modelling approaches with reduced computation times aimed at industrial implementation. The predictive accuracy and computational efficiency of the numerical models have been assessed and evaluated with regard to industrial implementation.
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