Statistical Quality Control. A Modern Introduction. 7th Edition International Student Version

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1 Brochure More information from Statistical Quality Control. A Modern Introduction. 7th Edition International Student Version Description: The Seventh Edition of Statistical Quality Control provides a comprehensive treatment of the major aspects of using statistical methodology for quality control and improvement. Both traditional and modern methods are presented, including state of the art techniques for statistical process monitoring and control and statistically designed experiments for process characterization, optimization, and process robustness studies. The seventh edition continues to focus on DMAIC (define, measure, analyze, improve, and control the problem solving strategy of six sigma) including a chapter on the implementation process. Additionally, the text includes new examples, exercises, problems, and techniques. Statistical Quality Control is best suited for students in engineering, statistics, business and management science or students in undergraduate courses. Contents: PART 1 INTRODUCTION 1 1 MODERN QUALITY MANAGEMENT AND IMPROVEMENT 3 Chapter Overview and Learning Objectives The Meaning of Quality and Quality Improvement Dimensions of Quality Quality Engineering Terminology A Brief History of Quality Control and Improvement Statistical Methods for Quality Control and Improvement Management Aspects of Quality Improvement Quality Philosophy and Management Strategies The Link Between Quality and Productivity Supply Chain Quality Management Quality Costs Legal Aspects of Quality Implementing Quality Improvement 45 2 THE DMAIC PROBLEM SOLVING PROCESS 48 Chapter Overview and Learning Objectives Overview of DMAIC The Define Step The Measure Step The Analyze Step The Improve Step 56

2 2.6 The Control Step Examples of DMAIC Litigation Documents Improving On Time Delivery Improving Service Quality in a Bank 62 PART 2 STATISTICAL METHODS USEFUL IN QUALITY CONTROL AND IMPROVEMENT 65 3 STATISTICAL MODELS OR QUALITY CONTROL AND IMPROVEMENT 67 Chapter Overview and Learning Objectives Describing Variation The Stem and Leaf Plot The Histogram Numerical Summary of Data The Box Plot Probability Distributions Important Discrete Distributions The Hypergeometric Distribution The Binomial Distribution The Poisson Distribution The Negative Binomial and Geometric Distributions Important Continuous Distributions The Normal Distribution The Lognormal Distribution The Exponential Distribution The Gamma Distribution The Weibull Distribution Probability Plots Normal Probability Plots Other Probability Plots Some Useful Approximations The Binomial Approximation to the Hypergeometric The Poisson Approximation to the Binomial 100

3 3.5.3 The Normal Approximation to the Binomial Comments on Approximations STATISTICAL INFERENCE IN QUALITY CONTROL AND IMPROVEMENT 108 Chapter Overview and Learning Objectives Statistics and Sampling Distributions Sampling from a Normal Distribution Sampling from a Bernoulli Distribution Sampling from a Poisson Distribution Point Estimation of Process Parameters Statistical Inference for a Single Sample Inference on the Mean of a Population, Variance Known The Use of P Values for Hypothesis Testing Inference on the Mean of a Normal Distribution, Variance Unknown Inference on the Variance of a Normal Distribution Inference on a Population Proportion The Probability of Type II Error and Sample Size Decisions Statistical Inference for Two Samples Inference for a Difference in Means, Variances Known Inference for a Difference in Means of Two Normal Distributions, Variances Unknown Inference on the Variances of Two Normal Distributions Inference on Two Population Proportions What If There Are More Than Two Populations? The Analysis of Variance An Example The Analysis of Variance Checking Assumptions: Residual Analysis Linear Regression Models Estimation of the Parameters in Linear Regression Models Hypothesis Testing in Multiple Regression Confidance Intervals in Multiple Regression Prediction of New Observations Regression Model Diagnostics 171 PART 3 BASIC METHODS OF STATISTICAL PROCESS CONTROL AND CAPABILITY ANALYSIS 185

4 5 HOW SPC WORKS 187 Chapter Overview and Learning Objectives Introduction Chance and Assignable Causes of Quality Variation Statistical Basis of the Control Chart Basic Principles Choice of Control Limits Sample Size and Sampling Frequency Rational Subgroups Analysis of Patterns on Control Charts Discussion of Sensitizing Rules for Control Charts Phase I and Phase II of Control Chart Application The Rest of the Magnificent Seven Implementing SPC in a Quality Improvement Program An Application of SPC Applications of Statistical Process Control and Quality Improvement Tools in Transactional and Service Businesses VARIABLES CONTROL CHARTS 234 Chapter Overview and Learning Objectives Introduction Control Charts for x and R Statistical Basis of the Charts Development and Use of x and R Charts Charts Based on Standard Values Interpretation of x and R Charts The Effect of Nonnormality on x and R Charts The Operating Characteristic Function The Average Run Length for the x Chart Control Charts for x and s Construction and Operation of x and s Charts The x and s Control Charts with Variable Sample Size The s2 Control Chart 267

5 6.4 The Shewhart Control Chart for Individual Measurements Summary of Procedures for x, R, and s Charts Applications of Variables Control Charts ATTRIBUTES CONTROL CHARTS 297 Chapter Overview and Learning Objectives Introduction The Control Chart for Fraction Nonconforming Development and Operation of the Control Chart Variable Sample Size Applications in Transactional and Service Businesses The Operating Characteristic Function and Average Run Length Calculations Control Charts for Nonconformities (Defects) Procedures with Constant Sample Size Procedures with Variable Sample Size Demerit Systems The Operating Characteristic Function Dealing with Low Defect Levels Nonmanufacturing Applications Choice Between Attributes and Variables Control Charts Guidelines for Implementing Control Charts DETERMINING PROCESS AND MEASUREMENT SYSTEMS CAPABILITY 355 Chapter Overview and Learning Objectives Introduction Process Capability Analysis Using a Histogram or a Probability Plot Using the Histogram Probability Plotting Process Capability Ratios Use and Interpretation of Cp Process Capability Ratio for an Off Center Process Normality and the Process Capability Ratio More about Process Centering 368

6 8.3.5 Confidence Intervals and Tests on Process Capability Ratios Process Capability Analysis Using a Control Chart Process Capability Analysis Using Designed Experiments Process Capability Analysis with Attribute Data Gauge and Measurement System Capability Studies Basic Concepts of Gauge Capability The Analysis of Variance Method Confidence Intervals in Gauge R & R Studies False Defectives and Passed Defectives Attribute Gauge Capability Comparing Customer and Supplier Measurement Systems Setting Specification Limits on Discrete Components Linear Combinations Nonlinear Combinations Estimating the Natural Tolerance Limits of a Process Tolerance Limits Based on the Normal Distribution Nonparametric Tolerance Limits 403 PART 4 OTHER STATISTICAL PROCESSMONITORING AND CONTROL TECHNIQUES TIME WEIGHTED CONTROL CHARTS 413 Chapter Overview and Learning Objectives The Cumulative Sum Control Chart Basic Principles: The CUSUM Control Chart for Monitoring the Process Mean The Tabular or Algorithmic CUSUM for Monitoring the Process Mean Recommendations for CUSUM Design The Standardized CUSUM Improving CUSUM Responsiveness for Large Shifts The Fast Initial Response or Headstart Feature One Sided CUSUMs A CUSUM for Monitoring Process Variability Rational Subgroups CUSUMs for Other Sample Statistics The V Mask Procedure 429

7 The Self Starting CUSUM The Exponentially Weighted Moving Average Control Chart The Exponentially Weighted Moving Average Control Chart for Monitoring the Process Mean Design of an EWMA Control Chart Robustness of the EWMA to Nonnormality Rational Subgroups Extensions of the EWMA The Moving Average Control Chart ADVANCED CONTROL CHARTING TECHNIQUES 448 Chapter Overview and Learning Objectives Statistical Process Control for Short Production Runs x and R Charts for Short Production Runs Attributes Control Charts for Short Production Runs Other Methods Modified and Acceptance Control Charts Modified Control Limits for the x Chart Acceptance Control Charts Control Charts for Multiple Stream Processes Multiple Stream Processes Group Control Charts Other Approaches SPC With Autocorrelated Process Data Sources and Effects of Autocorrelation in Process Data Model Based Approaches A Model Free Approach Adaptive Sampling Procedures Economic Design of Control Charts Designing a Control Chart Process Characteristics Cost Parameters Early Work and Semieconomic Designs 481

8 An Economic Model of the x Control Chart Other Work Cuscore Charts The Changepoint Model for Process Monitoring Profile Monitoring Control Charts in Health Care Monitoring and Public Health Surveillance Overview of Other Procedures Tool Wear Control Charts Based on Other Sample Statistics Fill Control Problems Precontrol Tolerance Interval Control Charts Monitoring Processes with Censored Data Monitoring Bernoulli Processes Nonparametric Control Charts MULTIVARIATE SPC 509 Chapter Overview and Learning Objectives The Multivariate Quality Control Problem Description of Multivariate Data The Multivariate Normal Distribution The Sample Mean Vector and Covariance Matrix The Hotelling T2 Control Chart Subgrouped Data Individual Observations The Multivariate EWMA Control Chart Regression Adjustment Control Charts for Monitoring Variability Latent Structure Methods Principal Components Partial Least Squares PROCESS ADJUSTMENT AND PROCESS MONITORING 542 Chapter Overview and Learning Objectives 542

9 12.1 Process Monitoring and Process Regulation Process Control by Feedback Adjustment A Simple Adjustment Scheme: Integral Control The Adjustment Chart Variations of the Adjustment Chart Other Types of Feedback Controllers Combining SPC and EPC 555 PART 5 PROCESS DESIGN AND IMPROVEMENT WITH DESIGNED EXPERIMENTS BASIC EXPERIMENTAL DESIGN FOR PROCESS IMPROVEMENT 563 Chapter Overview and Learning Objectives What is Experimental Design? Examples of Designed Experiments In Process and Product Improvement Guidelines for Designing Experiments Factorial Experiments An Example Statistical Analysis Residual Analysis The 2k Factorial Design The 22 Design The 2k Design for k 3 Factors A Single Replicate of the 2k Design Addition of Center Points to the 2k Design Blocking and Confounding in the 2k Design Fractional Replication of the 2k Design The One Half Fraction of the 2k Design Smaller Fractions: The 2k p Fractional Factorial Design PROCESS OPTIMIZATION 617 Chapter Overview and Learning Objectives Response Surface Methods and Designs The Method of Steepest Ascent Analysis of a Second Order Response Surface 622

10 14.2 Process Robustness Studies Background The Response Surface Approach to Process Robustness Studies Evolutionary Operation 634 PART 6 ACCEPTANCE SAMPLING BASIC ACCEPTANCE SAMPLING PROCEDURES 649 Chapter Overview and Learning Objectives The Acceptance Sampling Problem Advantages and Disadvantages of Sampling Types of Sampling Plans Lot Formation Random Sampling Guidelines for Using Acceptance Sampling Single Sampling Plans for Attributes Definition of a Single Sampling Plan The OC Curve Designing a Single Sampling Plan with a Specified OC Curve Rectifying Inspection Double, Multiple, and Sequential Sampling Double Sampling Plans Multiple Sampling Plans Sequential Sampling Plans Military Standard 105E (ANSI/ASQC Z1.4, ISO 2859) Description of the Standard Procedure Discussion The Dodge Romig Sampling Plans AOQL Plans LTPD Plans Estimation of Process Average ADDITIONAL SAMPLING PROCEDURES 688 Chapter Overview and Learning Objectives 688

11 16.1 Acceptance Sampling by Variables Advantages and Disadvantages of Variables Sampling Types of Sampling Plans Available Caution in the Use of Variables Sampling Designing a Variables Sampling Plan with a Specified OC Curve MIL STD 414 (ANSI/ASQC Z1.9) General Description of the Standard Use of the Tables Discussion of MIL STD 414 and ANSI/ASQC Z Other Variables Sampling Procedures Sampling by Variables to Give Assurance Regarding the Lot or Process Mean Sequential Sampling by Variables Chain Sampling Continuous Sampling CSP Other Continuous Sampling Plans Skip Lot Sampling Plans 704 APPENDIX 709 I. Summary of Common Probability Distributions Often Used in Statistical Quality Control 710 II. Cumulative Standard Normal Distribution 711 III. Percentage Points of the 2 Distribution 713 IV. Percentage Points of the t Distribution 714 V. Percentage Points of the F Distribution 715 VI. Factors for Constructing Variables Control Charts 720 VII. Factors for Two Sided Normal Tolerance Limits 721 VIII. Factors for One Sided Normal Tolerance Limits 722 BIBLIOGRAPHY 723 ANSWERS TO SELECTED EXERCISES 739 INDEX 749 Ordering: Order Online -

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