LEADER 05474nam 2200661Ia 450 001 9910877822503321 005 20200520144314.0 010 $a1-283-27393-4 010 $a9786613273932 010 $a1-118-16453-9 010 $a1-118-16446-6 035 $a(CKB)2550000000054311 035 $a(EBL)848509 035 $a(OCoLC)757394818 035 $a(SSID)ssj0000550643 035 $a(PQKBManifestationID)11355077 035 $a(PQKBTitleCode)TC0000550643 035 $a(PQKBWorkID)10509726 035 $a(PQKB)11628301 035 $a(MiAaPQ)EBC848509 035 $a(EXLCZ)992550000000054311 100 $a20080728d2009 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aStatistical control by monitoring and feedback adjustment /$fGeorge E.P. Box, Alberto Luceno, Maria del Carmen Paniagua-Quinones 205 $a2nd ed. 210 $aHoboken, N.J. $cJohn Wiley & Sons$d2009 215 $a1 online resource (358 p.) 225 1 $aWiley series in probability and statistics 300 $aDescription based upon print version of record. 311 $a0-470-14832-2 320 $aIncludes bibliographical references and index. 327 $aStatistical Control by Monitoring and Adjustment, Second Edition; Contents; Preface; 1 Introduction and Revision of Some Statistical Ideas; 1.1 Necessity for Process Control; 1.2 SPC and EPC; 1.3 Process Monitoring Without a Model; 1.4 Detecting a Signal in Noise; 1.5 Measurement Data; 1.6 Two Important Characteristics of a Probability Distribution; 1.7 Normal Distribution; 1.8 Normal Distribution Defined by ? and ?; 1.9 Probabilities Associated with Normal Distribution; 1.10 Estimating Mean and Standard Deviation from Data; 1.11 Combining Estimates of ?2 327 $a1.12 Data on Frequencies (Events): Poisson Distribution1.13 Normal Approximation to Poisson Distribution; 1.14 Data on Proportion Defective: Binomial Distribution; 1.15 Normal Approximation to Binomial Distribution; Appendix 1A: Central Limit Effect; Problems; 2 Standard Control Charts Under Ideal Conditions As a First Approximation; 2.1 Control Charts for Process Monitoring; 2.2 Control Chart for Measurement (Variables) Data; 2.3 Shewhart Charts for Sample Average and Range; 2.4 Shewhart Chart for Sample Range; 2.5 Process Monitoring With Control Charts for Frequencies 327 $a2.6 Data on Frequencies (Counts): Poisson Distribution2.7 Common Causes and Special Causes; 2.8 For What Kinds of Data Has the c Chart Been Used?; 2.9 Quality Control Charts for Proportions: p Chart; 2.10 EWMA Chart; 2.11 Process Monitoring Using Cumulative Sums; 2.12 Specification Limits, Target Accuracy, and Process Capability; 2.13 How Successful Process Monitoring can Improve Quality; Problems; 3 What Can Go Wrong and What Can We Do About It?; 3.1 Introduction; 3.2 Measurement Charts; 3.3 Need for Time Series Models; 3.4 Types of Variation; 3.5 Nonstationary Noise 327 $a3.6 Values for constants3.7 Frequencies and Proportions; 3.8 Illustration; 3.9 Robustness of EWMA; Appendix 3A: Alternative Forms of Relationships for EWMAs; Questions; 4 Introduction to Forecasting and Process Dynamics; 4.1 Forecasting with an EWMA; 4.2 Forecasting Sales of Dingles; 4.3 Pete's Rule; 4.4 Effect of Changing Discount Factor; 4.5 Estimating Best Discount Factor; 4.6 Standard Deviation of Forecast Errors and Probability Limits for Forecasts; 4.7 What to Do If You Do Not Have Enough Data to Estimate ?; 4.8 Introduction to Process Dynamics and Transfer Function 327 $a4.9 Dynamic Systems and Transfer Funtions4.10 Difference Equations to Represent Dynamic Relations; 4.11 Representing Dynamics of Industrial Process; 4.12 Transfer Function Models Using Difference Equations; 4.13 Stable and Unstable Systems; Problems; 5 Nonstationary Time Series Models for Process Disturbances; 5.1 Reprise; 5.2 Stationary Time Series Model in Which Successive Values Are Correlated; 5.3 Major Effects of Statistical Dependence: Illustration; 5.4 Random Walk; 5.5 How to Test a Forecasting Method; 5.6 Qualification of EWMA As a Forecast 327 $a5.7 Understanding Time Series Behavior with Variogram 330 $aPraise for the First Edition ""This book . . . is a significant addition to the literature on statistical practice . . . should be of considerable interest to those interested in these topics.""-International Journal of Forecasting Recent research has shown that monitoring techniques alone are inadequate for modern Statistical Process Control (SPC), and there exists a need for these techniques to be augmented by methods that indicate when occasional process adjustment is necessary. Statistical Control by Monitoring and Adjustment, Second Edition presents the relationship among these concep 410 0$aWiley series in probability and statistics. 606 $aFeedback control systems 606 $aProcess control$xStatistical methods 615 0$aFeedback control systems. 615 0$aProcess control$xStatistical methods. 676 $a629.8/3 700 $aBox$b George E. P$030397 701 $aLuceno$b Alberto$0253452 701 $aPaniagua-Quinones$b Maria del Carmen$01762981 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910877822503321 996 $aStatistical control by monitoring and feedback adjustment$94203206 997 $aUNINA