A compound control chart for monitoring and controlling high quality processes

被引:31
|
作者
Bersimis, Sotiris [1 ]
Koutras, Markos V. [1 ]
Maravelakis, Petros E. [2 ]
机构
[1] Univ Piraeus, Dept Stat & Insurance Sci, Piraeus 18534, Greece
[2] Univ Piraeus, Dept Business Adm, Piraeus 18534, Greece
关键词
Quality control; Applied probability; High quality processes; Run length distribution; Markov chain impedance; Conforming run length; PROCESS STANDARD-DEVIATION; LENGTH CONTROL CHARTS; HIGH-YIELD PROCESSES; CUSUM CHARTS; ATTRIBUTES; EWMA; RUN; INSPECTION; CCC;
D O I
10.1016/j.ejor.2013.08.017
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
In the present article, we propose a new control chart for monitoring high quality processes. More specifically, we suggest declaring the monitored process out of control, by exploiting a compound rule couching on the number of conforming units observed between the (i-1)th and the ith nonconforming item and the number of conforming items observed between the (i-2)th and the ith nonconforming item. Our numerical experimentation demonstrates that the proposed control chart, in most of the cases, exhibits a better (or at least equivalent) performance than its competitors. (C) 2013 Elsevier B.V. All rights reserved.
引用
收藏
页码:595 / 603
页数:9
相关论文
共 50 条
  • [1] Control chart of functional regression for monitoring and controlling quality of carbon electrodes
    de Mello, Marcello Neiva
    Leal Soares Ramos, Edson Marcos
    Almeida, Silvia dos Santos
    Araujo, Adrilayne dos Reis
    SIGMAE, 2016, 5 (02): : 33 - 41
  • [2] A new control chart based on proportional hazards and frailty regression models for monitoring high-quality processes with censored observations
    Keyvani, Elham
    Asadzadeh, Shervin
    Samimi, Yaser
    QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, 2025, 41 (01) : 401 - 424
  • [3] Empirical Bayes Prediction for an Attribute Control Chart in Quality Monitoring
    Supharakonsakun, Yadpirun
    IEEE ACCESS, 2024, 12 : 160784 - 160793
  • [4] The Shewhart F control chart for monitoring processes with finite number of inspections
    Celano, Giovanni
    Castagliola, Philippe
    QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, 2018, 34 (08) : 1685 - 1698
  • [5] A Generalized Likelihood Ratio Chart for Monitoring Bernoulli Processes
    Huang, Wandi
    Wang, Sai
    Reynolds, Marion R., Jr.
    QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, 2013, 29 (05) : 665 - 679
  • [6] Shewhart chart for monitoring high yield processes.
    Chin, CT
    Fah, FG
    INSURANCE MATHEMATICS & ECONOMICS, 2003, 32 (03) : 474 - 474
  • [7] Inflated beta control chart for monitoring double bounded processes
    de Araujo Lima-Filho, Luiz Medeiros
    Pereira, Tarciana Liberal
    de Souza, Tatiene Correia
    Bayer, Fabio Mariano
    COMPUTERS & INDUSTRIAL ENGINEERING, 2019, 136 : 265 - 276
  • [8] A directional multivariate control chart for monitoring univariate autocorrelated processes
    Yang, Wenwan
    Zi, Xuemin
    Zou, Changliang
    ADVANCED MATERIALS AND PROCESS TECHNOLOGY, PTS 1-3, 2012, 217-219 : 2607 - 2613
  • [9] New Cumulative Sum Control Chart for Monitoring Poisson Processes
    Abujiya, MU'Azu Ramat
    IEEE ACCESS, 2017, 5 : 14298 - 14308
  • [10] EWMA Control Charts for Monitoring High Yield Processes
    Mavroudis, Eleftheriou
    Nicolas, Farmakis
    COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, 2013, 42 (20) : 3639 - 3654