Skip to main content
Log in

Dynamic grey model of verification cycle and lifecycle of measuring instrument and its application

  • Life Cycle Technology And Life Cycle Assessment
  • Published:
Journal of Central South University of Technology Aims and scope Submit manuscript

Abstract

Two dynamic grey models DGM (1, 1) for the verification cycle and the lifecycle of measuring instrument based on time sequence and frequency sequence were set up, according to the statistical feature of examination data and weighting method. By a specific case, i. e. vernier caliper, it is proved that the fit precision and forecast precision of the models are much higher, the cycles are obviously different under different working conditions, and the forecast result of the frequency sequence model is better than that of the time sequence model. Combining dynamic grey model and auto-manufacturing case the controlling and information subsystems of verification cycle and the lifecycle based on information integration, multi-sensor controlling and management controlling were given. The models can be used in production process to help enterprise reduce error, cost and flaw.

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

Access this article

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

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Tien T L. A Research on the prediction of machining accuracy by the deterministic grey dynamic model DG-DM (1,1,1)[J]. Applied Mathematics and Computation, 2005, 161(1): 923–945.

    Article  MATH  Google Scholar 

  2. Tien T L. A research on the deterministic grey dynamic model with multiple inputs DGDMMI(1, 1, 1)[J]. Applied Mathematics and Computation, 2003, 139: 401–416.

    Article  MATH  MathSciNet  Google Scholar 

  3. Chen C K, Tien T L. A new forecasting method of discrete dynamic system[J]. Applied Mathematics and Computation, 1997, 86(1): 61–84.

    Article  MATH  MathSciNet  Google Scholar 

  4. Deng J L. Essential Topics on Grey System: Theory and Applications[M]. Beijing: China Ocean Press, 1988. (in Chinese)

    Google Scholar 

  5. LUO You-xin, PEN Zhu, ZHANG Long-ting. Grey GM(1, 1) model with function-transfer method for the wear trend prediction and its application[J]. Internal J of Plant Eng and Management, 2001, 21(4): 220–232.

    Google Scholar 

  6. Zhang L. Research on machining error and forecasting model[J]. Acta Metrologia Sinica, 1998, 19(3): 183–188. (in Chinese)

    Google Scholar 

  7. Chen C K, Tien T L. The indirect measurement of tensile strength by the deterministic grey dynamic model DGDM(1, 1, 1)[J]. International Journal of Systems Science, 1997, 28(7): 683–690.

    MATH  Google Scholar 

  8. Box G E P, Jenkins G M, Reinsel G C. Time Series Analysis: Forecasting and Control[M]. NJ: Prentice Hall Press Englewood cliffs, 1994.

    Google Scholar 

  9. DENG Ju-long. Forecast and Strategic Decision of Grey System[M]. Wuhan: Huazhong University of Science and Technology Press, 1986. (in Chinese)

    Google Scholar 

  10. LUO You-xin, CAI An-hui, ZHANG Long-ting. Grey problems of mechanical transmission system in a reliability study[J]. Internal J of Plant Eng and Management, 2001, 21(2): 104–110.

    MathSciNet  Google Scholar 

  11. LUO You-xin, ZHANG Long-ting, GUO Hui-xin. Grey system judgement on reliability of mechanical equipment[J]. Internal J of Plant Eng and Management, 2001, 21(3): 156–164.

    Google Scholar 

  12. DENG Lang-ming. Study on verification cycle of measurement instrument[J]. Measurement Technology, 2003(5): 40’41. (in Chinese)

  13. ZHANG Jin-long, LEI Wen-qiang. Research of product lifecycle information model based on internet[J]. Soft Science, 2002, 16(1): 5–9.

    MathSciNet  Google Scholar 

  14. Theodoros E. Information integration and information strategies for adaptive enterprises[J]. European Management Journal, 2002, 20(5): 486–494.

    Article  Google Scholar 

  15. Aras N. Intelligent process monitoring by interfacing knowledge-based systems and multivariate statistical monitoring[J]. Journal of Process Control, 2000, 10(4): 341–350.

    Article  MathSciNet  Google Scholar 

  16. CHEN Jung-hui, Liao C M. Dynamic process fault monitoring based on neural network and PCA[J]. Journal of Process Control, 2002, 12(2): 277–289.

    Article  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Su Hai-tao PhD.

Additional information

Foundation item: Project (70272032) supported by the National Natural Science Foundation of China

Rights and permissions

Reprints and permissions

About this article

Cite this article

Su, Ht., Yang, Sy., Dong, H. et al. Dynamic grey model of verification cycle and lifecycle of measuring instrument and its application. J Cent. South Univ. Technol. 12, 86–89 (2005). https://doi.org/10.1007/s11771-005-0016-y

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11771-005-0016-y

Key words

CLC number

Navigation