Statistical Quality

Module 0: Data Files

1. Equations

2. Data Files Used in the Videos

Module 1: Quality Control Graphical Tools

1. Run Chart in MS Excel

2. Run Chart in Minitab

3. Pareto Diagram MS Excel

4. Pareto Diagram in Minitab

5. Cause and Effect Diagram in Minitab

Module 2: Sample, Population, and The Normal Distribution, The Primary Basic

1. Standard Normal Distribution in MS Excel

2. Standard Normal Distribution Dynamic Chart in MS Excel

3. Normal Distribution Dynamic Chart in MS Excel

4. Normality Test PP MS Excel

5. Normality Test Chi Square Goodness of fit MS Excel

6. Definitions for Sample and Population with Examples

Module 3: Six Sigma Basics

1. Six Sigma Basic Centered Process Capability MS Excel

2. Six Sigma Basic Off Centered Process Capability MS Excel

Module 4: The Central Limit Theorem, The Basic to Variable Control Charts

1. Central Limit Theorem two Die MS Excel

2. Central Limit Theorem Proof using three four and five die MS Excel

Module 5 to 8: Introduction to the Control Charts World

1. Introduction to Control Charts (data/variable types)

Module 5: Control Charts for Variables

1. Trial R-Control Chart MS Excel

2. Revised R-Control Chart MS Excel

3. Control Capability Analysis for Centered Process normally distributed data

4. Capability Analysis for Off Centered Process normally distributed data

5. Capability Analysis for variables in MINITAB

6. Process Capability Cp & Cpk, vs. Process Performance Pp and Ppk MS Excel

7. Reverse Capability Analysis: USL & LSL from Cp

8. Variable Control Charts in Minitab

9. Trial s-Control Chart MS Excel

10. Revised s-Control Chart MS Excel

11. Normal Distribution Lay on Top of the Control Charts MS Excel (Not testing this one in the exam anymore!)

12. Variable Control Chart Case Study 1 Shaft Bearing Design

13. Variable Control Charts Case Study 2 Precision Scale

14. Variable Control Charts Case Study 3 Engine Emission

15. Variable Control Charts Case Study 4 Material Strength

16. Common Mistake #1. Why Do I Need the Revised Control Chart for a Process that is within the Control Limits?

Module 6: Advanced Control Charts for Variables

Data Used in the Videos

1. Why I-MR Chart

2. I-MR Chart

3. I_MR Chart Case Study Student Exam Taking Time

4. I MR Charts Capability Analysis

Module 7: Discrete Probability Distribution, the Basics to Attribute Control Charts

1. Hypergeometric Distribution

2. Binomial Distribution

3. Poisson Distribution

4. Binomial & Poisson Distribution Comparison

Module 8: Control Charts for Attributes

1. Attribute Control np chart MS Excel

2. Attribute Control p chart MS Excel

3. Attribute Control Revised p-Charts MS Excel

4. Attribute Control p-Charts Variable Subgroup Size

5. Attribute Control c-chart MS Excel

6. Attribute Control Trial u-chart MS Excel

7. Attribute Control Revised u-chart

8. Attribute Control p np c & u charts Minitab

9. Which Attribute Chart, p np c u charts?

10. Attribute Control Charts Example 1 Multiple Choice Questions

11. Attribute Control Charts Example 2 MNSU Campus Security

12. Attribute Control Charts Example 3 Variable Sample Size

Module 9: Acceptance Sampling

1. Acceptance Sampling Operating Characteristics Curve Single Sampling

2. Acceptance Sampling Operating Characteristics Curve Double Sampling Plan

3. Average Outgoing Quality (AOQ)

4. Average Total Inspected (ATI)

5. Acceptance Sampling Alpha Beta Consumer Risk Producer Risk AQL RQ LQ RQL

6. Sample Size Calculation from Producer Risks

7. Sample Size Calculation Consumer Risk

8. Sample Size Calculations Both consumer and producer risks (Graduate Students and Advanced Learners Only)

9. Acceptance Sampling in Minitab

10. Acceptance Sampling Zero Defect Policy Example

11. Acceptance Sampling Perishable Items Example

Module 10: Design of Experiments

1. P value and the Level of Significance

2. Single Sample T Test in MS Excel

3. Two Sample T Test in MS Excel

4. Two Sample Paired T Test in MS Excel

5. Explanation of Factor, Response, dependent, independent, variable

6. Levels of a Factor

7. Single Factor or One Way ANOVA in MS Excel

8. Single Factor or One Way ANOVA Post Hoc Analysis (MS Excel part of the Post-hoc Analysis is not for the exam)

9. Two Factors or Two Way ANOVA in MS Excel

10. Basic DOE in Minitab

11. Basic Taguchi DOE in Minitab

12. Basic DOE Analysis example in Minitab

13. Factorial Design of Experiments: 2K Design Layout

Click on this link to find more materials on the Design and Analysis of Experiments page.

Module 11: Design of Experiments: Taguchi Methods

Data Used in the Video for Robust Parameter Taguchi Design of Experiment

1. Robust parameter Taguchi Design Terms Explained

2. Introduction To Robust Parameter Taguchi Design of Experiments

3. Robust Parameter Taguchi Design Signal to Noise Ratio Calculation in MS Excel

4. Robust Parameter Taguchi Design Static Example Calculations in MS Excel

5. Robust Parameter Taguchi Design Example in Minitab

6. How to Create Robust Parameter Taguchi Design in Minitab

7. How to perform Robust Parameter Taguchi Static Analysis in Minitab

8. How to perform Robust Parameter Taguchi Dynamic Analysis in Minitab

Click on this link to find more materials on the Robust Parameter Design (Taguchi Design and Analysis of Experiments).

Module 12: Gage Repeatability and Reproducibility (Gage R & R)

1. Introduction to Measurement System Analysis (MSA)/ Gauge R & R Study/ Gauge Capability

2. Measurement System Analysis (MSA)/ Gauge R & R Study/ Typical Example

3. Measurement System Analysis (MSA)/ Gauge R & R Study / Gauge Capability using Control Chart/Range Method in MS Excel

4. Measurement System Analysis (MSA) / Gauge R & R Study / Gauge Capability ANOVA Method in MS Excel

Module 13: Setting Specification Limits on Discrete Components

1. Add Components to Meet Customer Specifications for the Final Assembly

2. Setting Specification Limits on Discrete Components from the Final Assembly Requirements Six Sigma Product

3. Assembly of a Shaft and a Bearing to Meet the clearance Requirements

Technology Accessibility

MS Excel

Minitab

Reference

[Texts are ordered based on the uses in the videos demonstrations]

1. Besterfield, D. H. (2013). Quality improvement. Pearson. Prentice Hall. ISBN-10: 0132624419; ISBN-13: 978-0132624411.

2. Montgomery, D. C., (2013). Introduction to Statistical Quality Control, 7th Edition. John Wiley & Sons. ISBN-13: 978-1118146811. ISBN-10: 1118146816. [Module 3-9]

3. Rahman, M., Sanjel, D. Wu, H. (2014). Statistics introduction. Publisher: Kendall Hunt. [Module 2 & 4]

4. Montgomery, D. C. (2012). Design and analysis of experiments 8th/E. John Wiley & Sons. ISBN-13: 978-1118146927; ISBN-10: 1118146921 [Module 10]

5. Taguchi, G., Chowdhury, S., Wu, Y., Taguchi, S., & Yano, H. (2011). Taguchi's quality engineering handbook. Hoboken, N.J: John Wiley & Sons. [Module 11]

6. Chowdhury, S., & Taguchi, S. (2016). Robust Optimization: World's Best Practices for Developing Winning Vehicles. John Wiley & Sons. [Module 11]

7. Borror, C. M. (2009). The certified quality engineer handbook. Milwaukee, Wis: ASQ Quality Press. [Module 12]

8. Burdick, R. K., Borror, C. M., & Montgomery, D. C. (2005). Design and analysis of gauge R & R studies: Making decisions with confidence intervals in random and mixed ANOVA models. Philadelphia, Pa: Society for Industrial Applied Mathematics. [Module 12]