Abstract
A modified Taguchi-grey relational analysis method has been used in this research work to optimize the flat end milling process considering chip compression ratio (Q) and workpiece surface roughness (Ra) simultaneously. Both of the output responses are of equal importance. Therefore, optimization of the process considering both of them at the same time is more practical than optimizing the process considering only a single response at a time. The effectiveness of dry cutting has been experimentally investigated as compared to flooded lubrication condition giving equal weights to the two important process responses simultaneously. From the findings of the analysis and the experimental results, it is recommended to perform flat end milling operation on AISI 4340 steel in dry cutting condition at high speed and low feed rate. Flooded lubrication technique is not feasible for flat end milling of this steel. Performing dry machining on the recommended cutting parameters will lead to cleaner and sustainable production which aims at reducing/omitting waste and making the process environment-friendly. The order of significance of the factors based on the analysis, in sequence, is spindle speed, feed rate, and machining environment. Analysis of variance (ANOVA) performed on grey relational grades confirms the order of significance.
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Muaz, M., Choudhury, S.K. (2019). Simultaneous Optimization of Milling Process Responses for Nano-Finishing of AISI-4340 Steel Through Sustainable Production. In: Shunmugam, M.S., Kanthababu, M. (eds) Advances in Forming, Machining and Automation. AIMTDR 2018. Lecture Notes on Multidisciplinary Industrial Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-32-9417-2_29
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DOI: https://doi.org/10.1007/978-981-32-9417-2_29
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