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Studying the Factors Affecting Tool Vibration and Surface Quality during Turning through 3D Cutting Simulation and Machine Learning Model
Nowadays, machining products, especially by turning methods, are more and more popular and require high-quality. With the development of science and technology, especially numerical computing technology and control technology, the application of these technological achievements to improve productivi...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10223796/ https://www.ncbi.nlm.nih.gov/pubmed/37241649 http://dx.doi.org/10.3390/mi14051025 |
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author | The Ho, Quang Ngoc Do, Thanh Trung Minh, Pham Son |
author_facet | The Ho, Quang Ngoc Do, Thanh Trung Minh, Pham Son |
author_sort | The Ho, Quang Ngoc |
collection | PubMed |
description | Nowadays, machining products, especially by turning methods, are more and more popular and require high-quality. With the development of science and technology, especially numerical computing technology and control technology, the application of these technological achievements to improve productivity and product quality has become increasingly essential. This study applies a simulation method considering the affecting factors of the vibration of the tool and the surface quality of the workpiece during turning. The study simulated and analyzed the characteristics of the cutting force and oscillation of the toolholder when stabilizing; at the same time, the study also simulated the behavior of the toolholder under the effect of cutting force and determined the finished surface quality through simulation. Additionally, the study utilized a machine learning model to examine the relationship between the toolholder length, cutting speed, feed rate, wavelength and surface roughness. The study found that tool hardness is the most crucial factor, and if the toolholder length exceeds the critical length, it leads to a rapid increase in roughness. In this study, the critical toolholder length was determined to be 60 mm, and this resulted in a corresponding surface roughness (Rz) of approximately 20 µm. |
format | Online Article Text |
id | pubmed-10223796 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-102237962023-05-28 Studying the Factors Affecting Tool Vibration and Surface Quality during Turning through 3D Cutting Simulation and Machine Learning Model The Ho, Quang Ngoc Do, Thanh Trung Minh, Pham Son Micromachines (Basel) Article Nowadays, machining products, especially by turning methods, are more and more popular and require high-quality. With the development of science and technology, especially numerical computing technology and control technology, the application of these technological achievements to improve productivity and product quality has become increasingly essential. This study applies a simulation method considering the affecting factors of the vibration of the tool and the surface quality of the workpiece during turning. The study simulated and analyzed the characteristics of the cutting force and oscillation of the toolholder when stabilizing; at the same time, the study also simulated the behavior of the toolholder under the effect of cutting force and determined the finished surface quality through simulation. Additionally, the study utilized a machine learning model to examine the relationship between the toolholder length, cutting speed, feed rate, wavelength and surface roughness. The study found that tool hardness is the most crucial factor, and if the toolholder length exceeds the critical length, it leads to a rapid increase in roughness. In this study, the critical toolholder length was determined to be 60 mm, and this resulted in a corresponding surface roughness (Rz) of approximately 20 µm. MDPI 2023-05-10 /pmc/articles/PMC10223796/ /pubmed/37241649 http://dx.doi.org/10.3390/mi14051025 Text en © 2023 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 The Ho, Quang Ngoc Do, Thanh Trung Minh, Pham Son Studying the Factors Affecting Tool Vibration and Surface Quality during Turning through 3D Cutting Simulation and Machine Learning Model |
title | Studying the Factors Affecting Tool Vibration and Surface Quality during Turning through 3D Cutting Simulation and Machine Learning Model |
title_full | Studying the Factors Affecting Tool Vibration and Surface Quality during Turning through 3D Cutting Simulation and Machine Learning Model |
title_fullStr | Studying the Factors Affecting Tool Vibration and Surface Quality during Turning through 3D Cutting Simulation and Machine Learning Model |
title_full_unstemmed | Studying the Factors Affecting Tool Vibration and Surface Quality during Turning through 3D Cutting Simulation and Machine Learning Model |
title_short | Studying the Factors Affecting Tool Vibration and Surface Quality during Turning through 3D Cutting Simulation and Machine Learning Model |
title_sort | studying the factors affecting tool vibration and surface quality during turning through 3d cutting simulation and machine learning model |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10223796/ https://www.ncbi.nlm.nih.gov/pubmed/37241649 http://dx.doi.org/10.3390/mi14051025 |
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