Optimisation of multiple response characteristics on end milling of aluminium alloy using Taguchi-Grey relational approach. (August 2018)

• Record Type: Journal Article
• Authors: Unnikrishna Pillai, Jayakrishnan; Sanghrajka, Ikshit; Shunmugavel, Manikandakumar; Muthuramalingam, T.; Goldberg, Moshe; Littlefair, Guy
• Is Part Of: Measurement. Volume 124(2018)
• Page Start: 291
• Page End: 298
• Publication Date: 2018-08
• Subjects: Milling -- Grey relational analysis -- Robotic machining centres -- Optimisation; Weights and measures -- Periodicals; Measurement -- Periodicals; Measurement; Weights and measures; Periodicals; 530.8
• DOI: 10.1016/j.measurement.2018.04.052
• Languages: English
• ISSNs: 0263-2241

Abstract

Graphical abstract: Highlights: The tool path strategy plays a vital role on surface roughness and machining time. The optimum combination found as 14, 000 rpm spindle speed and 800 mm/min feed rate. The optimum combination tool path strategy is found as raster. Improvement of end milling in a 6-axis robotic machining centre is found. Abstract: Computer Aided Manufacturing improves productivity in the modern manufacturing environment, however optimisation of numerous factors involved in automated manufacturing or material removal environment is critical to produce high quality products. This present study aims to derive a set of optimal process parameter combination for end milling process of Al6005A alloy on a 6-axis robotic machining centre. In addition, the effect of process parameters such as tool path strategic, spindle speed and feed rate on the performance characteristics such as machining time and surface roughness have been studied using Taguchi-Grey relational optimisation method. From the experimental results, it has been found that the tool path strategy has the most considerable influence on the performance characteristics considered, since it can optimise the motion of the robotic machining arm to provide high productivity and product quality. The optimal combination of the process parameters has been estimated using Taguchi-Grey relational analysis and the improvement of performance characteristics has been verified in the confirmation test for optimising milling processes of robotic machining centers.