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Tool Wear Prediction When Machining with Self-Propelled Rotary Tools

The performance of a self-propelled rotary carbide tool when cutting hardened steel is evaluated in this study. Although various models for evaluating tool wear in traditional (fixed) tools have been introduced and deployed, there have been no efforts in the existing literature to predict the progre...

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Autores principales: Umer, Usama, Mian, Syed Hammad, Mohammed, Muneer Khan, Abidi, Mustufa Haider, Moiduddin, Khaja, Kishawy, Hossam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9229163/
https://www.ncbi.nlm.nih.gov/pubmed/35744115
http://dx.doi.org/10.3390/ma15124059
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author Umer, Usama
Mian, Syed Hammad
Mohammed, Muneer Khan
Abidi, Mustufa Haider
Moiduddin, Khaja
Kishawy, Hossam
author_facet Umer, Usama
Mian, Syed Hammad
Mohammed, Muneer Khan
Abidi, Mustufa Haider
Moiduddin, Khaja
Kishawy, Hossam
author_sort Umer, Usama
collection PubMed
description The performance of a self-propelled rotary carbide tool when cutting hardened steel is evaluated in this study. Although various models for evaluating tool wear in traditional (fixed) tools have been introduced and deployed, there have been no efforts in the existing literature to predict the progression of tool wear while employing self-propelled rotary tools. The work-tool geometric relationship and the empirical function are used to build a flank wear model for self-propelled rotary cutting tools. Cutting experiments are conducted on AISI 4340 steel, which has a hardness of 54–56 HRC, at various cutting speeds and feeds. The rate of tool wear is measured at various intervals of time. The constant in the proposed model is obtained using genetic programming. When experimental and predicted flank wear are examined, the established model is found to be competent in estimating the rate of rotary tool flank wear progression.
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spelling pubmed-92291632022-06-25 Tool Wear Prediction When Machining with Self-Propelled Rotary Tools Umer, Usama Mian, Syed Hammad Mohammed, Muneer Khan Abidi, Mustufa Haider Moiduddin, Khaja Kishawy, Hossam Materials (Basel) Article The performance of a self-propelled rotary carbide tool when cutting hardened steel is evaluated in this study. Although various models for evaluating tool wear in traditional (fixed) tools have been introduced and deployed, there have been no efforts in the existing literature to predict the progression of tool wear while employing self-propelled rotary tools. The work-tool geometric relationship and the empirical function are used to build a flank wear model for self-propelled rotary cutting tools. Cutting experiments are conducted on AISI 4340 steel, which has a hardness of 54–56 HRC, at various cutting speeds and feeds. The rate of tool wear is measured at various intervals of time. The constant in the proposed model is obtained using genetic programming. When experimental and predicted flank wear are examined, the established model is found to be competent in estimating the rate of rotary tool flank wear progression. MDPI 2022-06-07 /pmc/articles/PMC9229163/ /pubmed/35744115 http://dx.doi.org/10.3390/ma15124059 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Umer, Usama
Mian, Syed Hammad
Mohammed, Muneer Khan
Abidi, Mustufa Haider
Moiduddin, Khaja
Kishawy, Hossam
Tool Wear Prediction When Machining with Self-Propelled Rotary Tools
title Tool Wear Prediction When Machining with Self-Propelled Rotary Tools
title_full Tool Wear Prediction When Machining with Self-Propelled Rotary Tools
title_fullStr Tool Wear Prediction When Machining with Self-Propelled Rotary Tools
title_full_unstemmed Tool Wear Prediction When Machining with Self-Propelled Rotary Tools
title_short Tool Wear Prediction When Machining with Self-Propelled Rotary Tools
title_sort tool wear prediction when machining with self-propelled rotary tools
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9229163/
https://www.ncbi.nlm.nih.gov/pubmed/35744115
http://dx.doi.org/10.3390/ma15124059
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