## Cumulative Sum Charts and Charting for Quality ImprovementCumulative sum (CUSUM) control charting is a valuable tool for detecting and diagnosing persistent shifts in series of readings. It is used in traditional statistical process control (SPC) settings such as manufacturing, but is also effective in settings as diverse as personnel management, econometrics, and conventional data analysis. It is an essential tool for the quality professional. This book covers CUSUMs from an application-oriented viewpoint, while also providing the essential theoretical underpinning. It is accessible to anyone with a basic statistical training, and is aimed at quality practitioners, teachers and students of quality methodologies, and people interested in analysis of time-ordered data. The text is supported by a Web site containing CUSUM software and data sets. Douglas M. Hawkins is Chair of the Department of Applied Statistics, University of Minnesota. He is a Fellow of the American Statistical Association, a Member of the International Statistical Institute and a Senior member of the American Society for Quality Control. His work on multivariate CUSUMs won him the Ellis R. Ott Award for the best paper on quality published in 1993. He has been Associate Editor of Technometrics and Journal of the American Statistical Association. David H. Olwell is Associate Professor in the Department of Mathematical Sciences at the United States Military Academy. He is a member of the American Statistical Association, the American Society for Quality Control, and the Military Operations Research Society, where his work on applications of CUSUMs to managing sexual harassment was nominated for the 1998 Barchi prize. He is Editor of Mathematica |

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### Contents

III | 1 |

IV | 5 |

V | 6 |

VI | 11 |

VII | 13 |

VIII | 14 |

IX | 16 |

X | 20 |

LXXIX | 119 |

LXXX | 120 |

LXXXI | 121 |

LXXXIII | 123 |

LXXXIV | 126 |

LXXXV | 127 |

LXXXVII | 129 |

LXXXVIII | 132 |

XI | 22 |

XII | 24 |

XIII | 28 |

XIV | 29 |

XVI | 31 |

XVII | 32 |

XVIII | 33 |

XIX | 35 |

XXI | 36 |

XXII | 40 |

XXIII | 43 |

XXIV | 44 |

XXVI | 47 |

XXVII | 50 |

XXVIII | 51 |

XXIX | 53 |

XXX | 54 |

XXXI | 55 |

XXXII | 56 |

XXXIII | 57 |

XXXIV | 59 |

XXXV | 61 |

XXXVI | 62 |

XXXVII | 63 |

XXXVIII | 66 |

XXXIX | 67 |

XL | 69 |

XLI | 71 |

XLII | 72 |

XLIII | 74 |

XLV | 76 |

XLVI | 77 |

XLVII | 80 |

XLVIII | 81 |

XLIX | 82 |

L | 83 |

LI | 84 |

LIII | 85 |

LIV | 86 |

LV | 88 |

LVI | 89 |

LVII | 91 |

LVIII | 93 |

LIX | 94 |

LX | 98 |

LXI | 99 |

LXII | 101 |

LXIV | 102 |

LXV | 103 |

LXVI | 104 |

LXVII | 105 |

LXVIII | 106 |

LXIX | 107 |

LXXI | 110 |

LXXII | 111 |

LXXIII | 112 |

LXXV | 113 |

LXXVI | 114 |

LXXVIII | 117 |

LXXXIX | 133 |

XC | 135 |

XCI | 137 |

XCII | 138 |

XCIII | 139 |

XCIV | 141 |

XCV | 142 |

XCVI | 144 |

XCVII | 145 |

XCVIII | 146 |

XCIX | 147 |

C | 148 |

CI | 150 |

CIII | 151 |

CIV | 153 |

CVI | 154 |

CVII | 156 |

CIX | 157 |

CX | 159 |

CXI | 162 |

CXIII | 165 |

CXIV | 169 |

CXVI | 170 |

CXVII | 171 |

CXVIII | 173 |

CXIX | 174 |

CXX | 175 |

CXXII | 180 |

CXXIII | 185 |

CXXIV | 186 |

CXXV | 187 |

CXXVI | 189 |

CXXVII | 191 |

CXXVIII | 192 |

CXXIX | 194 |

CXXX | 196 |

CXXXI | 198 |

CXXXII | 200 |

CXXXIII | 201 |

CXXXIV | 203 |

CXXXV | 204 |

CXXXVI | 206 |

CXXXVIII | 207 |

CXXXIX | 208 |

CXL | 209 |

CXLI | 211 |

CXLII | 214 |

CXLIII | 215 |

CXLIV | 218 |

CXLV | 220 |

CXLVI | 222 |

CXLVII | 225 |

CXLIX | 226 |

CLI | 227 |

CLII | 229 |

CLIII | 230 |

CLIV | 231 |

243 | |

### Other editions - View all

Cumulative Sum Charts and Charting for Quality Improvement Douglas M. Hawkins,David H. Olwell Limited preview - 2012 |

Cumulative Sum Charts and Charting for Quality Improvement Douglas M Hawkins,David H Olwell No preview available - 1998 |

Cumulative Sum Charts and Charting for Quality Improvement Douglas M. Hawkins,David H. Olwell No preview available - 2012 |

### Common terms and phrases

ANYGETH binomial distribution bolts calculations calibration Chapter control charts control limits CUSUM charts CUSUM scheme CUSUM signals decision interval CUSUM detect diagnose diameters discussion downward CUSUM downward shift effect Equation estimate example exponential family Figure FIR ARL FIR CUSUM gamma distribution gives in-control ARL increase individual readings inverse Gaussian inverse Gaussian distribution location CUSUM Markov chain mean shifts monitoring multivariate negative binomial negative binomial distribution nonconforming items normal data normal distribution optimal CUSUM out-of-control ARL overdispersion persistent shifts Poisson distribution Poisson process problem process measure process readings random variable rational group means recursive residuals reference value regression adjustment regular ARL run length running mean sample scale CUSUM self-starting CUSUM Shewhart chart shift in mean shows special causes SPRT standard deviation standard normal statistical step change sufficient statistic Table upward CUSUM upward shift variance vector Weibull distribution winsorization

### Popular passages

Page 240 - Srivastava, MS and Worsley, KJ (1986). Likelihood Ratio Tests for a Change in the Multivariate Normal Mean.

Page 232 - Bissell, AF (1984). The performance of control charts and cusums under linear trend.