Certified Quality Engineer Exam Preparation Course

OUTLINE (Return to Main)

1. Management and Leadership in Quality Engineering

   1. Management Systems for Improving Quality
      1. Benchmarking
      2. Project Management
      3. Goal Setting
   2. Leadership Principles and Techniques
      1. Maslow’s Hierarchy
      2. Theories X and Y
      3. Team Development and Management
   3. Facilitation Principles and Techniques
      1. Brainstorming
      2. NGT
      3. Conflict Resolution
   4. Cost of Quality
   5. Quality Philosophies and Approaches
      1. Benefits of Quality
      2. History of Quality (Deming’s 14 Points for Management, The Juran Trilogy, Philip Crosby, Taguchi)
   6. Customer Relations
      
2. Quality Systems Development, Implementation, and Verification
   1. Quality Standards (ISO 9000)
   2. Quality Audits
      1. Types of Audits
      2. Steps in the Audit Process
      3. Audit Roles and Responsibilities
      4. Verification of Corrective Action
3. Planning, Controlling, and Assuring Product and Process Quality
   1. Material Control
      1. Material Review Board (MRB)
   2. Acceptance Sampling
      1. General Concepts
      2. Type I (Producer’s) and Type II (Consumer’s) Risk
      3. Operating Characteristics (OC) Curves
      4. Overview of Acceptance Sampling Plans (ANSI/ASQ Z1.4 & Z1.9, Dodge-Romig, C=0)
         1. Use of ANSI/ASQ Z1.4 & Z 1.9
         2. Definitions of AQL, LTPD, AOQ, AOQL
   3. Measurement Systems
1. Terms and Definitions (Precision, accuracy, metrology, repeatability, reproducibility, etc.)
2. Gage R&R Studies
3. Sources of Measurement Variability
4. Control of Measurement Equipment
   
4. Reliability and Risk Management
   1. Terms and Definitions
   2. Reliability Life Characteristic Concepts
   3. Design of Systems for Reliability (Series, Parallel-Series, and Series-Parallel Systems)
   4. Active vs. Passive Redundancy
   5. Availability and Maintainability
   6. Failure Rates and the Bathtub Curve
      1. Methods to Maintain Process and Product Reliability
   7. Calculation of MTTF and MTBF
      
5. Problem Solving and Quality Improvement
   1. Approaches (the Shewhart PDCA Cycle, DMAIC, etc.)
   2. Quality Tools (Flowcharts, Cause-and-Effect Diagrams, Line Charts, Histograms, Pareto Analysis, Tally Sheets, Scatter Plots/Correlation Analysis)
   3. Corrective Action (Root Causes vs. Immediate Causes, Verification and Validation, Preventive Action)
   4. Overcoming Barriers to Quality Improvement (Force Field Analysis, Impact Analysis)
      
6. Quantitative Methods
   1. Concepts of Probability and Statistics
      1. Terms
      2. Drawing Valid Statistical Conclusions
      3. Central Limit Theorem and Sampling Distribution of the Mean
      4. Basic Probability Concepts
   2. Collecting and Summarizing Data
      1. Types of Data (Variables vs. Discrete)
      2. Measurement Scales (Nominal, Ordinal, Interval, and Ratio)
      3. Methods for Collecting Data
      4. Techniques for Assuring Data Accuracy and Integrity (Random Sampling vs. Systematic Sampling, Sample Representativeness, etc.)
      5. Descriptive Statistics (Mean, Median, Mode, Range, Standard Deviation, Variance)
      6. Graphical Methods
         1. Depicting Relationships (Scatter Diagrams)
         2. Depicting Distributions (Histograms, Normal Probability Plots)
   3. Properties and Applications of Probability Distributions
      1. Discrete Distributions (Binomial, Poisson, Hypergeometric)
      2. Continuous Distributions ( Normal z, Student’s t, Chi-Square, F, Lognormal, Exponential, Weibull, Uniform)
   4. Statistical Decision-Making
      1. Point and Interval Estimation (Means, Proportions, and Variances)
      2. Hypothesis Testing (Means, Proportions, and Variances)
         1. Significance Level, Risks, Type I vs. Type II Error
         2. Statistical vs. Practical Significance
      3. Paired Comparison Tests
      4. Goodness-of-Fit Tests
      5. Analysis of Variance (ANOVA)
      6. Contingency Tables
7. Measuring and Modeling Relationships Between Variables
   1. Simple and Multiple Least-Squares Linear Regression
   2. Simple Linear Correlation
      
8. Designing Experiments
   1. Terminology
   2. Planning and Organizing Experiments
   3. Design Principles
   4. Design and Analysis of One-Factor Experiments
   5. Design and Analysis of Full Factorial Experiments
   6. Design and Analysis of Two-Level Fractional Factorial Experiments
      
9. Statistical Process Control (SPC)
   1. Objectives and Benefits
   2. Selection of Variables
   3. Rational Subgrouping
   4. Selection and Application of Control Charts (X-bar and R, X-bar and S, Individual and Moving Range , p, np, c, and u Charts)
   5. Analysis of Control Charts (the Western Electric / Shewhart Tests)
   6. Pre-Control
   7. Short-Run SPC
      
10. Analyzing Process Capability
    1. Designing and Conducting Process Capability Studies
    2. Calculating Process Performance vs. Specification (Natural Process Limits vs. Specification Limits, Calculation of Percent Defective)
    3. Process Capability Indices (Cp / Cpk, Sigma Levels)
    4. Process Performance Indices (Pp / Ppk)
       
11. Appendix
    1. Statistical Tool Summary
    2. Probability Tool Summary
    3. Statistical Process Control (SPC) Tool Summary
    4. Hypothesis Test Tool Summary
    5. Glossary of Statistical Symbols
    6. Normalized z Table
    7. Cumulative Binomial Probability Distribution Table
    8. Cumulative Poisson Probability Distribution Table
    9. t Distribution Table
    10. c 2 Distribution Table
    11. F Distribution Table for 5% Alpha Risk
    12. Minimum Sample Sizes / Beta Risk Levels for Tests on Single Population Means: One- and Two-Tailed Tests
    13. Minimum Sample Sizes/Beta Risk Levels for Tests Comparing Two Population Means: One- and Two-Tailed Tests
    14. Normal Probability Plot Paper
    15. Set of 500+ Sample CQE Exam Questions With Answer Key

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