Optimization of machining parameters in turning Nimonic-75 using machine vision and acoustic emission signals by Taguchi technique

Abstract To select the optimal conditions of cutting which potentially characterizes status of tool wear, acoustic emission (AE) and machine vision signals have been used and the same is presented in this paper. Nimonic 75 is turned using carbide insert with titanium coating and Taguchi’s L27 array has been adopted for parametric optimization. Speed of spindle, feed and cutting depth being varied during experimentation and the tabulated data in terms of AE and machine vision signals have been analyzed further. The parameters such as wear area, perimeter, AERMS and AECOUNT have been found responsive to tool wear and their relationship follows the time wear trend. Depth of cut is optimally constant in terms of the considered parameters whereas slight inexplicable variation in speed and feed has been observed and this inexplicit variation may be accounted for under noise, distortion and inconsistent illumination. At the obtained optimal cutting conditions machining was repeated and the results ascertained the correctness of the procedure adopted. In processing Nimonic75 using coated carbide insert, the results presented in this paper in terms of optimal parameters, could be used in the manufacturing sector that potentially enhances quality. Of all the non-traditional measuring techniques, machine vision and AE have proved better in measuring response parameters to optimize machining.