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Optimization and prediction of CBN tool life sustainability during AA1100 CNC turning by response surface methodology

The aluminium alloy (AA1100) was familiar with automotive flexible shaft coupling applications due to its high strength, good machinability, and superior thermal and resistance to corrosion characteristics. Machining tool life drives the prominent role for deciding the product quality (machining) ac...

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Autores principales: H, Faisal M., Krishnan, A. Mohana, Prabagaran, S., Venkatesh, R., Kumar, D. Satish, Christysudha, J., Seikh, A.H., Iqbal, A., Ramaraj, Elangomathavan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10407727/
https://www.ncbi.nlm.nih.gov/pubmed/37560707
http://dx.doi.org/10.1016/j.heliyon.2023.e18807
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author H, Faisal M.
Krishnan, A. Mohana
Prabagaran, S.
Venkatesh, R.
Kumar, D. Satish
Christysudha, J.
Seikh, A.H.
Iqbal, A.
Ramaraj, Elangomathavan
author_facet H, Faisal M.
Krishnan, A. Mohana
Prabagaran, S.
Venkatesh, R.
Kumar, D. Satish
Christysudha, J.
Seikh, A.H.
Iqbal, A.
Ramaraj, Elangomathavan
author_sort H, Faisal M.
collection PubMed
description The aluminium alloy (AA1100) was familiar with automotive flexible shaft coupling applications due to its high strength, good machinability, and superior thermal and resistance to corrosion characteristics. Machining tool life drives the prominent role for deciding the product quality (machining) act aims to productivity target with zero interruptions. The novelty of this present investigation is the focus on increasing tool life during the complexity of CNC turning operation for AA1100 alloy by using CBN coated insert tool with varied input parameters of spindle speed (SS), feed rate (f), and depth of cut (DOC). Design of experiment (L16), analysis of variance (ANOVA) statistical system adopted with response surface methodology (RSM) is implemented for experimental analysis. The turning input parameters of SS, f and DOC are considered as factors and its SS (900, 1100, 1300, and 1500 rpm), f (0.1, 0.15, 0.2, and 0.25), and DOC (0.1, 0.2, 0.3, and 0.4 mm) values are treated as levels. The investigational analysis was made with the ANOVA technique and the desirability of high tool life with input turning parameters was optimized by RSM, and sample no 11/16 was predicted as high tool life and performed with extended working hours compared to other samples. The RSM optimized best turning parameter combinations are 0.1 mm DOC, 0.2mm/rev to 0.25mm/rev f, and 1300 rpm–1500 rpm SS, facilitating a higher tool life of more than 20min.
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spelling pubmed-104077272023-08-09 Optimization and prediction of CBN tool life sustainability during AA1100 CNC turning by response surface methodology H, Faisal M. Krishnan, A. Mohana Prabagaran, S. Venkatesh, R. Kumar, D. Satish Christysudha, J. Seikh, A.H. Iqbal, A. Ramaraj, Elangomathavan Heliyon Research Article The aluminium alloy (AA1100) was familiar with automotive flexible shaft coupling applications due to its high strength, good machinability, and superior thermal and resistance to corrosion characteristics. Machining tool life drives the prominent role for deciding the product quality (machining) act aims to productivity target with zero interruptions. The novelty of this present investigation is the focus on increasing tool life during the complexity of CNC turning operation for AA1100 alloy by using CBN coated insert tool with varied input parameters of spindle speed (SS), feed rate (f), and depth of cut (DOC). Design of experiment (L16), analysis of variance (ANOVA) statistical system adopted with response surface methodology (RSM) is implemented for experimental analysis. The turning input parameters of SS, f and DOC are considered as factors and its SS (900, 1100, 1300, and 1500 rpm), f (0.1, 0.15, 0.2, and 0.25), and DOC (0.1, 0.2, 0.3, and 0.4 mm) values are treated as levels. The investigational analysis was made with the ANOVA technique and the desirability of high tool life with input turning parameters was optimized by RSM, and sample no 11/16 was predicted as high tool life and performed with extended working hours compared to other samples. The RSM optimized best turning parameter combinations are 0.1 mm DOC, 0.2mm/rev to 0.25mm/rev f, and 1300 rpm–1500 rpm SS, facilitating a higher tool life of more than 20min. Elsevier 2023-07-28 /pmc/articles/PMC10407727/ /pubmed/37560707 http://dx.doi.org/10.1016/j.heliyon.2023.e18807 Text en © 2023 Published by Elsevier Ltd. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
H, Faisal M.
Krishnan, A. Mohana
Prabagaran, S.
Venkatesh, R.
Kumar, D. Satish
Christysudha, J.
Seikh, A.H.
Iqbal, A.
Ramaraj, Elangomathavan
Optimization and prediction of CBN tool life sustainability during AA1100 CNC turning by response surface methodology
title Optimization and prediction of CBN tool life sustainability during AA1100 CNC turning by response surface methodology
title_full Optimization and prediction of CBN tool life sustainability during AA1100 CNC turning by response surface methodology
title_fullStr Optimization and prediction of CBN tool life sustainability during AA1100 CNC turning by response surface methodology
title_full_unstemmed Optimization and prediction of CBN tool life sustainability during AA1100 CNC turning by response surface methodology
title_short Optimization and prediction of CBN tool life sustainability during AA1100 CNC turning by response surface methodology
title_sort optimization and prediction of cbn tool life sustainability during aa1100 cnc turning by response surface methodology
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10407727/
https://www.ncbi.nlm.nih.gov/pubmed/37560707
http://dx.doi.org/10.1016/j.heliyon.2023.e18807
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