OBRABOTKAMETALLOV MATERIAL SCIENCE Том 23 № 3 2021 EQUIPMEN . INSTRUM TS Vol. 7 No. 1 2025 Fig. 5. External view of the device for studying and simulating the electrochemical grinding process: 1 – current source for electrochemical process; 2 – engraver; 3 – linear drive; 4 – electrolyte container; 5 – sample basing and feeding equipment; 6 – upgraded collet chuck; 7 – time relay; 8 – current source for linear drive electric motor Ta b l e 4 Initial data for planning and processing experimental results Factors Levels Variation interval Upper Xi = +1 Primary (Zero) Xi = 0 Lower Xi = −1 X1 – cutting depth, t (mm) 0.06 0.05 0.04 0.01 X2 – feed rate, S (mm/min) 250 240 230 10 X3 – cutting speed, V (m/s) 6 5 4 1 The planning and processing of experimental results were performed using the standard methodology for preparing and conducting a full factorial experiment. The initial data for planning and processing experimental results are presented in Table 4. The regression equation obtained from the analysis of experimental data reflects the dependence of surface roughness on mechanical processing modes and is expressed as follows: 2.67 106.17 0.43 19,55 0.013 0.004 0.94 0.08 . t tS tV S SV V tSV = − + − − + − + + Ra The resulting model enables the determination of optimal mechanical cutting conditions and the assessment of their impact on the quality of the machined surface. Specific cases of the system response surfaces with constant cutting parameters at the zero level of variation are shown in Figs. 6–8. The obtainedmodel and response surfaces enable the prediction of surface roughness variation depending on grinding modes and represent an empirical model of the system under consideration.
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