Optimisation of Cutting Parameters in Dry Turning of EN19 Steel Material

The thrust of cost-cutting, in manufacturing enterprises recently, had been focused on energy efficiency and quality improvement consideration, largely, as an effort to respond to environmental apprehensions regarding legislation, standardisation and market growth. In steel material mechanical cutting, on the lathe machine, the convergence adequacy of the cost-quality-time matrix effectually is contingent upon the supreme choice combination of the set cutting parameters. This experimental investigation examined, the minimisation of energy consumption and enhancement of the generated component surface quality, by optimising the applied machining parameter settings, as a means of fostering sustainability in the dry cutting of EN19 material by turning on the conventional lathe. Optimising mechanical machining operating parameters points to a significant challenge confronting the machine shops industry as they endeavour to realise reduced electrical energy consumption and improved component surface finish quality, generated from their businesses. The study aimed to reconnoiter and establish the association of the machining process strategy factors with the consequence of minimum energy consumption and surface smoothness quality, of the components, as the machining input factors were adjusted from minimum to the highest level of setting respectively. Taguchi's Full Factorial investigational strategy was employed in organising the empirical machining experiments. Analysis of variance (ANOVA) and the main effects plot (MEP) signal-to-noise ratio optimising computation were utilised, in the study, to determine the impact of the variable input-cutting process factors on the dependent parameters – surface roughness and energy use. Optimum, minimum energy consumption and good surface roughness generating, machining conditions were determined. Results of the all-encompassing experimental investigation yielded optimum cutting conditions of, respectively, energy consumption minimisation (100 m/min cutting speed, 0.1 mm/rev feed rate and 0o rake angle) and surface smoothness quality (100 m/min cutting speed, 0.4 mm/rev feed rate and 0o rake angle). Validation experiments corroborated the results findings of the developed model within 4.7% variability.