Influence of Tool Wear and Workpiece Diameter on Surface Quality and Prediction of Surface Roughness in Turning

In turning, tool wear and cutting vibration are inevitable, which have great influence on surface quality. Analyzing the influence mechanism of tool wear and cutting vibration on surface quality is important to achieve the accurate prediction of surface roughness before machining and improve machining quality. In this paper, a turning vibration experiment is conducted to reveal that the diameter of shafts is an important factor affecting the vibration amplitude and frequency. In addition, based on machining parameters, tool wear and workpiece diameter, this empirical model, the response surface method and a support vector machine are used to model and predict surface roughness. The fitting accuracy, prediction accuracy and generalization performance of the proposed methods are compared in detail. The results show that the response surface modeling method has the highest fitting accuracy, but the exponential empirical modeling method has the highest prediction accuracy and best generalization performance. Additionally, the prediction results indicate that the surface roughness increases with the increase in tool wear and decreases with the increase in workpiece diameter.

Authors

Institutions

Publication Details

Journal
Metals
Published
2024-10-23
DOI
https://doi.org/10.3390/met14111205
Citations
9
Primary Topic
Advanced machining processes and optimization
Type
article
Field-Weighted Citation Impact
1.91
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Influence of Tool Wear and Workpiece Diameter on Surface Quality and Prediction of Surface Roughness in Turning

Guoyong Zhao, Chunxiao Li, Limin Liu, Guangteng Zhang et al.
9 citations
Metals
Advanced machining processes and optimization
1.91
article

Influence of Tool Wear and Workpiece Diameter on Surface Quality and Prediction of Surface Roughness in Turning

Guoyong Zhao, Chunxiao Li, Limin Liu, Guangteng Zhang, Fandi Zeng, Dong Ji, Zhihuan Zhao
article en
9 citations

Abstract

In turning, tool wear and cutting vibration are inevitable, which have great influence on surface quality. Analyzing the influence mechanism of tool wear and cutting vibration on surface quality is important to achieve the accurate prediction of surface roughness before machining and improve machining quality. In this paper, a turning vibration experiment is conducted to reveal that the diameter of shafts is an important factor affecting the vibration amplitude and frequency. In addition, based on machining parameters, tool wear and workpiece diameter, this empirical model, the response surface method and a support vector machine are used to model and predict surface roughness. The fitting accuracy, prediction accuracy and generalization performance of the proposed methods are compared in detail. The results show that the response surface modeling method has the highest fitting accuracy, but the exponential empirical modeling method has the highest prediction accuracy and best generalization performance. Additionally, the prediction results indicate that the surface roughness increases with the increase in tool wear and decreases with the increase in workpiece diameter.

MetalsVol. 14(11)
Shandong University of Technology (CN)
Openalex Percentile: Top 15%
Advanced machining processes and optimization
1.91
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.