Evaluation of Shewhart time-between-events-and-amplitude control charts for correlated data

被引:9
|
作者
Rahali, Dorra [1 ,2 ,3 ,4 ]
Castagliola, Philippe [1 ,2 ]
Taleb, Hassen [4 ,5 ]
Khoo, Michael Boon Chong [6 ]
机构
[1] Univ Nantes, Nantes, France
[2] LS2N UMR CNRS 6004, Nantes, France
[3] Univ Tunis, Tunis, Tunisia
[4] ARBRE Lab, Tunis, Tunisia
[5] Univ Carthage, Inst Super Commerce & Comptabilite, Tunis, Tunisia
[6] Univ Sains Malaysia, Sch Math Sci, George Town, Malaysia
关键词
amplitude; copulas; machine breakdowns; statistical process monitoring; time between events; CUSUM CHART; MAGNITUDE; FREQUENCY; MODEL;
D O I
10.1002/qre.2731
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In recent years, several techniques based on control charts have been developed for thesimultaneousmonitoring of the time intervalTand the amplitudeXof events, known as time-between-events-and-amplitude (TBEA) charts. However, the vast majority of the existing works have some limitations. First, they usually focus on statistics based on the ratioXT, and second, they only investigate a reduced number of potential distributions, that is, the exponential distribution forTand the normal distribution forX. Moreover, until now, very few research papers have considered the potential dependence betweenTandX. In this paper, we investigate three different statistics, denoted asZ(1),Z(2), andZ(3), for monitoring TBEA data in the case of three potential distributions (gamma, normal, and Weibull), for bothTandX, using copulas as a mechanism to model the dependence. An illustrative example considering times between machine breakdowns and associated maintenance illustrates the use of TBEA control charts.
引用
收藏
页码:219 / 241
页数:23
相关论文
共 50 条
  • [31] Phase I control charts for times between events
    Jones, LA
    Champ, CW
    QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, 2002, 18 (06) : 479 - 488
  • [32] Robust control charts for time series data
    Croux, Christophe
    Gelper, Sarah
    Mahieu, Koen
    EXPERT SYSTEMS WITH APPLICATIONS, 2011, 38 (11) : 13810 - 13815
  • [33] Original Observations-based Control Charts for Monitoring the Mean of Auto-correlated Processes: A Comparison among Modified Shewhart, Modified EWMA, and ARMAST charts
    Ulkhaq, M. Mujiya
    Dewanta, Favian
    3RD INTERNATIONAL MATERIALS, INDUSTRIAL AND MANUFACTURING ENGINEERING CONFERENCE (MIMEC2017), 2017, 1902
  • [34] Monitoring processes with multiple dependent production lines using time between events control charts
    Ahmad, Hussam
    Ahmadi Nadi, Adel
    Amini, Mohammad
    Gildeh, Bahram Sadeghpour
    QUALITY ENGINEERING, 2023, 35 (04) : 639 - 668
  • [35] An ARL-unbiased design of time-between-events control charts with runs rules
    Cheng, Chuen-Sheng
    Chen, Pei-Wen
    JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, 2011, 81 (07) : 857 - 871
  • [36] Comparison of Two Control Charts for Correlated High Dimensional Data Streams
    BIAN Shui-xian
    ZI Xue-min
    InternationalJournalofPlantEngineeringandManagement, 2017, 22 (01) : 33 - 40
  • [37] Economic design of exponential charts for time between events monitoring
    Zhang, CW
    Xie, M
    Goh, TN
    INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2005, 43 (23) : 5019 - 5032
  • [38] Shewhart-type control charts and functional data analysis for water quality analysis based on a global indicator
    Iglesias, C.
    Sancho, J.
    Pineiro, J. I.
    Martinez, J.
    Pastor, J. J.
    Taboada, J.
    DESALINATION AND WATER TREATMENT, 2016, 57 (06) : 2669 - 2684
  • [39] Comparison of fixed versus variable sampling interval Shewhart x¯ control charts in the presence of positively autocorrelated data
    Prybutok, Victor R.
    Clayton, Howard R.
    Harvey, Martha M.
    Communications in Statistics Part B: Simulation and Computation, 1997, 26 (01): : 83 - 106
  • [40] Change Point Estimation Based Statistical Monitoring with Variable Time Between Events (TBE) Control Charts
    Dogu, Eralp
    QUALITY TECHNOLOGY AND QUANTITATIVE MANAGEMENT, 2014, 11 (04): : 383 - 400