Solving a multi-dimensional matching problem for grouping clamping points on car body parts

• Published in: Procedia CIRP 2022, Vol.106, p.126-131
• Main Authors: Oberfichtner, Lena, Ahrens, Antje, Fritzsche, Rayk, Richter-Trummer, Valentin, Todtermuschke, Marcel
• Format: Article
• Language: English
• Subjects: adaptable jigs; analyzing software; automated design; body in white; flexible production; optimization; product flexibility
• ISSN: 2212-8271; 2212-8271
• DOI: 10.1016/j.procir.2022.02.166

Modern car body production is faced by an increasing number of car models as well as individualizing options, which leads to the need for more adaptable assembly equipment, e.g. grippers and fixtures that can switch between models in a matter of seconds. Based on known clamping positions, automated jigs consisting of several clamps can already adapt to different part geometries. To enable an efficient flexible jig, exactly one clamp must be assigned to each clamping point of each model taking into account different optimization criteria. Therefore, clamping points need to be grouped across all different models in the planning phase. Grouping of clamping points e.g. in order to minimize adaptation time or tooling costs is usually performed manually. In this paper, the grouping optimization problem is formalized, and a mathematical algorithm is introduced to solve this multi-dimensional matching. The envisaged approach uses a greedy algorithm to get an initial solution, which is optimised to a technically feasible solution considering economical aspects. To conclude, a short evaluation of the achieved results - especially in comparison with expert based grouping - is given.