Statistical control by monitoring and feedback adjustment [[electronic resource] /] / George E.P. Box, Alberto Luceño, Maria del Carmen Paniagua-Quiñones

• Record Nr.: UNINA9910831048103321
• Autore: Box George E. P
• Pubbl/distr/stampa: Hoboken, N.J., : John Wiley & Sons, 2009
• ISBN: 1-283-27393-4; 9786613273932; 1-118-16453-9; 1-118-16446-6
• Edizione: [2nd ed.]
• Descrizione fisica: 1 online resource (358 p.)
• Collana: Wiley series in probability and statistics
• Altri autori (Persone): LuceñoAlberto; Paniagua-QuiñonesMaría del Carmen
• Disciplina: 629.8/3; 629.83
• Soggetti: Feedback control systems; Process control - Statistical methods
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Statistical 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 μ and σ; 1.9 Probabilities Associated with Normal Distribution; 1.10 Estimating Mean and Standard Deviation from Data; 1.11 Combining Estimates of σ2; 1.12 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; 2.6 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; 3.6 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 θ; 4.8 Introduction to Process Dynamics and Transfer Function; 4.9 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; 5.7 Understanding Time Series Behavior with Variogram
• Sommario/riassunto: Praise 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