Max Robotics — Global Service Robot Directory + US Certification

About

Fredrik Edelvik is a computational scientist and engineer whose research sits at the intersection of industrial manufacturing simulation, robotics, and applied mathematics. His work has profoundly shaped how the automotive industry approaches spray painting, sealing, and adhesive joining processes through advanced computational modeling and automated path planning. Edelvik's most celebrated contribution is the development of optimization frameworks for robotic spray painting trajectories, with his 2022 paper garnering 61 citations and establishing him as a leading voice in intelligent manufacturing automation. His earlier foundational work on simulating electrostatic rotary bell spray painting (2013, 32 citations) introduced novel coupled algorithms combining Navier-Stokes solvers with electromagnetic field modeling, dramatically improving computational efficiency in paint shop simulations. Beyond painting, Edelvik has extended his expertise to sealing station optimization (2014, 26 citations) and adhesive joining processes (2016, 13 citations), tackling challenging multiphase, multi-scale flow phenomena involving large moving geometries. His pioneering SelfPaint project further demonstrated his vision for fully autonomous, self-programming paint booths. Spanning over a decade of consistently impactful publications, Edelvik's research bridges rigorous physical simulation with practical industrial robotics, offering manufacturers powerful tools to improve quality, reduce cycle times, and automate complex production processes.