로봇 팔 기반 대형 엔진 실린더 블록 후처리 공정 자동화를 위한 공구 및 버 형상 별 절삭력 분석에 관한 연구

Abstract

Large engine cylinder blocks are widely used in industries such as data centers, ships, gas turbines, and industrial plants, requiring post-processing machining to address surface defects and dimensional inaccuracies from casting. However, the current manual-based process heavily depends on the operator’s experience and skill level, leading to quality inconsistencies and an increased risk of workplace accidents due to handling heavy components. To overcome these challenges, automated post-processing using articulated robotic arms is being introduced. Robotic arms offer high degrees of freedom, enabling precise machining of complex shapes when integrated with vision and sensor technologies. However, improper tool selection can result in excessive machining loads and vibrations, negatively affecting machining accuracy and overall process stability. In this study, key burr formations were classified, and cutting force experiments were conducted for different tool types to minimize machining loads in automation processes. Experimental data were analyzed to determine machining load and vibration characteristics for each tool, providing insights into optimizing robotic-based automated post-processing. The findings of this study are expected to contribute to the precision machining of large engine cylinder blocks and can also be applied to automated machining of other heavy and complex industrial components.