Prediction of processing time and energy consumption and optimization of machining parameters in gear hobbing. (October 2019)
- Record Type:
- Journal Article
- Title:
- Prediction of processing time and energy consumption and optimization of machining parameters in gear hobbing. (October 2019)
- Main Title:
- Prediction of processing time and energy consumption and optimization of machining parameters in gear hobbing
- Authors:
- Huang, Wei
Yan, Chunping
Sun, Xiao
Huang, Feihu
Wang, Xingrong - Abstract:
- Abstract: This paper studied the characteristics of time and energy consumption of gear hobbing in batch production of small modulus gear. A method of integrating design of experiment, response surface method and multi-objective salp swarm algorithm (DOE/RSM/MMSA) is proposed for the complex optimization of machining parameters (namely hob rotation speed, cutting feed and depth of cut) in gear hobbing process. This paper uses three-level factorial design method to design gear hobbing experiments, and carries out mathematical and statistical analysis on the experimental results. It is found that cutting feed is the most significant machining parameter followed by hob rotation speed and depth of cut to reduce processing time and energy consumption. The prediction model of processing time and energy consumption in gear hobbing process is obtained through response surface methodology. The relative error rates of the predicted value and the actual value of the processing time and energy consumption are 0.11% and 0.09% respectively, indicating the validity of the model. Multi-objective salp swarm algorithm is used to optimize the machining parameters to minimizing processing time and energy consumption. Finally, through the comparison with the existing research results, it is concluded that the optimized machining parameters have better processing effect to achieve minimized processing time and energy consumption, which shows the effectiveness and rationality of the methodAbstract: This paper studied the characteristics of time and energy consumption of gear hobbing in batch production of small modulus gear. A method of integrating design of experiment, response surface method and multi-objective salp swarm algorithm (DOE/RSM/MMSA) is proposed for the complex optimization of machining parameters (namely hob rotation speed, cutting feed and depth of cut) in gear hobbing process. This paper uses three-level factorial design method to design gear hobbing experiments, and carries out mathematical and statistical analysis on the experimental results. It is found that cutting feed is the most significant machining parameter followed by hob rotation speed and depth of cut to reduce processing time and energy consumption. The prediction model of processing time and energy consumption in gear hobbing process is obtained through response surface methodology. The relative error rates of the predicted value and the actual value of the processing time and energy consumption are 0.11% and 0.09% respectively, indicating the validity of the model. Multi-objective salp swarm algorithm is used to optimize the machining parameters to minimizing processing time and energy consumption. Finally, through the comparison with the existing research results, it is concluded that the optimized machining parameters have better processing effect to achieve minimized processing time and energy consumption, which shows the effectiveness and rationality of the method proposed, and provides references for the decision-making of machining parameters in workshop. … (more)
- Is Part Of:
- IOP conference series. Volume 612:issue 3(2019)
- Journal:
- IOP conference series
- Issue:
- Volume 612:issue 3(2019)
- Issue Display:
- Volume 612, Issue 3 (2019)
- Year:
- 2019
- Volume:
- 612
- Issue:
- 3
- Issue Sort Value:
- 2019-0612-0003-0000
- Page Start:
- Page End:
- Publication Date:
- 2019-10
- Subjects:
- Materials science -- Periodicals
620.1105 - Journal URLs:
- http://iopscience.iop.org/1757-899X ↗
http://ioppublishing.org/ ↗ - DOI:
- 10.1088/1757-899X/612/3/032052 ↗
- Languages:
- English
- ISSNs:
- 1757-8981
- Deposit Type:
- Legaldeposit
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- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 12051.xml