Experimental approached optimisation of a linear motion performance with grey hazy set and Taguchi analysis methods (GHST) for ball-screw table type

In end effect to control a path, tracking, or cutting motion of CNC milling machine or other applications of machine tools, controlling its actuator, specifically a linear table motion, becomes a classical matter to be solved in industries. By applying an optimisation of grey hazy set Taguchi (GHST) analysis methods, it might get a performance improvement of a linear motion of ball-screw table type. In this paper, it is aimed to enhance on multi-performance characteristics, namely, displacement, velocity and torque. An improvement of an average error of position accuracy is from the 0.2100 to 0.0137 mm (S/N ratio from 13.4023 to 37.1935 dB). Average error of position time is significantly improved from 0.1599 to 0.0293 s (S/N ratio from 15.9229 to 29.9305 dB). The average error of torsion standard deviation from 0.0924 Nm is improved to 0.0481 Nm (S/N ratio from 20.5970 to 26.3447 dB). This study indicated that GHST analysis approach might be applied successfully to table motion performance optimisation, which is determined by many parameters at multi-quality performances.