Johan Segeborn
Papers
7
Total Citations
79
H-Index
5
About
Johan Segeborn is a researcher specializing in automated manufacturing optimization, with a particular focus on robotic welding systems in automotive sheet metal assembly. His work addresses some of the most computationally demanding challenges in modern car body production, where hundreds of robots must coordinate thousands of spot welds across complex assembly lines involving roughly 300 sheet metal parts and up to 4,000 individual welds per vehicle. Segeborn's most significant contributions lie in developing systematic, simulation-based methods for weld load balancing and welding sequence optimization — problems that were largely handled manually before his interventions. His industrially validated approaches to multi-station line balancing, published between 2010 and 2014, have collectively garnered over 75 citations, demonstrating strong uptake within both academic and industrial communities. His 2014 paper on simultaneously minimizing dimensional variation and robot travel time stands as his most influential work, addressing the dual challenge of maximizing product quality while reducing cycle time. A recurring theme across his research is the integration of dimensional variation analysis with path planning and equipment utilization, bridging the gap between geometric quality assurance and production efficiency. His application of genetic algorithms to welding sequence problems further highlights his interdisciplinary approach, combining evolutionary computation with precision manufacturing challenges of direct industrial relevance.
Research Focus
Key Achievements
Top Papers
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- 5Load Balancing of Welds in Multi Station Sheet Metal Assembly Lines9 citations · 2010
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