Skip to main content
SpringerLink
Log in

Comprehensive performance evaluation method of CNC servo turrets based on accuracy retentivity theory

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

Abstract

Repeated positioning accuracy, axial stiffness, cutting vibration, and rotation noise are key indexes that affect the comprehensive performance of computer numerical control (CNC) servo turrets. In order to evaluate the comprehensive performance of CNC servo turrets accurately, a new evaluation method is proposed based on accuracy retentivity theory in this paper. The retentivity degree evaluation methodology of performance indexes of the turret based on error threshold and 3δprinciple are proposed. Analytic hierarchy process (AHP) is used to calculate the weight of the influence degree on the turret, and the comprehensive performance retentivity degree of the turret is obtained. A comprehensive performance degradation model is established by using least squares. Finally, the comprehensive performance tracking test and analysis are conducted by taking two turrets as an example. The degradation law of the comprehensive performance retentivity degree of turrets is obtained, and the remaining performance retentivity time is predicted.

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
Fig. 13
Fig. 14
Fig. 15

Similar content being viewed by others

Data availability

Not applicable.

Code availability

Not applicable.

References

  1. Li CY., Wang W, Zhang YM., Guo S, Li ZY, Qiao CS. Indexing accuracy reliability sensitivity analysis of power tool turret, Eksploat. Niezawodn., 17 (2015) 27-34, 10.17531/ein.2015.1.4.

  2. Yang ZJ, Chen CH, Chen F, Li GF (2013) Process in the research of reliability technology of machine tools, Journal of Mechanical Engineering, 49:130-139, https://doi.org/10.3901/JME.2013.20.130 (in Chinese).

  3. He XC (2016) Recent development in reliability analysis of NC machine tools. Int J Adv Manuf Technol 85:115–131. https://doi.org/10.1007/s00170-015-7926-0

    Article  Google Scholar 

  4. Chen WZ, Hu W, Chen F, Xu BB, Li Q (2018) Designing of condition monitoring system for servo turret test platform, in: Conference on mechanical, automotive and materials engineering. IEEE. https://doi.org/10.1109/CMAME.2018.8592367

  5. Xu LJ, Chen N (2011) Natural properties analysis of an idler gear system of a new NC power turret. In: Zeng JM, Jiang ZY, Li TS, Yang DG, Kim YH (eds) Advances in Mechanical Design, Pts 1 and 2. Trans Tech Publications Ltd, Stafa-Zurich, pp 377–380. https://doi.org/10.4028/www.scientific.net/AMR.199-200.377

    Chapter  Google Scholar 

  6. Wang YQ, Wu JK, Liu HB, Kang K, Liu K (2018) Geometric accuracy long-term continuous monitoring using strain gauges for CNC machine tools. Int J Adv Manuf Technol 98:1145–1153. https://doi.org/10.1007/s00170-018-2337-7

    Article  Google Scholar 

  7. Ma JX, Zhao WH, Zhang GB (2015) Research status and analyses on accuracy retentivity of domestic CNC Machine Tools. China Mechanical Engineering 26:3108–3115. https://doi.org/10.3969/j.issn.1004-132X.2015.22.020 (in Chinese)

    Article  Google Scholar 

  8. Huang LL, Wang KS, Zha CL (2014) Study on ball screw accuracy reliability under radial force, in: Applied mechanics, materials and manufacturing Iv. Trans Tech Publications Ltd. https://doi.org/10.4028/www.scientific.net/AMM.670-671.1037

  9. Zhao JJ, Lin MX, Song XC, Guo QZ, Analysis of the precision sustainability of the preload double-nut ball screw with consideration of the raceway wear, Proc Inst Mech Eng Part J-J Eng. Tribol., 17, https://doi.org/10.1177/1350650119883484.

  10. Kamalzadeh A, Gordon DJ, Erkorkmaz K (2010) Robust compensation of elastic deformations in ball screw drives. Int J Mach Tool Manu 50:559–574. https://doi.org/10.1016/j.ijmachtools.2010.03.001

    Article  Google Scholar 

  11. Verl A, Frey S (2010) Correlation between feed velocity and preloading in ball screw drives. CIRP Ann-manuf Techn 59:429–432. https://doi.org/10.1016/j.cirp.2010.03.136

  12. Tan YQ, Zhang LH, Wang KF, Hu YF (2015) Modeling of precision retaining ability for slide guide of machine tool based on wear analysis. T Chin Soc Agric Mach 46:351–356. https://doi.org/10.6041/j.issn.1000-1298.2015.02.052 (in Chinese)

  13. Guo SJ, Tang SF, Zhang DS (2019) A Recognition methodology for the key geometric errors of a multi-axis machine tool based on accuracy retentivity Analysis. Complexity 2019:21. https://doi.org/10.1155/2019/8649496

    Article  Google Scholar 

  14. Jin T, Yan C, Chen C, Yang Z, Tian H, Guo J (2021) New domain adaptation method in shallow and deep layers of the CNN for bearing fault diagnosis under different working conditions. Int J Adv Manuf Technol. https://doi.org/10.1007/s00170-021-07385-9

  15. Niu P, Cheng Q, Liu Z, Chu H (2021) A machining accuracy improvement approach for a horizontal machining center based on analysis of geometric error characteristics. Int J Adv Manuf Technol 112(9–10):2873–2887. https://doi.org/10.1007/s00170-020-06565-3

  16. Standardization administration of China, metal-cutting machine tools-measurement method of sound pressure level:GB/T 16769-2008., 2008:2-4 (in Chinese).

  17. Herwan J, Kano S, Ryabov, Sawada OH, Kasashima N, Misaka T (2020) Predicting surface roughness of dry cut grey cast iron based on cutting parameters and vibration signals from different sensor positions in CNC turning. Int J Autom Technol 14:217–228. https://doi.org/10.20965/ijat.2020.p0217

    Article  Google Scholar 

  18. Azizi MW, Keblouti O, LBoulanouar L, Yallese MA (2020) Design optimization in hard turning of E19 alloy steel by analysing surface roughness, tool vibration and productivity. Struct Eng Mech 73:501–513. https://doi.org/10.12989/sem.2020.73.5.501

    Article  Google Scholar 

  19. Keblouti O, Boulanouar L, Azizi MW, Bouziane A (2019) Multi response optimization of surface roughness in hard turning with coated carbide tool based on cutting parameters and tool vibration. Struct Eng Mech 70:395–405. https://doi.org/10.12989/sem.2019.70.4.395

    Article  Google Scholar 

  20. Kim S, Ahmadi K (2019) Estimation of vibration stability in turning using operational modal analysis. Mech Syst Signal Process 130:315–332. https://doi.org/10.1016/j.ymssp.2019.04.057

    Article  Google Scholar 

  21. Bonda AGY, Nanda BK, Jonnalagadda S (2020) Vibration signature based stability studies in internal turning with a wavelet denoising preprocessor, Measurement, 154: 10.1016/j.measurement.2020.107520.

  22. Igba J, Alemzadeh K, Durugbo C, Eiriksson ET (2016) Analysing RMS and peak values of vibration signals for condition monitoring of wind turbine gearboxes. Renew Energy 91:90–106. https://doi.org/10.1016/j.renene.2016.01.006

    Article  Google Scholar 

  23. Wang YQ, Wu JK, Liu K, Liu HB, Liu ZS, Liang M (2019) Quantitative evaluation and error sensitivity analysis of accuracy retentivity of CNC machine tools. J Mech Eng 55:130–136. https://doi.org/10.3901/JME.2019.05.130 (in Chinese)

    Article  Google Scholar 

  24. Härdle WK, Simar L Applied multivariate statistical analysis. Springer International Publishing. https://doi.org/10.1007/978-3-030-26006-4

  25. Kuznetsov AP (2015) Probability methods of evaluation and control of precision reliability of metal-cutting machine tools under thermal effects. J Mach Manuf Reliab 44:363–371. https://doi.org/10.3103/s105261881504007x

    Article  Google Scholar 

  26. Fiorentini G, Sentana E, Calzolari G (2004) On the validity of the Jarque-Bera normality test in conditionally heteroskedastic dynamic regression models. Econ Lett 83:307–312. https://doi.org/10.1016/j.econlet.2003.10.023

    Article  MathSciNet  MATH  Google Scholar 

  27. Di Bona G, Silvestri A, Forcina A, Falcone D (2017) AHP-IFM target: an innovative method to define reliability target in an aerospace prototype based on analytic hierarchy process. Qual Reliab Eng Int 33:1731–1751. https://doi.org/10.1002/qre.2140

    Article  Google Scholar 

Download references

Acknowledgements

Our deepest gratitude goes first to the editors and reviewers for their constructive suggestions on the paper. And thank the authors of this paper’s references whose work have contributed greatly to the completion of this thesis. The authors would like to thank anonymous reviewers for their valuable comments and suggestions.

Funding

This work was funded in part by National Science and Technology Major Project (Grant No. 2019ZX04001024), National Natural Science Foundation of China (Grant Nos. 51675227 and 51975249), Jilin Province Science and Technology Development Funds (Grant Nos. 20180201007GX and 20190302017GX), Technology Development and Research of Jilin Province (Grant No. 2019C037-01), Changchun Science and Technology Planning Project (Grant No. 19SS011), and the Fundamental Research Funds for the Central Universities.

Author information

Authors and Affiliations

  1. Key Laboratory of CNC Equipment Reliability, Ministry of Education, Changchun, 130022, Jilin Province, China

    Tongtong Jin, Zhaojun Yang, Ronglin Yao, Chuanhai Chen, Yepeng Liu, Wei Hu & Hailong Tian

  2. School of Mechanical and Aerospace Engineering, Jilin University, Ren Min str. 5988, Changchun, 130022, Jilin Province, China

    Tongtong Jin, Zhaojun Yang, Ronglin Yao, Chuanhai Chen, Yepeng Liu, Wei Hu & Hailong Tian

  3. College of Materials Science and Engineering, Jilin University, Ren Min str. 5988, Changchun, 130022, Jilin Province, China

    Hailong Tian

Authors
  1. Tongtong Jin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zhaojun Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ronglin Yao
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Chuanhai Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yepeng Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Wei Hu
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Hailong Tian
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Zhaojun Yang: Conceptualization, Writing—review and editing, Supervision, Project administration, Funding acquisition. Ronglin Yao: Data curation, Software, Validation, Formal analysis, Writing—original draft, Visualization. Chuanhai Chen and Hailong Tian: Methodology, Writing—review and editing, Supervision. Yepeng Liu: Validation, Resources. Wei Hu: Validation, Resources. Zhaoming Su: Investigation.

Corresponding authors

Correspondence to Chuanhai Chen or Hailong Tian.

Ethics declarations

Conflict of interest

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

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jin, T., Yang, Z., Yao, R. et al. Comprehensive performance evaluation method of CNC servo turrets based on accuracy retentivity theory. Int J Adv Manuf Technol 117, 1209–1222 (2021). https://doi.org/10.1007/s00170-021-07810-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-021-07810-z

Keywords

Search

Navigation