Optimization of Processes Parameters on Temperature Rise in CNC End Milling of Al 7068 using Hybrid Techniques

• Main Authors: Kaushik, V.S., Subramanian, M., Sakthivel, M.
• Format: Conference Proceeding
• Language: English
• Subjects: End Mill; Genetic algorithm; Mathematical Model; Response surface methodology; Temperature rise; Tool geometry
• ISSN: 2214-7853; 2214-7853
• DOI: 10.1016/j.matpr.2017.11.367

Measuring temperature and the estimation of heat distribution in metal cutting is important because, it’s controlling contribution on tool deflection, tool life, cutting force and vibration as well as, the quality of the machined part. In this paper a statistical model has been evolved to estimate the temperature rise in terms of design parameters such as helix angle, radial rake angle of cutting tool and machining parameters such as cutting speed, feed rate and axial depth of cut under dry condition. Response surface methodology, experimental design was employed for execution of experiments. The work piece material was Aluminum Al 7068and the tool was high speed steel end mill cutter with different tool geometry. The temperature rise was evaluated by using a pyrometer. The second order mathematical model in terms of machining parameters was evolved for estimatinga temperature rise. The competence of the model was computed by employing ANOVA. The direct and interaction effect of the process parameter with temperature rise were analyzed, which aided to select process parameter in order to keep temperature rise minimum, which indicates the immobility of end milling process. The predictive models in this study are believed to produce values of the temperature rise close to those readings recorded experimentally with a 95% confidence interval.A Matlab Genetic algorithm solver was utilized to do the optimization.