Proceedings of the
9th International Conference of Asian Society for Precision Engineering and Nanotechnology (ASPEN2022)
15 – 18 November 2022, Singapore

Model-Based Feed Rate Optimization for Cycle Time Reduction in Milling

J. Y. Oh1, B. Sim1, W. J. Lee1, S. J. Choi1 and W. Leea

1School of Mechanical Engineering, Chungnam National University, 99, Daehak-ro, Yuseong-gu, Daejeon, Republic of Korea


Feed rate is an important determinant of cutting force and cycle time. Selection of appropriate feed rate can increase processing quality and production efficiency. Generally, in a software that generates tool path, the feed rate is determined based on the recommended conditions of the handbook provided by the tool company. Although various cutting conditions are included in one processing path, the recommended feed rate is limited to only one of slot milling or side milling. The optimal value of feed rate is derived based on the cutting force that depends on the cutting conditions, materials, and conditions of the equipment. For this reason, the limitedly recommended feed rate has low efficiency. To solve this problem, many methods were developed to maintain constant cutting force by applying real time feedback system. The feedback system was constructed with data such as tool condition, temperature and cutting load of spindle. However, these methods have low reliability, and a problem of different cycle time caused by changed feed rate in real time. In this study, the feed rate optimization that maintains cutting force was developed based on cutting force prediction model and an algorithm that extract cutting conditions from G code each line. The feed rate optimization is applied to flat end mill and ball end mill. The interpreter of G code were configured to calculate the tool center point and cutting condition. The real time spindle power measuring system were constructed to predict cutting force of G code for each line by identifying parameters of cutting force prediction model. The criteria cutting force was selected by highest value among the predicted cutting forces. The optimized feed rate that maintains the cutting force was extracted based on the cutting conditions of other lines and the cutting force prediction model. The extracted feed rate are applied to G code by modifying only feed rate command F. The feed rate optimized G code is newly generated. Experimental results by using commercial machine tool show that the proposed feed rate optimization significantly reduces overall cycle time and maintains the cutting force well.

Keywords: Cutting force, Feed rate, Optimization, Cutting force prediction model

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