Optimization of the tool wear and surface roughness in the high-speed dry turning of Inconel 800

AbstractMachining of Inconel 800 superalloy is associated with inherent issues like lower tool life and lower quality of machined surface owing to the work-hardening nature of the superalloy and increased mechanical and thermal stresses. The employment of cutting fluid in machining negatively affect...

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Main Authors: Ganesha Prasad, G. S. Vijay, Raghavendra C. Kamath, Harshit Jairaj Hemmady
Format: Article
Language:English
Published: Taylor & Francis Group 2024-12-01
Series:Cogent Engineering
Subjects:
Online Access:https://www.tandfonline.com/doi/10.1080/23311916.2024.2308993
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author Ganesha Prasad
G. S. Vijay
Raghavendra C. Kamath
Harshit Jairaj Hemmady
author_facet Ganesha Prasad
G. S. Vijay
Raghavendra C. Kamath
Harshit Jairaj Hemmady
author_sort Ganesha Prasad
collection DOAJ
description AbstractMachining of Inconel 800 superalloy is associated with inherent issues like lower tool life and lower quality of machined surface owing to the work-hardening nature of the superalloy and increased mechanical and thermal stresses. The employment of cutting fluid in machining negatively affects the locale. Hence, dry machining is a feasible alternate solution. This work aims to optimize the cutting parameters (CP): cutting speed, feed rate and depth of cut in the high-speed dry turning of Inconel 800 employing an uncoated carbide insert to minimize the responses: tool wear (TW) and surface roughness (SR). The superalloy machining is conducted as per the experimental runs designed applying the Taguchi analysis. Then, the effects and contributions of the CP on the outputs were examined employing the signal-to-noise (S/N) ratio and the analysis of variance (ANOVA). Additionally, the multi-objective optimization (MOO) method grey relational analysis was employed to optimize CP. The results of the research work showed that cutting speed, feed rate, and depth of cut have noteworthy sway on TW and SR with a % contribution of 33.3, 13.8 and 23.7, respectively. Additionally, evaluation of SEM images of the cutting insert revealed that the abrasion, adhesion and diffusion are the primary wear mechanisms leading to abrasion groves, crater, chipping, built-up-edge and notch formation.
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spelling doaj.art-e732d1466a104577bafd2dd311ed54d42024-02-02T10:03:23ZengTaylor & Francis GroupCogent Engineering2331-19162024-12-0111110.1080/23311916.2024.2308993Optimization of the tool wear and surface roughness in the high-speed dry turning of Inconel 800Ganesha Prasad0G. S. Vijay1Raghavendra C. Kamath2Harshit Jairaj Hemmady3Department of Mechanical and Industrial Engineering, Manipal Institute of Technology, Manipal, Manipal Academy of Higher Education, Manipal, Karnataka, IndiaDepartment of Mechanical and Industrial Engineering, Manipal Institute of Technology, Manipal, Manipal Academy of Higher Education, Manipal, Karnataka, IndiaDepartment of Mechanical and Industrial Engineering, Manipal Institute of Technology, Manipal, Manipal Academy of Higher Education, Manipal, Karnataka, IndiaDepartment of Mechanical and Industrial Engineering, Manipal Institute of Technology, Manipal, Manipal Academy of Higher Education, Manipal, Karnataka, IndiaAbstractMachining of Inconel 800 superalloy is associated with inherent issues like lower tool life and lower quality of machined surface owing to the work-hardening nature of the superalloy and increased mechanical and thermal stresses. The employment of cutting fluid in machining negatively affects the locale. Hence, dry machining is a feasible alternate solution. This work aims to optimize the cutting parameters (CP): cutting speed, feed rate and depth of cut in the high-speed dry turning of Inconel 800 employing an uncoated carbide insert to minimize the responses: tool wear (TW) and surface roughness (SR). The superalloy machining is conducted as per the experimental runs designed applying the Taguchi analysis. Then, the effects and contributions of the CP on the outputs were examined employing the signal-to-noise (S/N) ratio and the analysis of variance (ANOVA). Additionally, the multi-objective optimization (MOO) method grey relational analysis was employed to optimize CP. The results of the research work showed that cutting speed, feed rate, and depth of cut have noteworthy sway on TW and SR with a % contribution of 33.3, 13.8 and 23.7, respectively. Additionally, evaluation of SEM images of the cutting insert revealed that the abrasion, adhesion and diffusion are the primary wear mechanisms leading to abrasion groves, crater, chipping, built-up-edge and notch formation.https://www.tandfonline.com/doi/10.1080/23311916.2024.2308993Dry turninggrey relational analysisInconel 800flank wearsurface roughnessD T Pham, University of Birmingham, United Kingdom
spellingShingle Ganesha Prasad
G. S. Vijay
Raghavendra C. Kamath
Harshit Jairaj Hemmady
Optimization of the tool wear and surface roughness in the high-speed dry turning of Inconel 800
Cogent Engineering
Dry turning
grey relational analysis
Inconel 800
flank wear
surface roughness
D T Pham, University of Birmingham, United Kingdom
title Optimization of the tool wear and surface roughness in the high-speed dry turning of Inconel 800
title_full Optimization of the tool wear and surface roughness in the high-speed dry turning of Inconel 800
title_fullStr Optimization of the tool wear and surface roughness in the high-speed dry turning of Inconel 800
title_full_unstemmed Optimization of the tool wear and surface roughness in the high-speed dry turning of Inconel 800
title_short Optimization of the tool wear and surface roughness in the high-speed dry turning of Inconel 800
title_sort optimization of the tool wear and surface roughness in the high speed dry turning of inconel 800
topic Dry turning
grey relational analysis
Inconel 800
flank wear
surface roughness
D T Pham, University of Birmingham, United Kingdom
url https://www.tandfonline.com/doi/10.1080/23311916.2024.2308993
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