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Statistical control by monitoring and feedback adjustment [[electronic resource] /] / George E.P. Box, Alberto Luceño, Maria del Carmen Paniagua-Quiñones
| Statistical control by monitoring and feedback adjustment [[electronic resource] /] / George E.P. Box, Alberto Luceño, Maria del Carmen Paniagua-Quiñones |
| Autore | Box George E. P |
| Edizione | [2nd ed.] |
| Pubbl/distr/stampa | Hoboken, N.J., : John Wiley & Sons, 2009 |
| Descrizione fisica | 1 online resource (358 p.) |
| Disciplina |
629.8/3
629.83 |
| Altri autori (Persone) |
LuceñoAlberto
Paniagua-QuiñonesMaría del Carmen |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Feedback control systems
Process control - Statistical methods |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-283-27393-4
9786613273932 1-118-16453-9 1-118-16446-6 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| 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 |
| Record Nr. | UNINA-9910139597903321 |
Box George E. P
|
||
| Hoboken, N.J., : John Wiley & Sons, 2009 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Statistical control by monitoring and feedback adjustment [[electronic resource] /] / George E.P. Box, Alberto Luceño, Maria del Carmen Paniagua-Quiñones
| Statistical control by monitoring and feedback adjustment [[electronic resource] /] / George E.P. Box, Alberto Luceño, Maria del Carmen Paniagua-Quiñones |
| Autore | Box George E. P |
| Edizione | [2nd ed.] |
| Pubbl/distr/stampa | Hoboken, N.J., : John Wiley & Sons, 2009 |
| Descrizione fisica | 1 online resource (358 p.) |
| Disciplina |
629.8/3
629.83 |
| Altri autori (Persone) |
LuceñoAlberto
Paniagua-QuiñonesMaría del Carmen |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Feedback control systems
Process control - Statistical methods |
| ISBN |
1-283-27393-4
9786613273932 1-118-16453-9 1-118-16446-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| 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 |
| Record Nr. | UNINA-9910831048103321 |
|
Box George E. P
|
||
| Hoboken, N.J., : John Wiley & Sons, 2009 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||