Multivariate attribute control chart using Mahalanobis D2 statistic

被引:19
|
作者
Mukhopadhyay, Arup Ranjan [1 ]
机构
[1] Indian Stat Inst, SQC & OR Unit, Kolkata, India
关键词
Euclidean distance; Mahalanobis distance; multinomial distribution; correlation matrix; variance covariance matrix;
D O I
10.1080/02664760701834980
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Process control involves repeated hypothesis testing based on several samples. However, process control is not exactly hypothesis testing as such since it deals with detection of non-random patterns of variation as well in a fleeting kind of population. Compare this with hypothesis testing which is principally meant for a stagnant population. Dr Walter A. Shewhart introduced a graphic method for doing this testing in a fleeting population in 1924. This graphic method came to be known as control chart and is widely used throughout the world today for process management purposes. Subsequently there was much advancement in process control techniques. In particular, when more than one variable was involved, process control techniques were developed mainly by Hicks (1955), Jackson (1956 and 1959) and Montgomery and Wadsworth (1972) based on the pioneering work of Hotelling in 1931. Most of them have worked in the area of multivariate variable control chart with the underlying distribution as multivariate normal. When more than one attribute variables are involved some works relating to test of hypothesis was done by Mahalanobis (1946). These works were also based on the Hotelling T-2 test. This paper expands the concept of 'Mahalanobis Distance' in case of a multinomial distribution and thereby proposes a multivariate attribute control chart.
引用
收藏
页码:421 / 429
页数:9
相关论文
共 50 条
  • [1] Quality Index and Mahalanobis D2 Statistic
    Dasgupta, Ratan
    [J]. ADVANCES IN MULTIVARIATE STATISTICAL METHODS, 2009, 4 : 367 - 382
  • [2] Multivariate control charts for calibration of hydrophones using the Mahalanobis statistic
    Crocker, S. E.
    Slater, W. H.
    Bergeron, M. A.
    [J]. METROLOGIA, 2023, 60 (05)
  • [3] Control chart for multivariate attribute processes
    Lu, XS
    Xie, M
    Goh, TN
    Lai, CD
    [J]. INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 1998, 36 (12) : 3477 - 3489
  • [4] Attribute control chart for multivariate Poisson distribution
    Chiu, Jing-Er
    Kuo, Tsen-I
    [J]. COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, 2008, 37 (01) : 146 - 158
  • [5] A Shewhart chart with alternated charting statistic to control multivariate Poisson processes
    Leoni, Roberto Campos
    Branco Costa, Antonio Fernando
    [J]. COMPUTERS & INDUSTRIAL ENGINEERING, 2020, 145
  • [6] PROGRESSIVE SELECTION OF VARIABLES USING MAHALANOBIS D2 STATISTIC . APPLICATION TO DETERMINATION OF BEST DISCRIMINANT FUNCTION SEPARATING 2 SEED POPULATIONS OF VINE
    WAGNER, R
    [J]. ANNALES DE L AMELIORATION DES PLANTES, 1965, 15 (02): : 159 - &
  • [7] ON COMPUTATION OF MAHALANOBIS GENERALIZED DISTANCE (D2)
    RIGHTMIR.GP
    [J]. AMERICAN JOURNAL OF PHYSICAL ANTHROPOLOGY, 1969, 30 (01) : 157 - &
  • [8] An attribute control chart for multivariate Poisson distribution using multiple dependent state repetitive sampling
    Aldosari, Mansour Sattam
    Aslam, Muhammad
    Rao, Gadde Srinivasa
    Jun, Chi-Hyuck
    [J]. QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, 2019, 35 (02) : 627 - 643
  • [9] Control Of Wastewater Using Multivariate Control Chart
    Nugraha, Jaka
    Fatimah, Is
    Prabowo, Rino Galang
    [J]. INTERNATIONAL CONFERENCE ON CHEMISTRY, CHEMICAL PROCESS AND ENGINEERING (IC3PE) 2017, 2017, 1823
  • [10] A Nonparametric Synthetic Control Chart Using Sign Statistic
    Khilare, S. K.
    Shirke, D. T.
    [J]. COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, 2010, 39 (18) : 3282 - 3293