book

A First Course in Quality Engineering, 3rd Edition

by K.S. Krishnamoorthi, Arunkumar Pennathur, V. Ram Krishnamoorthi

September 2018

Intermediate to advanced

626 pages

18h 59m

English

CRC Press

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1.1 A Historical Overview1.1.1 A Note about “Quality Engineering”1.2 Defining Quality1.2.1 Product Quality vs. Service Quality1.3 The Total Quality System1.4 Total Quality Management1.5 Economics of Quality1.6 Quality, Productivity, and Competitive Position1.7 Quality Costs1.7.1 Categories of Quality Costs1.7.1.1 Prevention Cost1.7.1.2 Appraisal Cost1.7.1.3 Internal Failure Cost1.7.1.4 External Failure Cost1.7.2 Steps in Conducting a Quality Cost Study1.7.3 Projects Arising from a Quality Cost Study1.7.4 Quality Cost Scoreboard1.7.5 Quality Costs Not Included in the TQC1.7.6 Relationship among Quality Cost Categories1.7.7 Summary on Quality Costs1.7.8 A Case Study in Quality Costs1.8 Success Stories1.9 Exercise1.9.1 Practice Problems1.9.2 Mini-ProjectsMini-Project 1.1Mini-Project 1.2Mini-Project 1.3Mini-Project 1.4

2.1 Variability in Populations2.2 Some Definitions2.2.1 The Population and a Sample2.2.2 Two Types of Data2.3 Quality vs. Variability2.4 Empirical Methods for Describing Populations2.4.1 The Frequency Distribution2.4.1.1 The Histogram2.4.1.2 The Cumulative Frequency Distribution2.4.2 Numerical Methods for Describing Populations2.4.2.1 Calculating the Average and Standard Deviation2.4.3 Other Graphical Methods2.4.3.1 Stem-and-Leaf Diagram2.4.3.2 Box-and-Whisker Plot2.4.4 Other Numerical Measures2.4.4.1 Measures of Location2.4.4.2 Measures of DispersionSummary on Empirical Methods2.4.5 Exercises in Empirical Methods2.5 Mathematical Models for Describing Populations2.5.1 Probability2.5.1.1 Definition of Probability2.5.1.2 Computing the Probability of an Event2.5.1.2.1 Method of Analysis2.5.1.2.2 A Special Case2.5.1.2.3 Method of Relative Frequency2.5.1.3 Theorems on Probability2.5.1.3.1 Addition Theorem of ProbabilityCorollary2.5.1.3.2 The Extension of the Addition Theorem2.5.1.3.3 Complement Theorem of Probability2.5.1.3.4 Theorems on the Joint Occurrence of Events2.5.1.3.5 Conditional Probability2.5.1.3.6 Independent Events2.5.1.3.7 The Multiplication Theorems of Probability2.5.1.3.8 The Theorem of Total Probability2.5.1.4 Counting the Sample Points in a Sample Space2.5.1.4.1 The Multiplication Rule2.5.1.4.2 Permutations2.5.1.4.3 Theorem on Number of Permutations2.5.1.4.4 Combinations2.5.1.4.5 Theorem on Number of CombinationsSummary on Probability2.5.2 Exercises in Probability2.5.3 Probability Distributions2.5.3.1 Random Variable2.5.3.2 Probability Mass Function2.5.3.3 Probability Density Function2.5.3.4 The Cumulative Distribution Function2.5.3.5 The Mean and Variance of a Distribution2.5.4 Some Important Probability Distributions2.5.4.1 The Binomial Distribution2.5.4.1.1 The Mean and Variance of a Binomial Variable2.5.4.2 The Poisson Distribution2.5.4.2.1 The Mean and Variance of the Poisson Distribution2.5.4.3 The Normal Distribution2.5.4.3.1 The Standard Normal Distribution2.5.4.3.2 Application of the Normal Distribution2.5.4.4 Distribution of the Sample Average X¯2.5.4.5 The Central Limit TheoremSummary on Probability Distributions2.5.5 Exercises in Probability Distributions2.6 Inference of Population Quality from a Sample2.6.1 Definitions2.6.2 Confidence Intervals2.6.2.1 CI for the µ of a Normal Population When s Is Known2.6.2.2 Interpretation of CI2.6.2.3 CI for µ When s Is Not Known2.6.2.4 CI for s2 of a Normal Population2.6.3 Hypothesis TestingTwo Types of Errors2.6.3.1 Test Concerning the Mean µ of a Normal Population When s Is Known2.6.3.2 Why Place the Claim Made about a Parameter in H1?2.6.3.3 The Three Possible Alternate Hypotheses2.6.3.4 Test Concerning the Mean µ of a Normal Population When s Is Not Known2.6.3.5 Test for Difference of Two Means When ss Are Known2.6.4 Tests for Normality2.6.4.1 Use of the Normal Probability Plot2.6.4.2 Normal Probability Plot on the Computer2.6.4.3 A Goodness-of-Fit Test2.6.5 The P-ValueSummary on Inference Methods2.6.6 Exercises in Inference Methods2.6.6.1 Confidence Intervals2.6.6.2 Hypothesis Testing2.6.6.3 Goodness-of-Fit Test2.7 Mini-ProjectsMini-Project 2.1Mini-Project 2.2Mini-Project 2.3Mini-Project 2.4
3.1 Planning for Quality3.1.1 The Product Creation Cycle3.2 Product Planning3.2.1 Finding Customer Needs3.2.1.1 Customer Survey3.2.2 Quality Function Deployment3.2.2.1 Customer Requirements and Design Features3.2.2.2 Prioritizing Design Features3.2.2.3 Choosing a Competitor as Benchmark3.2.2.4 Targets3.2.3 Reliability Fundamentals3.2.3.1 Definition of Reliability3.2.3.2 Hazard Function3.2.3.3 The Bathtub Curve3.2.3.4 Distribution of Product Life3.2.3.5 The Exponential Distribution3.2.3.6 Mean Time to Failure3.2.3.7 Reliability Engineering3.3 Product Design3.3.1 Parameter Design3.3.2 Design of Experiments3.3.2.1 22 Factorial Design3.3.2.2 Randomization3.3.2.3 Experimental Results from a 22 Design3.3.2.4 Calculating the Factor Effects3.3.2.5 Main Effects3.3.2.6 Interaction Effects3.3.2.7 A Shortcut for Calculating Effects3.3.2.8 Determining the Significance of Effects3.3.2.9 The 23 Design3.3.2.10 Interpretation of the Results3.3.2.11 Model Building3.3.2.12 Taguchi Designs3.3.3 Tolerance Design3.3.3.1 Traditional Approaches3.3.3.2 Tolerancing According to Dr. Taguchi3.3.3.3 Assembly Tolerances3.3.3.4 The RSS Formula3.3.3.5 Natural Tolerance Limits3.3.4 Failure Mode and Effects Analysis3.3.5 Concurrent Engineering3.3.5.1 Design for Manufacturability/Assembly3.3.5.2 Design Reviews3.4 Process Design3.4.1 The Process Flow Chart3.4.2 Process Parameter Selection: Experiments3.4.3 Floor Plan Layout3.4.4 Process FMEA3.4.5 Process Control Plan3.4.6 Other Process Plans3.4.6.1 Process Instructions3.4.6.2 Packaging Standards3.4.6.3 Preliminary Process Capabilities3.4.6.4 Product and Process Validation3.4.6.5 Process Capability Results3.4.6.6 Measurement System Analysis3.4.6.7 Product/Process Approval3.4.6.8 Feedback, Assessment, and Corrective Action3.5 Exercise3.5.1 Practice Problems3.5.2 Mini-ProjectsMini-Project 3.1Mini-Project 3.2Mini-Project 3.3
4.1 Process Control4.2 The Control Charts4.2.1 Typical Control Chart4.2.2 Two Types of Data4.3 Measurement Control Charts4.3.1 >X¯- and R-Charts4.3.2 A Few Notes about the X¯ and R-Charts4.3.2.1 The Many Uses of the Charts4.3.2.2 Selecting the Variable for Charting4.3.2.3 Preparing Instruments4.3.2.4 Preparing Check Sheets4.3.2.5 False Alarm in the X¯-Chart4.3.2.6 Determining Sample Size4.3.2.7 Why 3-Sigma Limits?4.3.2.8 Frequency of Sampling4.3.2.9 Rational Subgrouping4.3.2.10 When the Sample Size Changes for X¯- and R-Charts4.3.2.11 Improving the Sensitivity of the X¯-Chart4.3.2.12 Increasing the Sample Size4.3.2.13 Use of Warning Limits4.3.2.14 Use of Runs4.3.2.15 Patterns in Control Charts4.3.2.16 Control vs. Capability4.3.3 X¯ and S-Charts4.3.4 The Run Chart4.4 Attribute Control Charts4.4.1 The P-Chart4.4.2 The C-Chart4.4.3 Some Special Attribute Control Charts4.4.3.1 The P-Chart with Varying Sample Sizes4.4.3.2 The nP-Char4.4.3.3 The Percent Defective Chart (100P-Chart)4.4.3.4 The U-Chart4.4.4 A Few Notes about the Attribute Control Charts4.4.4.1 Meaning of the LCL on the P- or C-Chart4.4.4.2 P-Chart for Many Characteristics4.4.4.3 Use of Runs4.4.4.4 Rational Subgrouping4.5 Summary on Control Charts4.5.1 Implementing SPC on Processes4.6 Process Capability4.6.1 Capability of a Process with Measurable Output4.6.2 Capability Indices Cp and C pk4.6.3 Capability of a Process with Attribute Output4.7 Measurement System Analysis4.7.1 Properties of Instruments4.7.2 Measurement Standards4.7.3 Evaluating an Instrument4.7.3.1 Properties of a Good Instrument4.7.3.2 Evaluation Methods4.7.3.3 Resolution4.7.3.4 Bias4.7.3.5 Variability (Precision)4.7.3.6 A Quick Check of Instrument Adequacy4.8 Exercise4.8.1 Practice Problems4.8.2 Mini-ProjectsMini-Project 4.1Mini-Project 4.2Mini-Project 4.3
5.1 Derivation of Limits5.1.1 Limits for the X¯-Chart5.1.2 Limits for the R-Chart5.1.3 Limits for the P-Chart5.1.4 Limits for the C-Chart5.2 Operating Characteristics of Control Charts5.2.1 Operating Characteristics of an X¯-Chart5.2.1.1 Computing the OC Curve of an X¯-Chart5.2.2 OC Curve of an R-Chart5.2.3 Average Run Length5.2.4 OC Curve of a P-Chart5.2.5 OC Curve of a C-Chart5.3 Measurement Control Charts for Special Situations5.3.1 X¯- and R-Charts When Standards for µ and/or s Are Given5.3.1.1 Case I: µ Given, s Not Given5.3.1.2 Case II: µ and s Given5.3.2 Control Charts for Slow Processes5.3.2.1 Control Chart for Individuals (X-Chart)5.3.2.2 Moving Average and Moving Range Charts5.3.2.3 Notes on Moving Average and Moving Range ChartsWhat Is a Good Value for n?A Caution5.3.3 The Exponentially Weighted Moving Average Chart5.3.3.1 Limits for the EWMA Chart5.3.4 Control Charts for Short Runs5.3.4.1 The DNOM Chart5.3.4.2 The Standardized DNOM Chart5.4 Topics in Process Capability5.4.1 The C pm Index5.4.2 Comparison of C p?, C pk?, and C pm5.4.3 Confidence Interval for Capability Indices5.4.4 Motorola’s 6s Capability5.5 Topics in the Design of Experiments5.5.1 Analysis of Variance5.5.2 The General 2k Design5.5.3 The 24 Design5.5.4 2k Design with Single Trial5.5.5 Fractional Factorials: One-Half Fractions5.5.5.1 Generating the One-Half Fraction5.5.5.2 Calculating the Effects5.5.6 Resolution of a Design5.6 Exercise5.6.1 Practice Problems5.6.2 Mini-ProjectsMini-Project 5.1Mini-Project 5.2
6.1 Managing Human Resources6.1.1 Importance of Human Resources6.1.2 Organizations6.1.2.1 Organization Structures6.1.2.2 Organizational Culture6.1.3 Quality Leadership6.1.3.1 Characteristics of a Good Leader6.1.4 Customer Focus6.1.5 Open Communications6.1.6 Empowerment6.1.7 Education and Training6.1.7.1 Need for TrainingNecessity of Basic SkillsGlobal CompetitionContinuous Change in TechnologyDiversity in the WorkplaceNeed to Improve Continuously6.1.7.2 Benefits from Training6.1.7.3 Planning for Training6.1.7.4 Training Methodology6.1.7.5 Finding Resources6.1.7.6 Evaluating Training Effectiveness6.1.8 Teamwork6.1.8.1 Team Building6.1.8.2 Selecting Team Members6.1.8.3 Defining the Team Mission6.1.8.4 Taking Stock of the Team’s Strength6.1.8.5 Building the Team6.1.8.6 Basic Training for Quality Teams6.1.8.7 Desirable Characteristics among Team MembersTrustSelflessnessResponsibilityEnthusiasmInitiativeResourcefulnessTolerancePerseverance6.1.8.8 Why a Team?6.1.8.9 Ground Rules for Running a Team Meeting6.1.8.10 Making the Teams WorkMaking Team Members Know One AnotherResolving Conflicts PromptlySetting an Example by the OrganizationRewarding Good Teams6.1.8.11 Different Types of TeamsProcess Improvement TeamsCross-Functional TeamsSelf-Managed Teams6.1.8.12 Quality Circles6.1.9 Motivation Methods6.1.10 Principles of Management6.2 Strategic Planning for Quality6.2.1 History of Planning6.2.2 Making the Strategic Plan6.2.3 Strategic Plan Deployment6.3 Exercise6.3.1 Practice Problems6.3.2 Mini-ProjectMini-Project 6.1
7.1 Importance of Quality in Supplies7.2 Establishing a Good Supplier Relationship7.2.1 Essentials of a Good Supplier Relationship7.3 Choosing and Certifying Suppliers7.3.1 Single vs. Multiple Suppliers7.3.2 Choosing a Supplier7.3.3 Certifying a Supplier7.4 Specifying the Supplies Completely7.5 Auditing the Supplier7.6 Supply Chain Optimization7.6.1 The Trilogy of Supplier Relationship7.6.2 Planning7.6.3 Control7.6.4 Improvement7.7 Using Statistical Sampling for Acceptance7.7.1 The Need for Sampling Inspection7.7.2 Single Sampling Plans for Attributes7.7.2.1 The Operating Characteristic Curve7.7.2.2 Calculating the OC Curve of a Single Sampling Plan7.7.2.3 Designing an SSP7.7.2.4 Choosing a Suitable OC Curve7.7.2.5 Choosing a Single Sampling Plan7.7.3 Double Sampling Plans for Attributes7.7.3.1 Why Use a DSP?7.7.3.2 The OC Curve of a DSP7.7.4 The Average Sample Number of a Sampling Plan7.7.5 MIL-STD-105E (ANSI Z1.4)7.7.5.1 Selecting a Sampling Plan from MIL-STD-105E7.7.6 Average Outgoing Quality Limit7.7.7 Some Notes about Sampling Plans7.7.7.1 What Is a Good AQL?7.7.7.2 Available Choices for AQL Values in the MIL-STD-105E7.7.7.3 A Common Misconception about Sampling Plans7.7.7.4 Sampling Plans vs. Control Charts7.7.7.5 Variable Sampling Plans7.8 Exercise
8.1 The Need for Continuous Improvement8.2 The Problem-Solving Methodology8.2.1 Deming’s PDCA Cycle8.2.2 Juran’s Breakthrough Sequence8.2.3 The Generic Problem-Solving Methodology8.3 Quality Improvement Tools8.3.1 Cause-and-Effect Diagram8.3.2 Brainstorming8.3.3 Benchmarking8.3.4 Pareto Analysis8.3.5 Histogram8.3.6 Control Charts8.3.7 Scatter Plots8.3.8 Regression Analysis8.3.8.1 Simple Linear Regression8.3.8.2 Model Adequacy8.3.8.3 Test of Significance8.3.8.4 Multiple Linear Regression8.3.8.5 Nonlinear Regression8.3.9 Correlation Analysis8.3.9.1 Significance in Correlation8.4 Lean Manufacturing8.4.1 Quality Control8.4.2 Quantity Control8.4.3 Waste and Cost Control8.4.4 Total Productive Maintenance8.4.5 Stable, Standardized Processes8.4.6 Visual Management8.4.7 Leveling and Balancing8.4.8 The Lean Culture8.5 Exercise8.5.1 Practice Problems8.5.2 Term Project
9.1 The Systems Approach9.2 Dr. Deming’s System9.2.1 Long-Term PlanningPoint 1: Create Constancy of Purpose for Improvement of Product and Service9.2.2 Cultural ChangePoint 2: Adopt the New Philosophy9.2.3 Prevention OrientationPoint 3: Cease Dependence on Mass Inspection9.2.4 Quality in ProcurementPoint 4: End the Practice of Awarding Business on the Basis of Price Tag Alone9.2.5 Continuous ImprovementPoint 5: Continuously Improve the System of Production and Service9.2.6 Training, Education, Empowerment, and TeamworkPoint 6: Institute TrainingPoint 7: Adopt and Institute LeadershipPoint 8: Drive Out FearPoint 9: Break Down Barriers between StaffPoint 10: Eliminate Slogans, Exhortations, and Targets for the WorkforcePoint 11(a): Eliminate Numerical Quotas for the WorkforcePoint 11(b): Eliminate Numerical Goals for People in ManagementPoint 12: Remove Barriers that Rob People of Pride of WorkmanshipPoint 13: Encourage Education and Self-Improvement for EveryonePoint 14: Take Action to Accomplish the Transformation9.3 Dr. Juran’s System9.3.1 Quality Planning9.3.2 Quality Control9.3.3 Quality Improvement9.4 Dr. Feigenbaum’s System9.5 Baldrige Award Criteria9.5.1 Criterion 1: Leadership9.5.1.1 Senior Leadership9.5.1.2 Governance and Societal Responsibilities9.5.2 Criterion 2: Strategic Planning9.5.2.1 Strategy Development9.5.2.2 Strategy Implementation9.5.3 Criterion 3: Customers9.5.3.1 Voice of the Customer9.5.3.2 Customer Engagement9.5.4 Criterion 4: Measurement, Analysis, and Knowledge Management9.5.4.1 Measurement, Analysis, and Improvement of Organizational Performance9.5.4.2 Information and Knowledge Management9.5.5 Criterion 5: Workforce9.5.5.1 Workforce Environment9.5.5.2 Workforce Engagement9.5.6 Criterion 6: Operations9.5.6.1 Work Processes9.5.6.2 Operational Effectiveness9.5.7 Criterion 7: Results9.5.7.1 Product and Process Results9.5.7.2 Customer Results9.5.7.3 Workforce Results9.5.7.4 Leadership and Governance Results9.5.7.5 Financial and Market Outcomes9.6 ISO 9000 Quality Management Systems9.6.1 The ISO 9000 Standards9.6.2 The Seven Quality Management PrinciplesQMP 1 Customer FocusQMP 2 LeadershipQMP 3 Engagement of PeopleQMP 4 Process ApproachQMP 5 ImprovementQMP 6 Evidence-Based Decision MakingQMP 7 Relationship Management9.7 ISO 9001:2015 Quality Management Systems—Requirements9.7.1 Scope9.7.2 Normative Reference9.7.3 Terms and Definitions9.7.4 Context of the Organization9.7.4.1 Understanding the Organization and its Context9.7.4.2 Understanding the Needs and Expectation of Interested Parties9.7.4.3 Determining the Scope of the Quality Management System9.7.4.4 Quality Management System and its Processes9.7.5 Leadership9.7.5.1 Leadership and Commitment9.7.5.2 Policy The top management shall establish, implement, and maintain the quality policy in accordance with their needs. The quality policy shall be maintained as a record and be communicated, understood, and applied. It should also be available to relevant interested parties.9.7.5.3 Organizational Roles, Responsibilities, and Authorities9.7.6 Planning9.7.6.1 Actions to Address Risks and Opportunities9.7.6.2 Quality Objectives and Planning to Achieve Them9.7.6.3 Planning of Changes9.7.7 Support9.7.7.1 Resources9.7.7.2 Competence9.7.7.3 Awareness9.7.7.4 Communication9.7.7.5 Documented Information9.7.8 Operation9.7.8.1 Operation Planning and Control9.7.8.2 Requirements for Products and Services9.7.8.3 Design and Development of Products and Services9.7.8.4 Control of Externally Provided Processes, Products, and Services9.7.8.5 Production and Service Provision9.7.8.6 Release of Products and Services9.7.8.7 Control of Nonconforming Outputs9.7.9 Performance Evaluation9.7.9.1 Monitoring, Measurement Analysis, and Evaluation9.7.9.2 Internal Audit9.7.9.3 Management Review9.7.10 Improvement9.7.10.1 General9.7.10.2 Nonconformity and Corrective Action9.7.10.3 Continual Improvement9.8 The Six Sigma System9.8.1 Six Themes of Six SigmaTheme 1: Focus on the CustomerTheme 2: Data and Fact-Driven ManagementTheme 3: Process FocusTheme 4: Proactive ManagementTheme 5: Boundaryless CollaborationTheme 6: Drive for Perfection (with Tolerance for Failure)9.8.2 The 6s Measure9.8.3 The Three StrategiesProcess ImprovementProcess Design/RedesignProcess Management9.8.4 The Two Improvement Processes9.8.5 The Five-Step Road Map9.8.6 The Organization for the Six Sigma System9.9 Summary of Quality Management Systems9.10 Exercise9.10.1 Practice ProblemsDeming SystemJuran SystemBaldrige SystemISO 9000 SystemSix Sigma System9.10.2 Mini-ProjectsMini-Project 9.1 The above set of 30 questions has been created to help students understand the various systems in good detail. However, it is only one of several possible sets. Generate another set of 30 questions, six from each system, similar to but different from the above set.Mini-Project 9.2 Compare the three modern systems— Baldrige Award, ISO 9000, and Six Sigma—and identify their differences.

Overview

The book is a compilation of essential methodologies that have been developed over several decades for obtaining the needs of customers, designing products and processes, making the product, packaging and delivering the product.