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Nonparametric Methods for Statistical Quality Control

Author: Subhabrata Chakraborti; Marien Graham
Publisher: Newark : John Wiley & Sons, Incorporated, 2019.
Edition/Format:   eBook : Document : EnglishView all editions and formats
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Chakraborti, Subhabrata.
Nonparametric Methods for Statistical Quality Control.
Newark : John Wiley & Sons, Incorporated, ©2019
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Subhabrata Chakraborti; Marien Graham
ISBN: 9781118890677 1118890671
OCLC Number: 1088328046
Notes: 3.8.2 CUSUM Chart for the Mean in Case U
Description: 1 online resource (451 pages)
Contents: Cover; Title Page; Copyright; Contents; About the Authors; Preface; About the Companion Website; Chapter 1 Background/Review of Statistical Concepts; Chapter Overview; 1.1 Basic Probability; 1.2 Random Variables and Their Distributions; 1.3 Random Sample; 1.4 Statistical Inference; 1.5 Role of the Computer; Chapter 2 Basics of Statistical Process Control; Chapter Overview; 2.1 Basic Concepts; 2.1.1 Types of Variability; 2.1.2 The Control Chart; 2.1.3 Construction of Control Charts; 2.1.4 Variables and Attributes Control Charts; 2.1.5 Sample Size or Subgroup Size; 2.1.6 Rational Subgrouping 2.1.7 Nonparametric or Distribution-free2.1.8 Monitoring Process Location and/or Process Scale; 2.1.9 Case K and Case U; 2.1.10 Control Charts and Hypothesis Testing; 2.1.11 General Steps in Designing a Control Chart; 2.1.12 Measures of Control Chart Performance; 2.1.12.1 False Alarm Probability (FAP); 2.1.12.2 False Alarm Rate (FAR); 2.1.12.3 The Average Run-length (ARL); 2.1.12.4 Standard Deviation of Run-length (SDRL); 2.1.12.5 Percentiles of Run-length; 2.1.12.6 Average Number of Samples to Signal (ANSS); 2.1.12.7 Average Number of Observations to Signal (ANOS) 2.1.12.8 Average Time to Signal (ATS)2.1.12.9 Number of Individual Items Inspected (I); 2.1.13 Operating Characteristic Curves (OC-curves); 2.1.14 Design of Control Charts; 2.1.14.1 Sample Size, Sampling Frequency, and Variable Sample Sizes; 2.1.14.2 Variable Control Limits; 2.1.14.3 Standardized Control Limits; 2.1.15 Size of a Shift; 2.1.16 Choice of Control Limits; 2.1.16.1 k-sigma Limits; 2.1.16.2 Probability Limits; Chapter 3 Parametric Univariate Variables Control Charts; 3.0 Chapter Overview; 3.1 Introduction; 3.2 Parametric Variables Control Charts in Case K 3.2.1 Shewhart Control Charts3.2.2 CUSUM Control Charts; 3.2.3 EWMA Control Charts; 3.3 Types of Parametric Variables Charts in Case K: Illustrative Examples; 3.3.1 Shewhart Control Charts; 3.3.1.1 Shewhart Control Charts for Monitoring Process Mean; 3.3.1.2 Shewhart Control Charts for Monitoring Process Variation; 3.3.2 CUSUM Control Charts; 3.3.3 EWMA Control Charts; 3.4 Shewhart, EWMA, and CUSUM Charts: Which to Use When; 3.5 Control Chart Enhancements; 3.5.1 Sensitivity Rules; 3.5.2 Runs-type Signaling Rules; 3.6 Run-length Distribution in the Specified Parameter Case (Case K) 3.6.1 Methods of Calculating the Run-length Distribution3.6.1.1 The Exact Approach (for Shewhart and some Shewhart-type Charts); 3.6.1.2 The Markov Chain Approach; 3.6.1.3 The Integral Equation Approach; 3.6.1.4 The Computer Simulations (the Monte Carlo) Approach; 3.7 Parameter Estimation Problem and Its Effects on the Control Chart Performance; 3.8 Parametric Variables Control Charts in Case U; 3.8.1 Shewhart Control Charts in Case U; 3.8.1.1 Shewhart Control Charts for the Mean in Case U; 3.8.1.2 Shewhart Control Charts for the Standard Deviation in Case U

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