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Modeling and Optimization of Process Variables in Turning of Inconel 617 through Criteria Importance through Inter-Criteria and Weighted Aggregated Sum Product Assessment Methodology

Journal Article
2022-28-0524
ISSN: 2641-9637, e-ISSN: 2641-9645
DOI: https://doi.org/10.4271/2022-28-0524
Published December 23, 2022 by SAE International in United States
Modeling and Optimization of Process Variables in Turning of Inconel 617 through Criteria Importance through Inter-Criteria and Weighted Aggregated Sum Product Assessment Methodology
Sector:
Citation: Sundararajan, D., "Modeling and Optimization of Process Variables in Turning of Inconel 617 through Criteria Importance through Inter-Criteria and Weighted Aggregated Sum Product Assessment Methodology," SAE Int. J. Adv. & Curr. Prac. in Mobility 5(4):1653-1667, 2023, https://doi.org/10.4271/2022-28-0524.
Language: English

Abstract:

Inconel 617 is found in industrial sectors, including chemical, petrochemical, and nuclear. This work mainly concentrates on the analysis and the input-parameters optimization that minimizes the surface roughness, tool wear, and force in turning Inconel 617. Then, the chip and inserts are morphologically characterized using optical images. The residual plots showed that the accomplished investigational data are reliable and suitable for further study. Abrasion is accountable for tool wear mechanisms, and a rise in cutting speed affects the tool wear profile. Chip burr adhering to the flank surface is responsible for the surface roughness increase. Optimum cutting parameters are determined as 0.3mm depth of cut, 0.1mm/rev feed rate, and 220m/min cutting speed. Feed rate is the most influential parameter for process variables through Criteria Importance through Inter Criteria and weighted aggregated sum product assessment methodology.