In-process surface roughness prediction using displacement signals from spindle motion |
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Authors: | Hun-Keun Chang Jin-Hyun Kim Il Hae Kim Dong Young Jang Dong Chul Han |
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Affiliation: | aSchool of Mechanical and Aerospace Engineering, Seoul National University, San 56-1, Shinlim-dong, Kwanak-gu, Seoul 151-742, South Korea;bCAMSYS Inc., 172 Gongreung 2-dong Nowon-gu, Seoul 139-743, South Korea;cDepartment of Industrial & Information Systems Engineering, Seoul National University of Technology, 172 Gongreung 2-dong Nowon-gu, Seoul 139-743, South Korea |
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Abstract: | A method to predict surface roughness in real time was proposed and its effectiveness was proved through experiment in this paper. To implement the proposed method in machining process, a sensor system to measure relative displacement caused by the cutting operation was developed. In this research, roughness of machined surface was assumed to be generated by the relative motion between tool and workpiece and the geometric factors of a tool. The relative motion caused by the machining process could be measured in process using a cylindrical capacitive displacement sensor (CCDS). The CCDS was installed at the quill of a spindle and the sensing was not disturbed by the cutting. The workpiece was NAK80 and TiAlN coated carbide end mills were used in the test. Model to predict surface roughness was developed. A simple linear regression model was developed to predict surface roughness using the measured signals of relative motion. Close relation between machined surface roughness and roughness predicted using the measured signals was verified with similarity of about 95%. |
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Keywords: | Surface roughness End milling Displacement sensor Spindle displacement |
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