RESUMEN
Modern machining requires reduction in energy usage, surface roughness, and burr width to produce finished or near-finished parts. To ensure high surface quality in machining processes, it is crucial to minimize surface finish and minimize burr width, which are considered as significant parameters as specific cutting energy. The objective of this study was to identify the optimal machining parameters for milling in order to minimize surface roughness, burr width, and specific cutting energy. To achieve this, the research investigated the impact of feed per tooth, cutting speed, depth of cut, and number of inserts on the responses across three intervals using Taguchi L9 array. Observing the responses by varying these parameters, underlined the need for multi objective optimisation. Machining conditions of 0.14 mm/tooth f z , 350 m/min V c and 2 mm ap using 1 cutting insert (exp no 9) was identified as the best machining run using grey relational analysis owing to its highest grey relational grade of 0.936. ANOVA examination identified cutting speed as the leading factor impacting the grey relational grade with 31.07 % contribution ratio, with the number of inserts, depth of cut, and feed per tooth also making notable contributions. Conclusively, machining parameters identified through response surface optimisation resulted in 21.69 % improvement in surface finish, 11.39 % reduction in specific energy consumption, and 6.2 % decrease in burr width on the down milling side albeit with an increase of 9 % in burr width on the up-milling side.
RESUMEN
Due to the increasing demand for higher production rates in the manufacturing sector, there is a need to manufacture finished or near-finished parts. Burrs and surface roughness are the two most important indicators of the surface quality of any machined parts. In addition to this, there is a constant need to reduce energy consumption during the machining operation in order to reduce the carbon footprint. Milling is one of the most extensively used cutting processes in the manufacturing industry. This research was conducted to investigate the effect of machining parameters on surface roughness, burr width, and specific energy consumption. In the present research, the machining parameters were varied using the Taguchi L9 array design of experiments, and their influence on the response parameters, including specific cutting energy, surface finish, and burr width, was ascertained. The response trends of burr width, energy consumption, and surface roughness with respect to the input parameters were analyzed using the main effect plots. Analysis of variance indicated that the cutting speed has contribution ratios of 55% and 47.98% of the specific cutting energy and burr width on the down-milling side, respectively. On the other hand, the number of inserts was found to be the influential member, with contribution ratios of 68.74% and 35% of the surface roughness and burr width on the up-milling side. The validation of the current design of the experiments was carried out using confirmatory tests in the best and worst conditions of the output parameters.