Signal-To- Noise-Ratios Evaluation of Industrial Machinery Utilization for Cutting Power and Sustainable Productivity

Abstract

Industrial machinery is power-driven equipment used by manufacturers in manufacturing or assembly plants. It is a special mechanically, electrically or electronically operated equipment designed to add value to a production chain. Several varieties of this equipment are available for different functions. Still, the lathe is the most versatile machine tool used in metal cutting, and the most common and essential operation is turning. In modern manufacturing, optimum quality responses can only be achieved by appropriately selecting and combining tool geometry and cutting conditions. This research focuses on the impacts of cutting variables on machining performance in turning AISI-1045 steel. The cutting power (P_c) was measured and predicted using multiple regression models, while metal removal rate (productivity) and machining time were evaluated. Machining time was also measured with a stopwatch. Signal-to-noiseThe signal-to-noise ratio was used to blend input factors for the most significant productivity, lowest cutting power, and least machining time. Statistical analysis of variance is used to estimate the influence of cutting variables on the respective performance parameters. The appropriate combination of cutting variables for minimum cutting power of 5.544kW was cutting speed (65m/min), feed rate (0.2mm/rev), depth of cut (0.5mm) and tool nose radius 0.25mm (Cs1k1d1R2, minimum machining time 0.46min was feed rate 0.4mm/rev, cut depth 0.5, cutting speed 101m/min (k3d1Cs3) and feed rare 0.2mm/rev, depth of cut 0.9mm, cutting speed 101m/min for maximum productivity 606.0131mm³/s. Feed rate is the most significant cutting variable that enhances the desired performance characteristics, while the depth of cut is the most minor factor.