Multi-Response Optimization of Face Milling Performance Considering Tool Path Strategies in Machining of Al-2024

• Main Authors: Raneen Abd Ali, Mozammel Mia, Aqib Mashood Khan, Wenliang Chen, Munish Kumar Gupta, Catalin Iulian Pruncu
• Format: Article
• Language: English
• Published: MDPI AG 2019-03-01
• Series: Materials
• Subjects: face milling; surface roughness; grey relation analysis; tool path strategy; multi-objective optimization
• Online Access: https://www.mdpi.com/1996-1944/12/7/1013

It is hypothesized that the orientation of tool maneuvering in the milling process defines the quality of machining. In that respect, here, the influence of different path strategies of the tool in face milling is investigated, and subsequently, the best strategy is identified following systematic optimization. The surface roughness, material removal rate and cutting time are considered as key responses, whereas the cutting speed, feed rate and depth of cut were considered as inputs (quantitative factors) beside the tool path strategy (qualitative factor) for the material Al 2024 with a torus end mill. The experimental plan, i.e., 27 runs were determined by using the Taguchi design approach. In addition, the analysis of variance is conducted to statistically identify the effects of parameters. The optimal values of process parameters have been evaluated based on Taguchi-grey relational analysis, and the reliability of this analysis has been verified with the confirmation test. It was found that the tool path strategy has a significant influence on the end outcomes of face milling. As such, the surface topography respective to different cutter path strategies and the optimal cutting strategy is discussed in detail.