Fundamentals of Quality Control and Improvement

COVER
TITLE PAGE
COPYRIGHT PAGE
CONTENTS
PREFACE
ABOUT THE COMPANION WEBSITE
PART I PHILOSOPHY AND FUNDAMENTALS
	Chapter 1 Introduction to Quality Control and the Total Quality System
		1-1 Introduction and Chapter Objectives
		1-2 Evolution of Quality Control
		1-3 Quality
			Quality Characteristics
			Variables and Attributes
			Defects
			Standard or Specification
			Quality of Design
			Quality of Conformance
			Quality of Performance
		1-4 Quality Control
			Off-Line Quality Control
			Statistical Process Control
			Acceptance Sampling Plans
		1-5 Quality Assurance
		1-6 Quality Circles and Quality Improvement Teams
		1-7 Customer Needs and Market Share
			Kano Model
		1-8 Benefits of Quality Control and the Total Quality System
			Total Quality System
		1-9 Quality and Reliability
		1-10 Quality Improvement
		1-11 Product and Service Costing
			Activity-Based Costing
		1-12 Quality Costs
			Prevention Costs
			Appraisal Costs
			Internal Failure Costs
			External Failure Costs
			Hidden Failure Costs
			Quality Costs Data Requirements
			Process Cost Approach
		1-13 Measuring Quality Costs
			Impact of Quality Improvement on Quality Costs
		1-14 Management of Quality
		1-15 Quality and Productivity
			Effect on Cost
			Effect on Market
		1-16 Total Quality Environmental Management
			Green Supply Chain
		Summary
		Key Terms
		Exercises
		References
	Chapter 2 Some Philosophies and Their Impact on Quality
		2-1 Introduction and Chapter Objectives
		2-2 Service Industries and Their Characteristics
			Differences in the Manufacturing and Service Sectors
			Service Quality Characteristics
			Measuring Service Quality
			Techniques for Evaluating Service Quality
		2-3 Model for Service Quality
		2-4 W. Edwards Deming’s Philosophy
			Extended Process
			Deming’s 14 Points for Management
			Deming’s Deadly Diseases
		2-5 Philip B. Crosby’s Philosophy
			Four Absolutes of Quality Management
			14-Step Plan for Quality Improvement
		2-6 Joseph M. Juran’s Philosophy
			Quality Trilogy Process
			Quality Planning
			Quality Control
			Quality Improvement
		2-7 The Three Philosophies Compared
			Definition of Quality
			Management Commitment
			Strategic Approach to a Quality System
			Measurement of Quality
			Never-Ending Process of Improvement
			Education and Training
			Eliminating the Causes of Problems
			Goal Setting
			Structural Plan
		Summary
		Key Terms
		Exercises
		References
	Chapter 3 Quality Management: Practices, Tools, and Standards
		3-1 Introduction and Chapter Objectives
		3-2 Management Practices
			Total Quality Management
			Vision and Quality Policy
			Balanced Scorecard
			Performance Standards
		3-3 Quality Function Deployment
			QFD Process
		3-4 Benchmarking and Performance Evaluation
			Benchmarking
			Quality Auditing
			Vendor Selection and Certification Programs
			Vendor Rating and Selection
		3-5 Health Care Analytics
			Health Care Analytics and Big Data
			Uniqueness of Health Care
			Challenges in Health Care Quality
		3-6 Tools for Continuous Quality Improvement
			Pareto Diagrams
			Flowcharts
			Cause-and-Effect Diagrams
			Scatterplots
			Multivariable Charts
			Matrix and Three-Dimensional Plots
			Failure Mode and Effects Criticality Analysis
		3-7 International Standards ISO 9000 and Other Derivatives
			Features of ISO 9000
			Other Industry Standards
		Case Study
		Summary
		Key Terms
		Exercises
		References
PART II STATISTICAL FOUNDATIONS AND METHODS OF QUALITY IMPROVEMENT
	Chapter 4 Fundamentals of Statistical Concepts and Techniques in Quality Control and Improvement
		4-1 Introduction and Chapter Objectives
		4-2 Population and Sample
		4-3 Parameter and Statistic
		4-4 Probability
			Relative Frequency Definition of Probability
			Simple and Compound Events
			Complementary Events
			Additive Law
			Multiplicative Law
			Independence and Mutually Exclusive Events
		4-5 Descriptive Statistics: Describing Product or Process Characteristics
			Data Collection
			Measurement Scales
			Measures of Central Tendency
			Measures of Dispersion
			Measures of Skewness and Kurtosis
			Measures of Association
		4-6 Probability Distributions
			Cumulative Distribution Function
			Expected Value
			Discrete Distributions
			Continuous Distributions
		4-7 Inferential Statistics: Drawing Conclusions on Product and Process Quality
			Sampling Distributions
			Estimation of Product and Process Parameters
			Hypothesis Testing
		Summary
		Appendix: Approximations to Some Probability Distributions
		Binomial Approximation to the Hypergeometric
		Poisson Approximation to the Binomial
		Normal Approximation to the Binomial
		Normal Approximation to the Poisson
		Key Terms
		Exercises
		References
	Chapter 5 Data Analyses and Sampling
		5-1 Introduction and Chapter Objectives
		5-2 Empirical Distribution Plots
			Histograms
			Stem-and-Leaf Plots
			Box Plots
			Variations of the Basic Box Plot
		5-3 Randomness of a Sequence
			Run Chart
		5-4 Validating Distributional Assumptions
			Probability Plotting
		5-5 Transformations to Achieve Normality
			Some Common Transformations
			Power Transformations
			Johnson Transformation
		5-6 Analysis of Count Data
			Hypothesis Test on Cell Probabilities
			Contingency Tables
			Measures of Association
		5-7 Analysis of Customer Satisfaction Data
			Customer Needs and Their Level of Satisfaction
			Displaying Survey Results
			Analysis of Survey Results
		5-8 Concepts in Sampling
			Sampling Designs and Schemes
			Sample Size Determination
			Bound on the Error of Estimation and Associated Confidence Level
			Estimating the Difference of Two Population Means
			Estimating the Difference of Two Population Proportions
			Controlling the Type I Error, Type II Error, and Associated Parameter Shift
		5-9 Bayes Rule and Decision Making Based on Samples
		5-10 Deming’s kp rule
			Critique of the kp Rule
		Summary
		Key Terms
		Exercises
		References
PART III STATISTICAL PROCESS CONTROL
	Chapter 6 Statistical Process Control Using Control Charts
		6-1 Introduction and Chapter Objectives
		6-2 Causes of Variation
			Special Causes
			Common Causes
		6-3 Statistical Basis for Control Charts
			Selection of Control Limits
			Errors in Making Inferences from Control Charts
			Effect of Control Limits on Errors in Inference Making
			Warning Limits
			Effect of Sample Size on Control Limits
			Average Run Length
		6-4 Selection of Rational Samples
			Sample Size
			Frequency of Sampling
		6-5 Analysis of Patterns in Control Charts
			Some Rules for Identifying an Out-of-Control Process
			Interpretation of Plots
			Determination of Causes of Out-of-Control Points
		6-6 Maintenance of Control Charts
		Summary
		Key Terms
		Exercises
		References
	Chapter 7 Control Charts for Variables
		7-1 Introduction and Chapter Objectives
		7-2 Selection of Characteristics for Investigation
		7-3 Preliminary Decisions
			Selection of Rational Samples
			Sample Size
			Frequency of Sampling
			Choice of Measuring Instruments
			Design of Data Recording Forms
		7-4 Control Charts for the Mean and Range
			Development of the Charts
			Variable Sample Size
			Standardized Control Charts
			Control Limits for a Given Target or Standard
			Interpretation and Inferences from the Charts
			Control Chart Patterns and Corrective Actions
		7-5 Control Charts for the Mean and Standard Deviation
			No Given Standards
			Given Standard
		7-6 Control Charts for Individual Units
			No Given Standards
			Given Standard
		7-7 Control Charts for Short Production Runs
			X- and R-Charts for Short Production Runs
			Z-MR Chart
		7-8 Other Control Charts
			Cumulative Sum Control Chart for the Process Mean
			Tabular Method
			V-Mask Method
			Cumulative Sum for Monitoring Process Variability
			Moving-Average Control Chart
			Exponentially Weighted Moving-Average or Geometric Moving-Average Control Chart
			Modified Control Chart
			Acceptance Control Chart
		7-9 Risk-Adjusted Control Charts
			Risk-Adjusted Cumulative Sum (RACUSUM) Chart
			Risk-Adjusted Sequential Probability Ratio Test (RASPRT)
			Risk-Adjusted Exponentially Weighted Moving-Average (RAEWMA) Chart
			Variable Life-Adjusted Display (VLAD) Chart
		7-10 Multivariate Control Charts
			Controlling Several Related Quality Characteristics
			Hotelling’s T2 Control Chart and Its Variations
			Phase 1 and Phase 2 Charts
			Usage and Interpretations
			Individual Observations with Unknown Process Parameters
			Generalized Variance Chart
		Case Study
		Summary
		Key Terms
		Exercises
		References
	Chapter 8 Control Charts for Attributes
		8-1 Introduction and Chapter Objectives
		8-2 Advantages and Disadvantages of Attribute Charts
			Advantages
			Disadvantages
		8-3 Preliminary Decisions
		8-4 Chart for Proportion Nonconforming: p-Chart
			Construction and Interpretation
			Variable Sample Size
			Risk-Adjusted p-Charts in Health Care
			Special Considerations for p-Charts
		8-5 Chart for Number of Nonconforming Items: np-Chart
			No Standard Given
			Standard Given
		8-6 Chart for Number of Nonconformities: c-Chart
			No Standard Given
			Standard Given
			Probability Limits
			Applications in Health Care When Nonoccurence of Nonconformities Are Not Observable
		8-7 Chart for Number of Nonconformities Per Unit: u-Chart
			Variable Sample Size and No Specified Standard
			Risk-Adjusted u–Charts in Health Care
		8-8 Chart for Demerits Per Unit: u-Chart
			Classification of Nonconformities
			Construction of a U-Chart
		8-9 Charts for Highly Conforming Processes
			Transformation to Normality
			Use of Exponential Distribution for Continuous Variables
			Use of Geometric Distribution for Discrete Variables
			Probability Limits
			Applications in Health Care of Low-Occurrence Nonconformities
		8-10 Operating Characteristic Curves for Attribute Control Charts
		Case Study
		Summary
		Key Terms
		Exercises
		References
	Chapter 9 Process Capability Analysis
		9-1 Introduction and Chapter Objectives
		9-2 Specification Limits and Control Limits
		9-3 Process Capability Analysis
			Process Capability
		9-4 Natural Tolerance Limits
			Statistical Tolerance Limits
		9-5 Specifications and Process Capability
		9-6 Process Capability Indices
			Cp Index
			Upper and Lower Capability Indices
			Cpk Index
			Capability Ratio
			Taguchi Capability Index, Cpm
			Cpmk Index
			Confidence Intervals and Hypothesis Testing on Capability Indices
			Comparison of Capability Indices
			Effect of Measurement Error on Capability Indices
			Gage Repeatability and Reproducibility
			Evaluation of Measurement Systems
			Metrics for Evaluation of Measurement Systems
			Preparation for a Gage Repeatability and Reproducibility Study
			Cp Index and the Nonconformance Rate
		9-7 Process Capability Analysis Procedures
			Estimating Process Mean and Standard Deviation
		9-8 Capability Analysis for Nonnormal Distributions
			Identification of Appropriate Distribution
			Box-Cox Transformation
			Using Attribute Charts
			Using a Nonparametric Approach
		9-9 Setting Tolerances on Assemblies and Components
			Tolerances on Assemblies and Subassemblies
			Tolerance Limits on Individual Components
			Tolerance on Mating Parts
			Nonlinear Combinations of Random Variables
		9-10 Estimating Statistical Tolerance Limits of a Process
			Statistical Tolerance Limits Based on Normal Distribution
			Nonparametric Statistical Tolerance Limits
		Case Study
		Summary
		Key Terms
		Exercises
		References
PART IV PRODUCT AND PROCESS DESIGN
	Chapter 10 Reliability
		10-1 Introduction and Chapter Objectives
		10-2 Reliability
		10-3 Life-Cycle Curve and Probability Distributions in Modeling Reliability
			Probability Distributions to Model Failure Rate
			Availability
		10-4 System Reliability
			Systems with Components in Series
			Systems with Components in Parallel
			Systems with Components in Series and in Parallel
			Systems with Standby Components
		10-5 Operating Characteristic Curves
		10-6 Reliability and Life Testing Plans
			Types of Tests
			Life Testing Plans Using the Exponential Distribution
			Standard Life Testing Plans Using Handbook H-108
		10-7 Survival Analysis
			Estimation of the Survival Function
			Confidence Intervals for the Survival Function
			Comparion of Survival Functions of Two Groups
		Summary
		Key Terms
		Exercises
		References
	Chapter 11 Experimental Design and the Taguchi Method
		11-1 Introduction and Chapter Objectives
		11-2 Experimental Design Fundamentals
			Features of Experimentation
		11-3 Some Experimental Designs
			Completely Randomized Design
			Randomized Block Design
			Latin Square Design
		11-4 Factorial Experiments
			Two-Factor Factorial Experiment Using a Completely Randomized Design
			Two-Factor Factorial Experiment Using a Randomized Block Design
			Role of Contrasts
			The 2k Factorial Experiment
			Confounding in 2k Factorial Experiments
			Fractional Replication in 2k Experiments
		11-5 The Taguchi Method
		11-6 The Taguchi Philosophy
		11-7 Loss Functions
			Target Is Best
			Smaller Is Better
			Larger Is Better
		11-8 Signal-to-Noise Ratio and Performance Measures
			Target Is Best
			Smaller Is Better
			Larger Is Better
		11-9 Critique of S/N Ratios
		11-10 Experimental Design in the Taguchi Method
			Orthogonal Arrays and Linear Graphs
			Estimation of Effects
		11-11 Parameter Design in the Taguchi Method
			Application to Attribute Data
		11-12 Critique of Experimental Design and the Taguchi Method
		Summary
		Key Terms
		Exercises
		References
	Chapter 12 Process Modeling Through Regression Analysis
		12-1 Introduction and Chapter Objectives
		12-2 Deterministic and Probabilistic Models
		12-3 Model Assumptions
		12-4 Least Squares Method for Parameter Estimation
			Performance Measures of a Regression Model
		12-5 Model Validation and Remedial Measures
			Linearity of Regression Function
			Constancy of Error Variance
			Normality of Error Component
			Independence of Error Components
		12-6 Estimation and Inferences from a Regression Model
			Inferences on Individual βi Parameters
			Inferences on All βi, i= 1, 2, . . ., p . 1 Parameters
			Simultaneous Inferences on Some βi, i= 1, 2, . . ., p . 1
			Hypothesis Tests on a Subset of βi Parameters
			Estimation of Mean Response
			Simultaneous Confidence Intervals for Several Mean Responses
			Prediction of Individual Observations
			Simultaneous Prediction Intervals for Several New Observations
		12-7 Qualitative Independent Variables
			Additive Model
			Interaction Model
		12-8 Issues in Multiple Regression
			Data from a Retrospective Versus Designed Experiment
			Outliers in the Space of the Independent Variables
			Outliers for the Dependent Variable
			Influential Observations
			Multicollinearity
			Detection of Multicollinearity
			Effects of Multicollinearity
		12-9 Logistic Regression
			Binary Response Variable
			Assumptions in Regression
			Nominal Polytomous Response Variable
			Ordinal Polytomous Response Variable
		12-10 Classification Problems
			Performance Measures in Classification Problems
			Tests of Association in 2 ~ 2 Contingency Tables
			Receiver Operating Characteristic Curve
		Summary
		Key Terms
		Exercises
		References
Appendixes
	A-1 Cumulative Binomial Distribution
	A-2 Cumulative Poisson Distribution
	A-3 Cumulative Standard Normal Distribution
	A-4 Values of t for a Specified Right-Tail Area
	A-5 Chi-Squared Values for a Specified Right-Tail Area
	A-6 Values of F for a Specified Right-Tail Area
	A-7 Factors for Computing Centerline and Three-Sigma Control Limits
	A-8 Uniform Random Numbers
Index
EULA