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IJMERR 2022 Vol.11(9): 682-689
DOI: 10.18178/ijmerr.11.9.682-689

The Characteristics of Cutting Force in the Rough Machining Process of 5-Axis Milling on PEEK Material Based on Cutting Speed Parameters

Himawan Hadi Sutrisno
Fire, Material and Safety Laboratory, Universitas Negeri Jakarta, Indonesia

Abstract—This study determines the cutting force characteristics of the 5-axis milling rough machining process based on the differences in cutting speed, especially on composite materials. The data generated are useful for operators in the machining process in the manufacturing industry. Simulations and experimental methods are used, and data generated from cutting force sensors are validated using mathematical models commonly used for cutting force calculations. From the obtained data, the characteristics of the cutting force influenced by the cutting speed of the machining process are further analysed. The material is a PEEK composite used by the manufacturing industry. The tool used is a material-type high-speed tool steel end mill. By using a machine-type table tilting 5-axis mill for the rough machining process, the variation in cutting speed affects the tool cutting force at each shear angle. The data showed that the lowest cutting speed produces a high cutting force on the x-axis component. In this component, the largest value is 39.73 N at a cutting speed of 18.84 m/min; at the y-axis at the same cutting speed, the largest cutting force value is 79.20 N. The z-axis component value is 16,405 N, which exhibits the lowest cut force value compared to the increase in the speed of the other cuts used in the study. The increase in tool cutting speed does not always increase the cutting force of each machining axis.

Index Terms—5-axis machining, cutting force, cutting speed, PEEK, rough machining

Cite: Himawan Hadi Sutrisno, "The Characteristics of Cutting Force in the Rough Machining Process of 5-Axis Milling on PEEK Material Based on Cutting Speed Parameters," International Journal of Mechanical Engineering and Robotics Research, Vol. 11, No. 9, pp. 682-689, September 2022. DOI: 10.18178/ijmerr.11.9.682-689

Copyright © 2022 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.