Experimental investigation towards achieving optimised responses of Inconel 800 by high-speed dry turning

Inconel 800, widely used in defence, aviation, and oil refineries, is difficult to machine due to its toughness and work-hardening nature. This study examines the hard turning of Inconel 800, focusing on the impact of cutting speed, feed rate, depth of cut, and tool nose radius on key outcomes like surface roughness (SR), material removal rate (MRR), and cutting power (CP). Experiments were conducted using the Taguchi L9 orthogonal array, with analysis of variance (ANOVA) applied to determine the most significant factors. Grey relational analysis (GRA) was also used for multi-objective optimisation. Results indicated that feed rate had the largest influence, followed by tool nose radius, cutting speed, and depth of cut. The optimal machining parameters were a cutting speed of 182 m/min, a feed rate of 0.180 mm/rev, a depth of cut of 1 mm, and a tool nose radius of 1.2 mm.

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Publication Details

Journal
International Journal of Machining and Machinability of Materials
Published
2025-01-01
DOI
https://doi.org/10.1504/ijmmm.2025.147841
Primary Topic
Advanced machining processes and optimization
Type
article
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article

Experimental investigation towards achieving optimised responses of Inconel 800 by high-speed dry turning

Sovan Sahoo, Subhash Chandra Panja, Sumit Dhar
International Journal of Machining and Machinability of Materials
Advanced machining processes and optimization
article

Experimental investigation towards achieving optimised responses of Inconel 800 by high-speed dry turning

Sovan Sahoo, Subhash Chandra Panja, Sumit Dhar
article en

Abstract

Inconel 800, widely used in defence, aviation, and oil refineries, is difficult to machine due to its toughness and work-hardening nature. This study examines the hard turning of Inconel 800, focusing on the impact of cutting speed, feed rate, depth of cut, and tool nose radius on key outcomes like surface roughness (SR), material removal rate (MRR), and cutting power (CP). Experiments were conducted using the Taguchi L9 orthogonal array, with analysis of variance (ANOVA) applied to determine the most significant factors. Grey relational analysis (GRA) was also used for multi-objective optimisation. Results indicated that feed rate had the largest influence, followed by tool nose radius, cutting speed, and depth of cut. The optimal machining parameters were a cutting speed of 182 m/min, a feed rate of 0.180 mm/rev, a depth of cut of 1 mm, and a tool nose radius of 1.2 mm.

International Journal of Machining and Machinability of MaterialsVol. 27(3)
Jadavpur University (IN)
Climate action
Openalex Percentile: Top 81%
Advanced machining processes and optimization
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