Prediction of Cutting Temperature and Optimization of Process Parameters in Gear Skiving

Gear skiving has been paid more and more attention for high efficiency and wide application in gear manufacturing. In gear skiving, prediction of cutting temperature and optimization of process parameters have an important influence on increasing tool life, improving machining quality and decreasing...

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Main Authors: Wen Zijin, Chen Yongpeng
Format: Article
Language:zho
Published: Editorial Office of Journal of Mechanical Transmission 2024-04-01
Series:Jixie chuandong
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Online Access:http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2024.04.004
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author Wen Zijin
Chen Yongpeng
author_facet Wen Zijin
Chen Yongpeng
author_sort Wen Zijin
collection DOAJ
description Gear skiving has been paid more and more attention for high efficiency and wide application in gear manufacturing. In gear skiving, prediction of cutting temperature and optimization of process parameters have an important influence on increasing tool life, improving machining quality and decreasing residual stress. In this study, firstly, according to the kinematic theory of gear skiving, the entity models of the skiving tool and the workpiece are established, and then the cutting temperature nephograms on the rake face of single tooth during the cutting process are obtained based on Deform software. Secondly, aiming at the influences of the cutting velocity, feed rate and shaft angle on the maximum cutting temperature on the rake face, the prediction model of the cutting temperature under multiple parameters is established by response surface methodology. Finally, a method of process parameter optimization is proposed to maximize the machining efficiency with the constraint of cutting temperature. Combined with three groups of optimization examples, the validity of the cutting temperature prediction model is verified by comparing the error between the predicted values and simulation results under the optimized parameters. The results show that the shaft angle has the greatest effect on the cutting temperature under single parameter, the cutting velocity-shaft angle has the greatest effect on the cutting temperature under multiple parameters, and the optimized predicted values are within a reasonable error range from the simulation results. The results of this study provide methodological support for improving the machining quality and tool life in gear skiving.
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institution Kabale University
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spelling doaj-art-432a88fb1a0341099532d7159430d3162025-01-10T15:00:14ZzhoEditorial Office of Journal of Mechanical TransmissionJixie chuandong1004-25392024-04-0148263255347200Prediction of Cutting Temperature and Optimization of Process Parameters in Gear SkivingWen ZijinChen YongpengGear skiving has been paid more and more attention for high efficiency and wide application in gear manufacturing. In gear skiving, prediction of cutting temperature and optimization of process parameters have an important influence on increasing tool life, improving machining quality and decreasing residual stress. In this study, firstly, according to the kinematic theory of gear skiving, the entity models of the skiving tool and the workpiece are established, and then the cutting temperature nephograms on the rake face of single tooth during the cutting process are obtained based on Deform software. Secondly, aiming at the influences of the cutting velocity, feed rate and shaft angle on the maximum cutting temperature on the rake face, the prediction model of the cutting temperature under multiple parameters is established by response surface methodology. Finally, a method of process parameter optimization is proposed to maximize the machining efficiency with the constraint of cutting temperature. Combined with three groups of optimization examples, the validity of the cutting temperature prediction model is verified by comparing the error between the predicted values and simulation results under the optimized parameters. The results show that the shaft angle has the greatest effect on the cutting temperature under single parameter, the cutting velocity-shaft angle has the greatest effect on the cutting temperature under multiple parameters, and the optimized predicted values are within a reasonable error range from the simulation results. The results of this study provide methodological support for improving the machining quality and tool life in gear skiving.http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2024.04.004Gear skivingCutting temperatureProcess parametersFinite element simulationParameter optimization
spellingShingle Wen Zijin
Chen Yongpeng
Prediction of Cutting Temperature and Optimization of Process Parameters in Gear Skiving
Jixie chuandong
Gear skiving
Cutting temperature
Process parameters
Finite element simulation
Parameter optimization
title Prediction of Cutting Temperature and Optimization of Process Parameters in Gear Skiving
title_full Prediction of Cutting Temperature and Optimization of Process Parameters in Gear Skiving
title_fullStr Prediction of Cutting Temperature and Optimization of Process Parameters in Gear Skiving
title_full_unstemmed Prediction of Cutting Temperature and Optimization of Process Parameters in Gear Skiving
title_short Prediction of Cutting Temperature and Optimization of Process Parameters in Gear Skiving
title_sort prediction of cutting temperature and optimization of process parameters in gear skiving
topic Gear skiving
Cutting temperature
Process parameters
Finite element simulation
Parameter optimization
url http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2024.04.004
work_keys_str_mv AT wenzijin predictionofcuttingtemperatureandoptimizationofprocessparametersingearskiving
AT chenyongpeng predictionofcuttingtemperatureandoptimizationofprocessparametersingearskiving