Week 1 : QUALITY: FUNDAMENTALS AND KEY CONCEPTS
Lecture 1: Brief overview of the course
Lecture 2: Quality concepts and definition
Lecture 3: History of continuous improvement
Lecture 4: Six Sigma Principles and Focus Areas (Part 1)
Lecture 5: Six Sigma Principles and Focus Areas (Part 2)
Lecture 6: Six Sigma Applications
Week 2 :
QUALITY: FUNDAMENTALS AND KEY CONCEPTSLecture 7: Quality Management: Basics and Key Concepts
Lecture 8: Fundamentals of Total Quality Management
Lecture 9: Cost of quality
Lecture 10: Voice of customer
Lecture 11: Quality Function Deployment (QFD)
Lecture 12: Management and Planning Tools (Part 1)
Lecture 13: Management and Planning Tools (Part 2)
Week 3 :
DEFINELecture 14: Six Sigma Project Identification, Selection and Definition
Lecture 15: Project Charter and Monitoring
Lecture 16: Process characteristics and analysis
Lecture 17: Process Mapping: SIPOC
Week 4 :
MEASURE Lecture 18: Data Collection and Summarization (Part 1)
Lecture 19: Data Collection and Summarization (Part 2)
Lecture 20: Measurement systems: Fundamentals
Lecture 21: Measurement systems analysis: Gage R&R study
Lecture 22: Fundamentals of statistics
Lecture 23: Probability theory
Week 5 :
MEASURE Lecture 24: Process capability analysis: Key ConceptsLecture 25: Process capability analysis: Measures and Indices
Lecture 26: Process capability analysis: Minitab Application
Lecture 27: Non-normal process capability analysis
Week 6 :
ANALYZE Lecture 28: Hypothesis testing: Fundamentals
Lecture 29: Hypothesis Testing: Single Population Test
Lecture 30: Hypothesis Testing: Two Population Test
Lecture 31: Hypothesis Testing: Two Population: Minitab Application
Lecture 32: Correlation and Regression Analysis
Lecture 33: Regression Analysis: Model Validation
Week 7 : ANALYZE
Lecture 34: One-Way ANOVA
Lecture 35: Two-Way ANOVA
Lecture 36: Multi-vari Analysis
Lecture 37: Failure Mode Effect Analysis (FMEA)
Week 8 :
IMPROVELecture 38: Introduction to Design of Experiment
Lecture 39: Randomized Block Design
Lecture 40: Randomized Block Design: Minitab Application
Lecture 41: Factorial Design
Lecture 42: Factorial Design: Minitab Application
Week 9 :
IMPROVELecture 43: Fractional Factorial Design
Lecture 44: Fractional Factorial Design: Minitab Application
Lecture 45: Taguchi Method: Key Concepts
Lecture 46: Taguchi Method: Illustrative Application
Week 10 :
CONTROL Lecture 47: Seven QC Tools
Lecture 48: Statistical Process Control: Key Concepts
Lecture 49: Statistical Process Control: Control Charts for Variables
Lecture 50: Operating Characteristic (OC) Curve for Variable Control charts
Lecture 51: Statistical Process Control: Control Charts for Attributes
Lecture 52: Operating Characteristic (OC) Curve for Attribute Control charts
Lecture 53: Statistical Process Control: Minitab Application
Week 11 :
CONTROL Lecture 54: Acceptance Sampling: Key Concepts
Lecture 55: Design of Acceptance Sampling Plans for Attributes (Part 1)
Lecture 56: Design of Acceptance Sampling Plans for Attributes (Part 2)
Lecture 57: Design of Acceptance Sampling Plans for Variables
Lecture 58: Acceptance Sampling: Minitab Application
Week 12 :
SIX SIGMA IMPLEMENTATION CHALLENGESLecture 59: Design for Six Sigma (DFSS): DMADV, DMADOV
Lecture 60: Design for Six Sigma (DFSS): DFX
Lecture 61: Team Management
Lecture 62: Six Sigma: Case study
Lecture 63: Six Sigma: Summary of key concepts
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