Bounded Intensity Process and Its Applications in Reliability Assessment of NC Machine Tools

Abstract

Abstract: Based on Akaike information criterion, Bayesian information criterion and the root-mean-square error of the fitting failure data, the best non-homogeneous Poisson process model of reliability analysis for repairable system was proposed. The point maximum likelihood and interval estimators of the parameters, as well as the reliability indices of the bounded intensity process model were given using the asymptotic lognormal distribution of the maximum likelihood estimation and the Fisher information matrix method. The failure data with time truncation of multiple NC machine tools were analyzed. The results show that the bounded intensity process is suitable for reliability assessment of deterioration machine tools with frequent maintenance actions.

Key words: bounded intensity process, repairable system, maximum likelihood estimation, NC machine tool, reliability assessment

CLC Number:

WANG Zhi-Ming-1, YANG Jian-Guo-2. Bounded Intensity Process and Its Applications in Reliability Assessment of NC Machine Tools[J]. Journal of Shanghai Jiaotong University, 2012, 46(10): 1622-1626.

References

［1］Marshall S E, Chukova S. On analysing warranty data from repairable items［J］. Quality and Reliability Engineering International, 2010, 26(1): 4352.
［2］敖长林, 李一军, 闫相斌, 等. 基于非齐次泊松过程的拖拉机发动机使用可靠性［J］. 机械工程学报, 2007, 43(10): 206210.
AO Changlin, LI Yijun, YAN Xiangbin, et al. Operational reliability of tractor engines based on nonhomogeneous Poisson process［J］. Chinese Journal of Mechanical Engineering, 2007, 43(10): 206210.
［3］TAN Furong, JIANG Zhibin, BAI Tongshuo. Reliability analysis of repairable systems using stochastic point processes ［J］. Journal of Shanghai Jiaotong University, 2008, 13(3): 366369.
［4］王智明, 杨建国, 王国强, 等. 多台数控机床最小维修的可靠性评估［J］. 哈尔滨工业大学学报, 2011, 43(7): 127130.
WANG Zhiming, YANG Jianguo, WANG Guoqiang, et al. Reliability assessment of multiple NC machine tools with minimal repair ［J］. Journal of Harbin Institute of Technology, 2011, 43(7): 127130.

［5］Pulcini G. A bounded intensity process for the reliability of repairable equipment ［J］. Journal of Quality Technology, 2001, 33(4): 480492.
［6］Louit D M, Pascual R, Jardine A K S. A practical procedure for the selection of timetofailure models based on the assessment of trends in maintenance data［J］. Reliability Engineering and System Safety, 2009, 94(10): 16181628.
［7］Viertava J, Vaurio J K. Testing statistical significance of trends in learning, ageing and safety indicators［J］. Reliability Engineering and System Safety, 2009, 94(6):11281132.
［8］Meeker W Q, Escobar L A. Statistical methods for reliability data［M］. New York: John Wiley & Sons, 1998.
［9］Nelson W. Accelerated testing: Statistical methods, test plans, and data analysis ［M］. New York: John Wiley & Sons, 1990.
［10］张英芝, 申桂香, 薛玉霞, 等. 随机截尾数控机床故障过程［J］. 吉林大学学报: 工学版, 2007, 37(6): 13461348.
ZHANG Yingzhi, SHEN Guixiang, XUE Yuxia, et al. Failure process for numerical control machine with random ending method ［J］. Journal of Jilin University: Engineering and Technology Edition, 2007, 37(6): 13461348.

[1]	FENG Pengfei, ZHOU Mi, LI Zhixuan, ZHU Guoqiang. Probability Statistical Model for Measured Ground Motion Based on Generalized Extreme Value Distribution [J]. Journal of Shanghai Jiao Tong University, 2025, 59(8): 1133-1144.
[2]	HU Xinming,WANG Deyu. Optimization of Ship Structures Using Ensemble of Surrogates with Recursive Arithmetic Average and Sequential Optimization and Reliability Assessment [J]. Journal of Shanghai Jiao Tong University, 2017, 51(2): 150-.
[3]	Gu Y.; Chen J.; Cheng Z.; Hu K.. Reliability analysis of multi-state repairable system with dynamic transition probabilities [J]. J Shanghai Jiaotong Univ Sci, 2016, 21(5): 615-620.
[4]	Liu Z.; Li Y.; Huang H.. Imprecise reliability assessment for heavy numerical control machine tools against small sample size problem [J]. J Shanghai Jiaotong Univ Sci, 2016, 21(5): 605-610.
[5]	Huang J.; Kong D.; Cui L.. Bayesian reliability assessment and degradation modeling with calibrations and random failure threshold [J]. J Shanghai Jiaotong Univ Sci, 2016, 21(4): 478-483.
[6]	WANG Wen-guang (王文光), DU Shi-jia* (杜时佳), CUI Li-rong (崔利荣). Multi-Point and Multi-Interval Availabilities for Markov Repairable Systems with History-Dependent Up and Down States [J]. Journal of shanghai Jiaotong University (Science), 2015, 20(3): 349-352.
[7]	REN Lina,RUI Zhiyuan,LIU Jun,LEI Chunli. Whole Lifecycle Reliability Assessment of Multiple NC Machine Tools with Minimal Repair [J]. Journal of Shanghai Jiaotong University, 2015, 49(01): 19-23.
[8]	FANG Pengya,CHANG Xinlong,HU Kuan,ZHANG Xiaojun. Optimization of Multidisciplinary Reliability Design Based on Interval Uncertainty [J]. Journal of Shanghai Jiaotong University, 2014, 48(10): 1451-1456.
[9]	WANG Zhiming1,YANG Jianguo2. Aperiodic Imperfect Preventive Maintenance Method of Bounded Intensity Process for Numerical Control Machine Tools [J]. Journal of Shanghai Jiaotong University, 2013, 47(11): 1661-1665.
[10]	WEN Qing-Guo, SONG Bao-Wei, WANG Peng, WANG Si-Ling. An Improved Kriging Approximation and Its Application to Shape Design Optimization of Torpedo [J]. Journal of Shanghai Jiaotong University, 2013, 47(04): 613-618.
[11]	张毅,杨建国. Grey Neural Network Modeling for Machine Tool Thermal Error [J]. Journal of Shanghai Jiaotong University, 2011, 45(11): 1581-1586.