The Resource Introduction to statistical quality control, Douglas C. Montgomery

Introduction to statistical quality control, Douglas C. Montgomery

Label
Introduction to statistical quality control
Title
Introduction to statistical quality control
Statement of responsibility
Douglas C. Montgomery
Creator
Subject
Language
eng
Summary
This Edition continues to explore the modern practice of statistical quality control, providing comprehensive coverage of the subject from basic principles to state-of-the-art concepts and applications. The objective is to give the reader a thorough grounding in the principles of statistical quality control and a basis for applying those principles in a wide variety of both product and nonproduct situations. Divided into four parts, it contains numerous changes, including a more detailed discussion of the basic SPC problem-solving tools and two new case studies, expanded treatment on variable control charts with new examples, a chapter devoted entirely to cumulative-sum control charts and exponentially-weighted, moving-average control charts, and a new section on process improvement with designed experiments
Cataloging source
DLC
http://library.link/vocab/creatorName
Montgomery, Douglas C
Dewey number
658.5/62
Illustrations
illustrations
Index
index present
LC call number
TS 156 .M64 2013
Literary form
non fiction
Nature of contents
bibliography
http://library.link/vocab/subjectName
  • Quality control
  • Process control
  • Process control
  • Quality control
Label
Introduction to statistical quality control, Douglas C. Montgomery
Instantiates
Publication
Bibliography note
Includes bibliographical references (pages 723-737) and index
Carrier category
volume
Carrier category code
  • nc
Carrier MARC source
rdacarrier
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
  • PART 1 INTRODUCTION -- 1 Quality Improvement in the Modern Business Environment -- Chapter Overview and Learning Objectives -- 1.1 The Meaning of Quality and Quality Improvement -- 1.1.1 Dimensions of Quality -- 1.1.2 Quality Engineering Terminology -- 1.2 A Brief History of Quality Control and Improvement -- 1.3 Statistical Methods for Quality Control and Improvement -- 1.4 Management Aspects of Quality Improvement -- 1.4.1 Quality Philosophy and Management Strategies -- 1.4.2 The Link Between Quality and Productivity -- 1.4.3 Supply Chain Quality Management -- 1.4.4 Quality Costs -- 1.4.5 Legal Aspects of Quality -- 1.4.6 Implementing Quality Improvement -- 2 The DMAIC Process -- Chapter Overview and Learning Objectives -- 2.1 Overview of DMAIC -- 2.2 The Define Step -- 2.3 The Measure Step -- 2.4 The Analyze Step -- 2.5 The Improve Step -- 2.6 The Control Step -- 2.7 Examples of DMAIC -- 2.7.1 Litigation Documents -- 2.7.2 Improving On-Time Delivery -- 2.7.3 Improving Service Quality in a Bank
  • PART 2 STATISTICAL METHODS USEFUL IN QUALITY CONTROL AND IMPROVEMENT -- 3 Modeling Process Quality -- Chapter Overview and Learning Objectives -- 3.1 Describing Variation -- 3.1.1 The Stem-and-Leaf Plot -- 3.1.2 The Histogram -- 3.1.3 Numerical Summary of Data -- 3.1.4 The Box Plot -- 3.1.5 Probability Distributions -- 3.2 Important Discrete Distributions -- 3.2.1 The Hypergeometric Distribution -- 3.2.2 The Binomial Distribution -- 3.2.3 The Poisson Distribution -- 3.2.4 The Negative Binomial and Geometric Distributions -- 3.3 Important Continuous Distributions -- 3.3.1 The Normal Distribution -- 3.3.2 The Lognormal Distribution -- 3.3.3 The Exponential Distribution -- 3.3.4 The Gamma Distribution -- 3.3.5 The Weibull Distribution -- 3.4 Probability Plots -- 3.4.1 Normal Probability Plots -- 3.4.2 Other Probability Plots -- 3.5 Some Useful Approximations -- 3.5.1 The Binomial Approximation to the Hypergeometric -- 3.5.2 The Poisson Approximation to the Binomial -- 3.5.3 The Normal Approximation to the Binomial -- 3.5.4 Comments on Approximations -- 4 Inferences about Process Quality -- Chapter Overview and Learning Objectives -- 4.1 Statistics and Sampling Distributions -- 4.1.1 Sampling from a Normal Distribution -- 4.1.2 Sampling from a Bernoulli Distribution -- 4.1.3 Sampling from a Poisson Distribution -- 4.2 Point Estimation of Process Parameters
  • 4.3 Statistical Inference for a Single Sample -- 4.3.1 Inference on the Mean of a Population, Variance Known -- 4.3.2 The Use of P-Values for Hypothesis Testing -- 4.3.3 Inference on the Mean of a Normal Distribution, Variance Unknown -- 4.3.4 Inference on the Variance of a Normal Distribution -- 4.3.5 Inference on a Population Proportion -- 4.3.6 The Probability of Type II Error and Sample Size Decisions -- 4.4 Statistical Inference for Two Samples -- 4.4.1 Inference for a Difference in Means, Variances Known -- 4.4.2 Inference for a Difference in Means of Two Normal Distributions, Variances Unknown -- 4.4.3 Inference on the Variances of Two Normal Distributions -- 4.4.4 Inference on Two Population Proportions -- 4.5 What If There Are More Than Two Populations? The Analysis of Variance -- 4.5.1 An Example -- 4.5.2 The Analysis of Variance -- 4.5.3 Checking Assumptions: Residual Analysis -- 4.6 Linear Regression Models -- 4.6.1 Estimation of the Parameters in Linear Regression Models -- 4.6.2 Hypothesis Testing in Multiple Regression -- 4.6.3 Confidance Intervals in Multiple Regression -- 4.6.4 Prediction of New Observations -- 4.6.5 Regression Model Diagnostics
  • PART 3 BASIC METHODS OF STATISTICAL PROCESS CONTROL AND CAPABILITY ANALYSIS -- 5 Methods and Philosophy of Statistical Process Control -- Chapter Overview and Learning Objectives -- 5.1 Introduction -- 5.2 Chance and Assignable Causes of Quality Variation -- 5.3 Statistical Basis of the Control Chart -- 5.3.1 Basic Principles -- 5.3.2 Choice of Control Limits -- 5.3.3 Sample Size and Sampling Frequency -- 5.3.4 Rational Subgroups -- 5.3.5 Analysis of Patterns on Control Charts -- 5.3.6 Discussion of Sensitizing Rules for Control Charts -- 5.3.7 Phase I and Phase II of Control Chart Application -- 5.4 The Rest of the Magnificent Seven -- 5.5 Implementing SPC in a Quality Improvement Program -- 5.6 An Application of SPC -- 5.7 Applications of Statistical Process Control and Quality Improvement Tools in Transactional and Service Businesses -- 6 Control Charts for Variables -- Chapter Overview and Learning Objectives -- 6.1 Introduction -- 6.2 Control Charts for -x and R -- 6.2.1 Statistical Basis of the Charts -- 6.2.2 Development and Use of -x and R Charts -- 6.2.3 Charts Based on Standard Values -- 6.2.4 Interpretation of -x and R Charts -- 6.2.5 The Effect of Nonnormality on -x and R Charts -- 6.2.6 The Operating-Characteristic Function -- 6.2.7 The Average Run Length for the -x Chart -- 6.3 Control Charts for -x and s
  • PART 3 BASIC METHODS OF STATISTICAL PROCESS CONTROL AND CAPABILITY ANALYSIS -- 5 Methods and Philosophy of Statistical Process Control -- Chapter Overview and Learning Objectives -- 5.1 Introduction -- 5.2 Chance and Assignable Causes of Quality Variation -- 5.3 Statistical Basis of the Control Chart -- 5.3.1 Basic Principles -- 5.3.2 Choice of Control Limits -- 5.3.3 Sample Size and Sampling Frequency -- 5.3.4 Rational Subgroups -- 5.3.5 Analysis of Patterns on Control Charts -- 5.3.6 Discussion of Sensitizing Rules for Control Charts -- 5.3.7 Phase I and Phase II of Control Chart Application -- 5.4 The Rest of the Magnificent Seven -- 5.5 Implementing SPC in a Quality Improvement Program -- 5.6 An Application of SPC -- 5.7 Applications of Statistical Process Control and Quality Improvement Tools in Transactional and Service Businesses -- 6 Control Charts for Variables -- Chapter Overview and Learning Objectives -- 6.1 Introduction -- 6.2 Control Charts for -x and R -- 6.2.1 Statistical Basis of the Charts -- 6.2.2 Development and Use of -x and R Charts -- 6.2.3 Charts Based on Standard Values -- 6.2.4 Interpretation of -x and R Charts -- 6.2.5 The Effect of Nonnormality on -x and R Charts -- 6.2.6 The Operating-Characteristic Function -- 6.2.7 The Average Run Length for the -x Chart -- 6.3 Control Charts for -x and s -- 6.3.1 Const
  • 8.3 Process Capability Ratios -- 8.3.1 Use and Interpretation of Cp -- 8.3.2 Process Capability Ratio for an Off-Center Process -- 8.3.3 Normality and the Process Capability Ratio -- 8.3.4 More about Process Centering -- 8.3.5 Confidence Intervals and Tests on Process Capability Ratios -- 8.4 Process Capability Analysis Using a Control Chart -- 8.5 Process Capability Analysis Using Designed Experiments -- 8.6 Process Capability Analysis with Attribute Data -- 8.7 Gauge and Measurement System Capability Studies -- 8.7.1 Basic Concepts of Gauge Capability -- 8.7.2 The Analysis of Variance Method -- 8.7.3 Confidence Intervals in Gauge R & R Studies -- 8.7.4 False Defectives and Passed Defectives -- 8.7.5 Attribute Gauge Capability -- 8.7.6 Comparing Customer and Supplier Measurement Systems -- 8.8 Setting Specification Limits on Discrete Components -- 8.8.1 Linear Combinations -- 8.8.2 Nonlinear Combinations -- 8.9 Estimating the Natural Tolerance Limits of a Process -- 8.9.1 Tolerance Limits Based on the Normal Distribution -- 8.9.2 Nonparametric Tolerance Limits
  • PART 4 OTHER STATISTICAL PROCESSMONITORING AND CONTROL TECHNIQUES -- 9 Cumulative Sum and Exponentially Weighted Moving Average Control Charts -- Chapter Overview and Learning Objectives -- 9.1 The Cumulative Sum Control Chart -- 9.1.1 Basic Principles: The CUSUM Control Chart for Monitoring the Process Mean -- 9.1.2 The Tabular or Algorithmic CUSUM for Monitoring the Process Mean -- 9.1.3 Recommendations for CUSUM Design -- 9.1.4 The Standardized CUSUM -- 9.1.5 Improving CUSUM Responsiveness for Large Shifts -- 9.1.6 The Fast Initial Response or Headstart Feature -- 9.1.7 One-Sided CUSUMs -- 9.1.8 A CUSUM for Monitoring Process Variability -- 9.1.9 Rational Subgroups -- 9.1.10 CUSUMs for Other Sample Statistics -- 9.1.11 The V-Mask Procedure -- 9.1.12 The Self-Starting CUSUM -- 9.2 The Exponentially Weighted Moving Average Control Chart -- 9.2.1 The Exponentially Weighted Moving Average Control Chart for Monitoring the Process Mean -- 9.2.2 Design of an EWMA Control Chart -- 9.2.3 Robustness of the EWMA to Nonnormality -- 9.2.4 Rational Subgroups -- 9.2.5 Extensions of the EWMA -- 9.3 The Moving Average Control Chart -- 10 Other Univariate Statistical Process-Monitoring and Control Techniques -- Chapter Overview and Learning Objectives -- 10.1 Statistical Process Control for Short Production Runs
  • PART 4 OTHER STATISTICAL PROCESSMONITORING AND CONTROL TECHNIQUES -- 9 Cumulative Sum and Exponentially Weighted Moving Average Control Charts -- Chapter Overview and Learning Objectives -- 9.1 The Cumulative Sum Control Chart -- 9.1.1 Basic Principles: The CUSUM Control Chart for Monitoring the Process Mean -- 9.1.2 The Tabular or Algorithmic CUSUM for Monitoring the Process Mean -- 9.1.3 Recommendations for CUSUM Design -- 9.1.4 The Standardized CUSUM -- 9.1.5 Improving CUSUM Responsiveness for Large Shifts -- 9.1.6 The Fast Initial Response or Headstart Feature -- 9.1.7 One-Sided CUSUMs -- 9.1.8 A CUSUM for Monitoring Process Variability -- 9.1.9 Rational Subgroups -- 9.1.10 CUSUMs for Other Sample Statistics -- 9.1.11 The V-Mask Procedure -- 9.1.12 The Self-Starting CUSUM -- 9.2 The Exponentially Weighted Moving Average Control Chart -- 9.2.1 The Exponentially Weighted Moving Average Control Chart for Monitoring the Process Mean -- 9.2.2 Design of an EWMA Control Chart -- 9.2.3 Robustness of the EWMA to Nonnormality -- 9.2.4 Rational Subgroups -- 9.2.5 Extensions of the EWMA -- 9.3 The Moving Average Control Chart -- 10 Other Univariate Statistical Process-Monitoring and Control Techniques -- Chapter Overview and Learning Objectives -- 10.1 Statistical Process Control for Short Production Runs -- 10.1.1 x and R Cha
  • 10.11.7 Monitoring Bernoulli Processes -- 10.11.8 Nonparametric Control Charts -- 11 Multivariate Process Monitoring and Control -- Chapter Overview and Learning Objectives -- 11.1 The Multivariate Quality-Control Problem -- 11.2 Description of Multivariate Data -- 11.2.1 The Multivariate Normal Distribution -- 11.2.2 The Sample Mean Vector and Covariance Matrix -- 11.3 The Hotelling T2 Control Chart -- 11.3.1 Subgrouped Data -- 11.3.2 Individual Observations -- 11.4 The Multivariate EWMA Control Chart -- 11.5 Regression Adjustment -- 11.6 Control Charts for Monitoring Variability -- 11.7 Latent Structure Methods -- 11.7.1 Principal Components -- 11.7.2 Partial Least Squares -- 12 Engineering Process Control and SPC -- Chapter Overview and Learning Objectives -- 12.1 Process Monitoring and Process Regulation -- 12.2 Process Control by Feedback Adjustment -- 12.2.1 A Simple Adjustment Scheme: Integral Control -- 12.2.2 The Adjustment Chart -- 12.2.3 Variations of the Adjustment Chart -- 12.2.4 Other Types of Feedback Controllers -- 12.3 Combining SPC and EPC
  • PART 5 PROCESS DESIGN AND IMPROVEMENT WITH DESIGNED EXPERIMENTS -- 13 Factorial and Fractional Factorial Experiments for Process Design and Improvement -- Chapter Overview and Learning Objectives -- 13.1 What is Experimental Design? -- 13.2 Examples of Designed Experiments In Process and Product Improvement -- 13.3 Guidelines for Designing Experiments -- 13.4 Factorial Experiments -- 13.4.1 An Example -- 13.4.2 Statistical Analysis -- 13.4.3 Residual Analysis -- 13.5 The 2k Factorial Design -- 13.5.1 The 22 Design -- 13.5.2 The 2k Design for k e"3 Factors -- 13.5.3 A Single Replicate of the 2k Design -- 13.5.4 Addition of Center Points to the 2k Design -- 13.5.5 Blocking and Confounding in the 2k Design -- 13.6 Fractional Replication of the 2k Design -- 13.6.1 The One-Half Fraction of the 2k Design -- 13.6.2 Smaller Fractions: The 2k-p Fractional Factorial Design -- 14 Process Optimization with Designed Experiments -- Chapter Overview and Learning Objectives -- 14.1 Response Surface Methods and Designs -- 14.1.1 The Method of Steepest Ascent -- 14.1.2 Analysis of a Second-Order Response Surface -- 14.2 Process Robustness Studies -- 14.2.1 Background -- 14.2.2 The Response Surface Approach to Process Robustness Studies -- 14.3 Evolutionary Operation
  • PART 6 ACCEPTANCE SAMPLING -- 15 Lot-By-Lot Acceptance Sampling for Attributes -- Chapter Overview and Learning Objectives -- 15.1 The Acceptance-Sampling Problem -- 15.1.1 Advantages and Disadvantages of Sampling -- 15.1.2 Types of Sampling Plans -- 15.1.3 Lot Formation -- 15.1.4 Random Sampling -- 15.1.5 Guidelines for Using Acceptance Sampling -- 15.2 Single-Sampling Plans for Attributes -- 15.2.1 Definition of a Single-Sampling Plan -- 15.2.2 The OC Curve -- 15.2.3 Designing a Single-Sampling Plan with a Specified OC Curve -- 15.2.4 Rectifying Inspection -- 15.3 Double, Multiple, and Sequential Sampling -- 15.3.1 Double-Sampling Plans -- 15.3.2 Multiple-Sampling Plans -- 15.3.3 Sequential-Sampling Plans -- 15.4 Military Standard 105E (ANSI/ASQC Z1.4, ISO 2859) -- 15.4.1 Description of the Standard -- 15.4.2 Procedure -- 15.4.3 Discussion -- 15.5 The Dodge-Romig Sampling Plans -- 15.5.1 AOQL Plans -- 15.5.2 LTPD Plans -- 15.5.3 Estimation of Process Average -- 16 Other Acceptance-Sampling Techniques -- Chapter Overview and Learning Objectives -- 16.1 Acceptance Sampling by Variables -- 16.1.1 Advantages and Disadvantages of Variables Sampling -- 16.1.2 Types of Sampling Plans Available -- 16.1.3 Caution in the Use of Variables Sampling
Dimensions
27 cm
Edition
7th ed.
Extent
xiv, 754 pages
Isbn
9781118322574
Lccn
2012471290
Media category
unmediated
Media MARC source
rdamedia
Media type code
  • n
Other control number
9781118322574
Other physical details
illustrations
System control number
  • (OCoLC)780144219
  • (OCoLC)ocn780144219
Label
Introduction to statistical quality control, Douglas C. Montgomery
Publication
Bibliography note
Includes bibliographical references (pages 723-737) and index
Carrier category
volume
Carrier category code
  • nc
Carrier MARC source
rdacarrier
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
  • PART 1 INTRODUCTION -- 1 Quality Improvement in the Modern Business Environment -- Chapter Overview and Learning Objectives -- 1.1 The Meaning of Quality and Quality Improvement -- 1.1.1 Dimensions of Quality -- 1.1.2 Quality Engineering Terminology -- 1.2 A Brief History of Quality Control and Improvement -- 1.3 Statistical Methods for Quality Control and Improvement -- 1.4 Management Aspects of Quality Improvement -- 1.4.1 Quality Philosophy and Management Strategies -- 1.4.2 The Link Between Quality and Productivity -- 1.4.3 Supply Chain Quality Management -- 1.4.4 Quality Costs -- 1.4.5 Legal Aspects of Quality -- 1.4.6 Implementing Quality Improvement -- 2 The DMAIC Process -- Chapter Overview and Learning Objectives -- 2.1 Overview of DMAIC -- 2.2 The Define Step -- 2.3 The Measure Step -- 2.4 The Analyze Step -- 2.5 The Improve Step -- 2.6 The Control Step -- 2.7 Examples of DMAIC -- 2.7.1 Litigation Documents -- 2.7.2 Improving On-Time Delivery -- 2.7.3 Improving Service Quality in a Bank
  • PART 2 STATISTICAL METHODS USEFUL IN QUALITY CONTROL AND IMPROVEMENT -- 3 Modeling Process Quality -- Chapter Overview and Learning Objectives -- 3.1 Describing Variation -- 3.1.1 The Stem-and-Leaf Plot -- 3.1.2 The Histogram -- 3.1.3 Numerical Summary of Data -- 3.1.4 The Box Plot -- 3.1.5 Probability Distributions -- 3.2 Important Discrete Distributions -- 3.2.1 The Hypergeometric Distribution -- 3.2.2 The Binomial Distribution -- 3.2.3 The Poisson Distribution -- 3.2.4 The Negative Binomial and Geometric Distributions -- 3.3 Important Continuous Distributions -- 3.3.1 The Normal Distribution -- 3.3.2 The Lognormal Distribution -- 3.3.3 The Exponential Distribution -- 3.3.4 The Gamma Distribution -- 3.3.5 The Weibull Distribution -- 3.4 Probability Plots -- 3.4.1 Normal Probability Plots -- 3.4.2 Other Probability Plots -- 3.5 Some Useful Approximations -- 3.5.1 The Binomial Approximation to the Hypergeometric -- 3.5.2 The Poisson Approximation to the Binomial -- 3.5.3 The Normal Approximation to the Binomial -- 3.5.4 Comments on Approximations -- 4 Inferences about Process Quality -- Chapter Overview and Learning Objectives -- 4.1 Statistics and Sampling Distributions -- 4.1.1 Sampling from a Normal Distribution -- 4.1.2 Sampling from a Bernoulli Distribution -- 4.1.3 Sampling from a Poisson Distribution -- 4.2 Point Estimation of Process Parameters
  • 4.3 Statistical Inference for a Single Sample -- 4.3.1 Inference on the Mean of a Population, Variance Known -- 4.3.2 The Use of P-Values for Hypothesis Testing -- 4.3.3 Inference on the Mean of a Normal Distribution, Variance Unknown -- 4.3.4 Inference on the Variance of a Normal Distribution -- 4.3.5 Inference on a Population Proportion -- 4.3.6 The Probability of Type II Error and Sample Size Decisions -- 4.4 Statistical Inference for Two Samples -- 4.4.1 Inference for a Difference in Means, Variances Known -- 4.4.2 Inference for a Difference in Means of Two Normal Distributions, Variances Unknown -- 4.4.3 Inference on the Variances of Two Normal Distributions -- 4.4.4 Inference on Two Population Proportions -- 4.5 What If There Are More Than Two Populations? The Analysis of Variance -- 4.5.1 An Example -- 4.5.2 The Analysis of Variance -- 4.5.3 Checking Assumptions: Residual Analysis -- 4.6 Linear Regression Models -- 4.6.1 Estimation of the Parameters in Linear Regression Models -- 4.6.2 Hypothesis Testing in Multiple Regression -- 4.6.3 Confidance Intervals in Multiple Regression -- 4.6.4 Prediction of New Observations -- 4.6.5 Regression Model Diagnostics
  • PART 3 BASIC METHODS OF STATISTICAL PROCESS CONTROL AND CAPABILITY ANALYSIS -- 5 Methods and Philosophy of Statistical Process Control -- Chapter Overview and Learning Objectives -- 5.1 Introduction -- 5.2 Chance and Assignable Causes of Quality Variation -- 5.3 Statistical Basis of the Control Chart -- 5.3.1 Basic Principles -- 5.3.2 Choice of Control Limits -- 5.3.3 Sample Size and Sampling Frequency -- 5.3.4 Rational Subgroups -- 5.3.5 Analysis of Patterns on Control Charts -- 5.3.6 Discussion of Sensitizing Rules for Control Charts -- 5.3.7 Phase I and Phase II of Control Chart Application -- 5.4 The Rest of the Magnificent Seven -- 5.5 Implementing SPC in a Quality Improvement Program -- 5.6 An Application of SPC -- 5.7 Applications of Statistical Process Control and Quality Improvement Tools in Transactional and Service Businesses -- 6 Control Charts for Variables -- Chapter Overview and Learning Objectives -- 6.1 Introduction -- 6.2 Control Charts for -x and R -- 6.2.1 Statistical Basis of the Charts -- 6.2.2 Development and Use of -x and R Charts -- 6.2.3 Charts Based on Standard Values -- 6.2.4 Interpretation of -x and R Charts -- 6.2.5 The Effect of Nonnormality on -x and R Charts -- 6.2.6 The Operating-Characteristic Function -- 6.2.7 The Average Run Length for the -x Chart -- 6.3 Control Charts for -x and s
  • PART 3 BASIC METHODS OF STATISTICAL PROCESS CONTROL AND CAPABILITY ANALYSIS -- 5 Methods and Philosophy of Statistical Process Control -- Chapter Overview and Learning Objectives -- 5.1 Introduction -- 5.2 Chance and Assignable Causes of Quality Variation -- 5.3 Statistical Basis of the Control Chart -- 5.3.1 Basic Principles -- 5.3.2 Choice of Control Limits -- 5.3.3 Sample Size and Sampling Frequency -- 5.3.4 Rational Subgroups -- 5.3.5 Analysis of Patterns on Control Charts -- 5.3.6 Discussion of Sensitizing Rules for Control Charts -- 5.3.7 Phase I and Phase II of Control Chart Application -- 5.4 The Rest of the Magnificent Seven -- 5.5 Implementing SPC in a Quality Improvement Program -- 5.6 An Application of SPC -- 5.7 Applications of Statistical Process Control and Quality Improvement Tools in Transactional and Service Businesses -- 6 Control Charts for Variables -- Chapter Overview and Learning Objectives -- 6.1 Introduction -- 6.2 Control Charts for -x and R -- 6.2.1 Statistical Basis of the Charts -- 6.2.2 Development and Use of -x and R Charts -- 6.2.3 Charts Based on Standard Values -- 6.2.4 Interpretation of -x and R Charts -- 6.2.5 The Effect of Nonnormality on -x and R Charts -- 6.2.6 The Operating-Characteristic Function -- 6.2.7 The Average Run Length for the -x Chart -- 6.3 Control Charts for -x and s -- 6.3.1 Const
  • 8.3 Process Capability Ratios -- 8.3.1 Use and Interpretation of Cp -- 8.3.2 Process Capability Ratio for an Off-Center Process -- 8.3.3 Normality and the Process Capability Ratio -- 8.3.4 More about Process Centering -- 8.3.5 Confidence Intervals and Tests on Process Capability Ratios -- 8.4 Process Capability Analysis Using a Control Chart -- 8.5 Process Capability Analysis Using Designed Experiments -- 8.6 Process Capability Analysis with Attribute Data -- 8.7 Gauge and Measurement System Capability Studies -- 8.7.1 Basic Concepts of Gauge Capability -- 8.7.2 The Analysis of Variance Method -- 8.7.3 Confidence Intervals in Gauge R & R Studies -- 8.7.4 False Defectives and Passed Defectives -- 8.7.5 Attribute Gauge Capability -- 8.7.6 Comparing Customer and Supplier Measurement Systems -- 8.8 Setting Specification Limits on Discrete Components -- 8.8.1 Linear Combinations -- 8.8.2 Nonlinear Combinations -- 8.9 Estimating the Natural Tolerance Limits of a Process -- 8.9.1 Tolerance Limits Based on the Normal Distribution -- 8.9.2 Nonparametric Tolerance Limits
  • PART 4 OTHER STATISTICAL PROCESSMONITORING AND CONTROL TECHNIQUES -- 9 Cumulative Sum and Exponentially Weighted Moving Average Control Charts -- Chapter Overview and Learning Objectives -- 9.1 The Cumulative Sum Control Chart -- 9.1.1 Basic Principles: The CUSUM Control Chart for Monitoring the Process Mean -- 9.1.2 The Tabular or Algorithmic CUSUM for Monitoring the Process Mean -- 9.1.3 Recommendations for CUSUM Design -- 9.1.4 The Standardized CUSUM -- 9.1.5 Improving CUSUM Responsiveness for Large Shifts -- 9.1.6 The Fast Initial Response or Headstart Feature -- 9.1.7 One-Sided CUSUMs -- 9.1.8 A CUSUM for Monitoring Process Variability -- 9.1.9 Rational Subgroups -- 9.1.10 CUSUMs for Other Sample Statistics -- 9.1.11 The V-Mask Procedure -- 9.1.12 The Self-Starting CUSUM -- 9.2 The Exponentially Weighted Moving Average Control Chart -- 9.2.1 The Exponentially Weighted Moving Average Control Chart for Monitoring the Process Mean -- 9.2.2 Design of an EWMA Control Chart -- 9.2.3 Robustness of the EWMA to Nonnormality -- 9.2.4 Rational Subgroups -- 9.2.5 Extensions of the EWMA -- 9.3 The Moving Average Control Chart -- 10 Other Univariate Statistical Process-Monitoring and Control Techniques -- Chapter Overview and Learning Objectives -- 10.1 Statistical Process Control for Short Production Runs
  • PART 4 OTHER STATISTICAL PROCESSMONITORING AND CONTROL TECHNIQUES -- 9 Cumulative Sum and Exponentially Weighted Moving Average Control Charts -- Chapter Overview and Learning Objectives -- 9.1 The Cumulative Sum Control Chart -- 9.1.1 Basic Principles: The CUSUM Control Chart for Monitoring the Process Mean -- 9.1.2 The Tabular or Algorithmic CUSUM for Monitoring the Process Mean -- 9.1.3 Recommendations for CUSUM Design -- 9.1.4 The Standardized CUSUM -- 9.1.5 Improving CUSUM Responsiveness for Large Shifts -- 9.1.6 The Fast Initial Response or Headstart Feature -- 9.1.7 One-Sided CUSUMs -- 9.1.8 A CUSUM for Monitoring Process Variability -- 9.1.9 Rational Subgroups -- 9.1.10 CUSUMs for Other Sample Statistics -- 9.1.11 The V-Mask Procedure -- 9.1.12 The Self-Starting CUSUM -- 9.2 The Exponentially Weighted Moving Average Control Chart -- 9.2.1 The Exponentially Weighted Moving Average Control Chart for Monitoring the Process Mean -- 9.2.2 Design of an EWMA Control Chart -- 9.2.3 Robustness of the EWMA to Nonnormality -- 9.2.4 Rational Subgroups -- 9.2.5 Extensions of the EWMA -- 9.3 The Moving Average Control Chart -- 10 Other Univariate Statistical Process-Monitoring and Control Techniques -- Chapter Overview and Learning Objectives -- 10.1 Statistical Process Control for Short Production Runs -- 10.1.1 x and R Cha
  • 10.11.7 Monitoring Bernoulli Processes -- 10.11.8 Nonparametric Control Charts -- 11 Multivariate Process Monitoring and Control -- Chapter Overview and Learning Objectives -- 11.1 The Multivariate Quality-Control Problem -- 11.2 Description of Multivariate Data -- 11.2.1 The Multivariate Normal Distribution -- 11.2.2 The Sample Mean Vector and Covariance Matrix -- 11.3 The Hotelling T2 Control Chart -- 11.3.1 Subgrouped Data -- 11.3.2 Individual Observations -- 11.4 The Multivariate EWMA Control Chart -- 11.5 Regression Adjustment -- 11.6 Control Charts for Monitoring Variability -- 11.7 Latent Structure Methods -- 11.7.1 Principal Components -- 11.7.2 Partial Least Squares -- 12 Engineering Process Control and SPC -- Chapter Overview and Learning Objectives -- 12.1 Process Monitoring and Process Regulation -- 12.2 Process Control by Feedback Adjustment -- 12.2.1 A Simple Adjustment Scheme: Integral Control -- 12.2.2 The Adjustment Chart -- 12.2.3 Variations of the Adjustment Chart -- 12.2.4 Other Types of Feedback Controllers -- 12.3 Combining SPC and EPC
  • PART 5 PROCESS DESIGN AND IMPROVEMENT WITH DESIGNED EXPERIMENTS -- 13 Factorial and Fractional Factorial Experiments for Process Design and Improvement -- Chapter Overview and Learning Objectives -- 13.1 What is Experimental Design? -- 13.2 Examples of Designed Experiments In Process and Product Improvement -- 13.3 Guidelines for Designing Experiments -- 13.4 Factorial Experiments -- 13.4.1 An Example -- 13.4.2 Statistical Analysis -- 13.4.3 Residual Analysis -- 13.5 The 2k Factorial Design -- 13.5.1 The 22 Design -- 13.5.2 The 2k Design for k e"3 Factors -- 13.5.3 A Single Replicate of the 2k Design -- 13.5.4 Addition of Center Points to the 2k Design -- 13.5.5 Blocking and Confounding in the 2k Design -- 13.6 Fractional Replication of the 2k Design -- 13.6.1 The One-Half Fraction of the 2k Design -- 13.6.2 Smaller Fractions: The 2k-p Fractional Factorial Design -- 14 Process Optimization with Designed Experiments -- Chapter Overview and Learning Objectives -- 14.1 Response Surface Methods and Designs -- 14.1.1 The Method of Steepest Ascent -- 14.1.2 Analysis of a Second-Order Response Surface -- 14.2 Process Robustness Studies -- 14.2.1 Background -- 14.2.2 The Response Surface Approach to Process Robustness Studies -- 14.3 Evolutionary Operation
  • PART 6 ACCEPTANCE SAMPLING -- 15 Lot-By-Lot Acceptance Sampling for Attributes -- Chapter Overview and Learning Objectives -- 15.1 The Acceptance-Sampling Problem -- 15.1.1 Advantages and Disadvantages of Sampling -- 15.1.2 Types of Sampling Plans -- 15.1.3 Lot Formation -- 15.1.4 Random Sampling -- 15.1.5 Guidelines for Using Acceptance Sampling -- 15.2 Single-Sampling Plans for Attributes -- 15.2.1 Definition of a Single-Sampling Plan -- 15.2.2 The OC Curve -- 15.2.3 Designing a Single-Sampling Plan with a Specified OC Curve -- 15.2.4 Rectifying Inspection -- 15.3 Double, Multiple, and Sequential Sampling -- 15.3.1 Double-Sampling Plans -- 15.3.2 Multiple-Sampling Plans -- 15.3.3 Sequential-Sampling Plans -- 15.4 Military Standard 105E (ANSI/ASQC Z1.4, ISO 2859) -- 15.4.1 Description of the Standard -- 15.4.2 Procedure -- 15.4.3 Discussion -- 15.5 The Dodge-Romig Sampling Plans -- 15.5.1 AOQL Plans -- 15.5.2 LTPD Plans -- 15.5.3 Estimation of Process Average -- 16 Other Acceptance-Sampling Techniques -- Chapter Overview and Learning Objectives -- 16.1 Acceptance Sampling by Variables -- 16.1.1 Advantages and Disadvantages of Variables Sampling -- 16.1.2 Types of Sampling Plans Available -- 16.1.3 Caution in the Use of Variables Sampling
Dimensions
27 cm
Edition
7th ed.
Extent
xiv, 754 pages
Isbn
9781118322574
Lccn
2012471290
Media category
unmediated
Media MARC source
rdamedia
Media type code
  • n
Other control number
9781118322574
Other physical details
illustrations
System control number
  • (OCoLC)780144219
  • (OCoLC)ocn780144219

Library Locations

  • Architecture LibraryBorrow it
    Gould Hall 830 Van Vleet Oval Rm. 105, Norman, OK, 73019, US
    35.205706 -97.445050
  • Bizzell Memorial LibraryBorrow it
    401 W. Brooks St., Norman, OK, 73019, US
    35.207487 -97.447906
  • Boorstin CollectionBorrow it
    401 W. Brooks St., Norman, OK, 73019, US
    35.207487 -97.447906
  • Chinese Literature Translation ArchiveBorrow it
    401 W. Brooks St., RM 414, Norman, OK, 73019, US
    35.207487 -97.447906
  • Engineering LibraryBorrow it
    Felgar Hall 865 Asp Avenue, Rm. 222, Norman, OK, 73019, US
    35.205706 -97.445050
  • Fine Arts LibraryBorrow it
    Catlett Music Center 500 West Boyd Street, Rm. 20, Norman, OK, 73019, US
    35.210371 -97.448244
  • Harry W. Bass Business History CollectionBorrow it
    401 W. Brooks St., Rm. 521NW, Norman, OK, 73019, US
    35.207487 -97.447906
  • History of Science CollectionsBorrow it
    401 W. Brooks St., Rm. 521NW, Norman, OK, 73019, US
    35.207487 -97.447906
  • John and Mary Nichols Rare Books and Special CollectionsBorrow it
    401 W. Brooks St., Rm. 509NW, Norman, OK, 73019, US
    35.207487 -97.447906
  • Library Service CenterBorrow it
    2601 Technology Place, Norman, OK, 73019, US
    35.185561 -97.398361
  • Price College Digital LibraryBorrow it
    Adams Hall 102 307 West Brooks St., Norman, OK, 73019, US
    35.210371 -97.448244
  • Western History CollectionsBorrow it
    Monnet Hall 630 Parrington Oval, Rm. 300, Norman, OK, 73019, US
    35.209584 -97.445414
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