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The changing behavior of vibration signals with varying cutting parameters (cutting speed, feed rate and depth of cut) for turning hardened AISI52100 steel has been studied and reported. The vibration response of cutting tool in all three mutually perpendicular directions, namely, in feed Vx, radial Vy and, tangential Vz directions have been captured by mounting piezoelectric tri-axial accelerometer close to the cutting tool. Experiments are planned and conducted as per Central composite rotatable design of Surface response methodology. The second order multiple regression models are developed to correlate cutting parameters with vibration acceleration and surface roughness. The coefficient of regression R2 for all models is found close to 0.92 which shows that the developed models are reliable and provide an excellent explanation between the cutting parameter and the vibration of cutting tool within limits. The analysis of the results revealed that cutting conditions are having prominent and mixed type effect on vibration signals. The acceleration amplitude Vx, Vy and Vz increases with increase in cutting speed, and depth of cut. The vibration amplitude Vx, Vy and Vz initially increases as feed increases and, with further increase in feed, the vibration amplitude decreases. The surface roughness is highly influenced by the feed rate followed by cutting speed whereas the depth of cut was found less significant. The fluctuation in frequency is observed in all directions. However, the band of frequency remains within a certain range. Within selected cutting parameter range, the maximum acceleration amplitude is observed in frequency band of 4 kHz - 16 kHz.

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The stainless steel-304 is used in various surgical instruments due to its low carbon content and better corrosion resistance. SS-304 is machined using photochemical machining process (PCM) to obtain the components with micro-dimensions. The statistical methods of signal-to-noise (S/N) ratio and the analysis of variance (ANOVA) are applied to investigate effect of concentration of etchant, time of etching and temperature of etchant using DoE (L 27) orthogonal array. The performance characteristics like material removal rate (MRR), surface roughness (R a), undercut (U C) and etch factor (EF) are optimized during the investigation. The ANOVA technique is used to evaluate significance and percentage contribution of each parameter. The regression model for PCM of SS-304 is developed. The ANN technique is used to compare the predicted and experimental results of machining. The MRR, R a , EF and U C are showing improvement of 0.38 mm 3 /min, 1.271 µm, 0.11 and 0.028 mm, respectively, after the confirmatory test. The developed model is used to manufacture the array of micro-holes (5 × 5) with hole size of 220 µm, 280 µm and 370 µm which are used for metering of medicine in biomedical applications.

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