Analysis reveals that parallel and equidistant strategies impact surface quality and efficiency in soft material robotic machining.
The modern manufacturing industry is increasingly focused on robotic machining for soft materials, such as foam, due to its ability to provide precise automated operations. This study examines the effect of robotic movement parameters on soft material machining, considering material surface quality and machining time for strategy comparison. The testing of the Parallel and Equidistant machining methods revealed their operational capabilities and practical viability. The parallel method promotes robot motion stability and controlled amplitude, resulting in uniform machining outcomes. In contrast, the equidistant approach results in irregular robotic movement and oscillatory amplitude variations, which can lead to surface imperfections and reduced efficiency. The success of this research was driven by SprutCAM’s comprehensive simulation capabilities, including its visualisation tools, which enabled prior to actual machining, reduced testing time, expanded operator options, and automatically aligned processes to enhance efficiency. Simulation data from SprutCAM has been proven instrumental in identifying key motion factors crucial for improving machining results. The findings highlight the indispensable role of simulation tools, such as SprutCAM, in robotic machining to ensure precision and consistency during the foam processing process. As a result, machining time is reduced, surface quality improves, and the performance of robot axis movement is refined alongside toolpath strategies. These results suggest that simulation-based process optimisation can significantly benefit modern manufacturing by providing essential principles for advancing robotic machining techniques.
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Jusoh et al. (2025) studied this question.
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