Skip to main content
SpringerLink
Log in

Multi-objective process parameter optimization considering minimum thermal accumulation on spindles of dry hobbing machine

  • ORIGINAL ARTICLE
  • Published:
The International Journal of Advanced Manufacturing Technology Aims and scope Submit manuscript

Abstract

The thermal accumulation problem of the dry hobbing machine spindles is quite serious and is an essential reason for gear machining accuracy. Hence, this study focuses on thermal accumulation modeling and optimization for dry hobbing machine spindles. Firstly, the thermal accumulation characteristics of the hob spindle and workbench spindle in dry hobbing machine are clarified, and the effect mechanism of thermal accumulation on the machine spindles deformation is revealed. Then, the thermal accumulation models for the hob spindle and workbench spindle in dry hobbing machine are established, respectively, and the characteristic parameters of the thermal accumulation models are quantitatively analyzed. Finally, a multi-objective optimization approach for the process parameters considering minimum thermal accumulation in dry hobbing machine spindles is proposed, and a case study is conducted. The experimental results indicate that the thermal accumulation of the hob spindle and workbench spindle is reduced by 11.17% and 19.3%, respectively; the hobbing efficiency is increased by 8.22% as well as effectively reducing the average temperature of the machine spindles and controlling the gear’s M-value, which proves the effectiveness of proposed approach.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

Data availability

The datasets used or analyzed during the current study are available from the corresponding author on reasonable request.

References

  1. Pawanr S, Garg G, Routroy S (2022) A novel approach to model the energy consumption of machine tools for machining cylindrical parts. J Manuf Process 84:28–42

    Article  Google Scholar 

  2. Liu C, He Y, Wang Y, Li Y, Wang S, Wang L, Wang Y (2020) Effects of process parameters on cutting temperature in dry machining of ball screw. ISA Trans 101:493–502

    Article  Google Scholar 

  3. Gupta K, Laubscher R, Davim J, Jain N (2016) Recent developments in sustainable manufacturing of gears: a review. J Clean Prod 112:3320–3330

    Article  Google Scholar 

  4. Sreejith P, Ngoi B (2000) Dry machining: Machining of the future. J Mater Process Technol 101:287–291

    Article  Google Scholar 

  5. Li Z, Wang B, Zhu B, Wang Q, Zhu W (2022) Thermal error modeling of electrical spindle based on optimised ELM with marine predator algorithm. Case Stud Thermal Eng 38:102326

    Article  Google Scholar 

  6. Bitar-Nehme E, Mayer J (2018) Modelling and compensation of dominant thermally induced geometric errors using rotary axes’ power consumption. CIRP Ann 67:547–550

    Article  Google Scholar 

  7. Zhang C, Gao F, Yan L (2017) Thermal error characteristic analysis and modeling for machine tools due to time-varying environmental temperature. Precis Eng 47:231–238

    Article  Google Scholar 

  8. Zhao Z, Wang Y, Wang Z, Liu J (2019) Thermal analysis for the large precision EDM machine tool considering the spark energy during long-time processing. J Mech Sci Technol 33:773–782

    Article  Google Scholar 

  9. Yao X, Du Z, Ge G, Yang J (2020) Dynamic temperature gradient and unfalsified control approach for machine tool thermal error compensation. J Mech Sci Technol 34:319–331

    Article  Google Scholar 

  10. Feng W, Li Z, Gu Q, Yang J (2015) Thermally induced positioning error modelling and compensation based on thermal characteristic analysis. Int J Mach Tools Manuf 93:26–36

    Article  Google Scholar 

  11. Wei X, Ye H, Miao E, Pan Q (2022) Thermal error modeling and compensation based on Gaussian process regression for CNC machine tools. Precis Eng 77:65–76

    Article  Google Scholar 

  12. Narendra Reddy T, Shanmugaraj V, Vinod P, Gopi Krishna S (2020) Real-time thermal error compensation strategy for precision machine tools. Mater Today: Proc 22:2386–2396

    Google Scholar 

  13. Zhu L, Cao H, Zeng D, Yang X, Li B (2017) Multi-variable driving thermal energy control model of dry hobbing machine tool. Int J Adv Manuf Technol 92:259–275

    Article  Google Scholar 

  14. Kadashevich I, Beutner M, Karpuschewski B, Halle T (2015) A novel simulation approach to determine thermally induced geometric deviations in dry gear hobbing. Procedia CIRP 31:483–488

    Article  Google Scholar 

  15. Li X, Yang Y, Zou Z, Liu Z, Wang L, Tang Q (2019) Critical study on the thermal-structural characteristics of worktable assembly of a dry hobbing machine. Int J Adv Manuf Technol 100:179–188

    Article  Google Scholar 

  16. Yang X, Cao H, Li B, Jafar S, Zhu L (2018) A thermal energy balance optimisation model of cutting space enabling environmentally benign dry hobbing. J Clean Prod 172:2323–2335

    Article  Google Scholar 

  17. Li B, Cao H, Yang X, Jafar S, Zeng D (2018) Thermal energy balance control model of motorised spindle system enabling high-speed dry hobbing process. J Manuf Process 35:29–39

    Article  Google Scholar 

  18. Yang X, Zeng L, Chen P, Du Y, Li B (2022) Complex characteristics and multi-dimensional control strategies of heat flow in dry gear hobbing machines. China Mech Eng 33:623–629

    Google Scholar 

  19. Yang X, Chen P (2022) Heat transfer enhancement strategies for eco-friendly dry hobbing considering the heat exchange capacity of chips. Case Stud Therm Eng 29:101716

    Article  Google Scholar 

  20. Li B, Yang X, Du Y, He L (2022) Optimisation of chip repose angle in dry hobbing machine considering minimum thermal accumulation on workbench. Int J Adv Manuf Technol 122:1821–1833

    Article  Google Scholar 

  21. Incropera F, Dewitt D, Bergman T, Lavine A (2007) Fundamentals of heat and mass transfer. John Wiley & Sons Inc

    Google Scholar 

  22. Li Y, Zhou S, Liu J, Tong J, Dang J, Yang F, Ouyang M (2023) Multi-objective optimisation of the Atkinson cycle gasoline engine using NSGA III coupled with support vector machine and back-propagation algorithm. Energy 262:125262

    Article  Google Scholar 

  23. Li Z, Luo Z, Wang Y, Fan G, Zhang J (2022) Suitability evaluation system for the shallow geothermal energy implementation in region by entropy weight method and TOPSIS method. Renew Energy 184:564–576

    Article  Google Scholar 

Download references

Funding

This work was supported by the Key Projects of Strategic Scientific and Technological Innovation Cooperation of National Key R&D Program of China (Grant No. 2020YFE0201000), the National Natural Science Foundation of China (NSFC) (Grant No. 51905059), the China Postdoctoral Science Foundation (Grant No. 2021M693748), the Innovative Research Group of Universities in Chongqing (Grant No. CXQT21024), the Special Funding for Postdoctoral Research Projects in Chongqing (Grant No. 2021XM2020), and the Graduate Research Innovation Project (Grant No. CYS22621).

Author information

Authors and Affiliations

  1. Chongqing Key Laboratory of Manufacturing Equipment Mechanism Design and Control, Chongqing Technology and Business University, Chongqing, 400067, China

    Bo Li, Yanbin Du, Xiao Yang, Guohua He & Lang He

  2. Chongqing Machine Tool (Group) Co., Ltd, Chongqing, 400055, China

    Yanbin Du & Xiao Yang

Authors
  1. Bo Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yanbin Du
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Xiao Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Guohua He
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Lang He
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Bo Li contributed to the conception of the study; Bo Li, Yanbin Du, and Xiao Yang contributed significantly to analysis and manuscript preparation; Guohua He and Lang He helped perform the analysis with constructive discussions.

Corresponding author

Correspondence to Yanbin Du.

Ethics declarations

Ethical approval

Not applicable.

Consent to participate

Not applicable.

Consent for publication

Yes.

Competing interests

The authors declare no competing interests.

Additional information

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, B., Du, Y., Yang, X. et al. Multi-objective process parameter optimization considering minimum thermal accumulation on spindles of dry hobbing machine. Int J Adv Manuf Technol 126, 4337–4351 (2023). https://doi.org/10.1007/s00170-023-11371-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-023-11371-8

Keywords

Search

Navigation