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

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.

Keywords

measuring equipment / verification cycle / lifecycle / dynamic grey model / qualification rate / information system

References

[1] TienT 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

[2] TienT 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

[3] ChenC K, TienT L. A new forecasting method of discrete dynamic system[J]. Applied Mathematics and Computation, 1997, 86(1): 61-84

[4] DengJ LEssential Topics on Grey System: Theory and Applications[M], 1988, Beijing, China Ocean Press(in Chinese)

[5] LuoYou-xin, PenZhu, ZhangLong-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

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

[7] ChenC K, TienT 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

[8] BoxG E P, JenkinsG M, ReinselG CTime Series Analysis: Forecasting and Control[M], 1994, NJ, Prentice Hall Press Englewood cliffs

[9] DengJu-longForecast and Strategic Decision of Grey System[M], 1986, Wuhan, Huazhong University of Science and Technology Press(in Chinese)

[10] LuoYou-xin, CaiAn-hui, ZhangLong-ting. Grey problems of mechanical transmission system in a reliability study[J]. Internal J of Plant Eng and Management, 2001, 21(2): 104-110

[11] LuoYou-xin, ZhangLong-ting, GuoHui-xin. Grey system judgement on reliability of mechanical equipment[J]. Internal J of Plant Eng and Management, 2001, 21(3): 156-164

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

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

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

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

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