Abstract
As manufacturing requires reliable models and methods for the prediction of output performance of machining processes, the quality of surface finish is an important requirement for many turned workpieces. This paper presents a method for surface roughness identification based on the measurement of root mean square for feed vibration of the cutting tool and workpiece surface temperature for machining mild steel in turning operation. Grey relational analysis method used and developed to identify the surface roughness utilizes the grey relational coefficient and grey relational grades for combined effects of two performance characteristics, namely tool vibration and workpiece surface temperature. The method proposed has been proved by series of cutting experiments that the values of surface roughness are well identified and would ideally be able to measure the surface roughness in-process in real time and also shows the ability to specify the cutting conditions as well.
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