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Optimization of a welding gun use case by using a time-based ergonomics evaluation methodMora Quiles, Elia January 2022 (has links)
Nowadays virtual simulations are commonly used to solve problems regarding worker well-being or productivity in manufacturing companies. However, when it comes to finding a solution to one of these two objectives, the other usually tends to be secondary. In order to solve this problem, the Ergonomics in Production Platform (EPP) has been developed within research efforts at University of Skövde, which through the use of optimizations is able to obtain solutions where both objectives are taken into account. In turn, in order to address worker well-being, EPP makes use of the digital human modelling (DHM) tool. DHM tools are often used to evaluate simulations focused on studying human-machine interaction. However, as these software evolve and start to be able to reproduce complete motions, before they were only considering frames, new methods are needed to be able to assess risk factors such as time and prevent the occurrence of musculoskeletal disorders (MSDs). In order to assist in the development of EPP optimizations for simulations carried out in DHM tools, the time-based observational method RAMP was implemented, specifically the posture-related criteria of RAMP II. Using the Design and Creation research methodology, a welding gun case study located in China offered by Volvo Cars was used to evaluate the results of the optimizations carried out with EPP. For the evaluation of this case study, a manikin family of 10 members representing key cases of the Asian population was created for this task. Later, this task was recreated in IPS IMMA, where the 10 cases interacted with 3 welding guns to weld different spots on a piece. The analysis of this case study consisted of two distinct phases where the results of RAMP II implemented in EPP could be evaluated. The first phase focused on analyzing initial results of three different trajectories for all members of the family. The second phase consisted of optimizing one of the trajectories analyzed in the previous phase in such a way as to find the best welding angle of the gun to improve the results of the worst case in the first analysis. Three different factors were evaluated in this phase: RAMP II results versus the new angle, RAMP II results versus the results of other methods and the effect of productivity versus worker well-being. The results showed that welding angles of 116º and 80º were able to improve the values of the RAMP II criteria for the most disadvantaged manikin in the welding task. At the same time, it was observed that the higher the percentage of value added time, the higher the risk obtained in the analysis, worsening the worker's well-being.
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