Six Sigma

Six Sigma

IIT Kharagpur July 2018 via YouTube Direct link

Lecture 07 : Quality Management: Basics and Key Concepts

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8 of 64

Lecture 07 : Quality Management: Basics and Key Concepts

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Six Sigma

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  1. 1 Six Sigma-Introductory Video
  2. 2 Lecture 1: Brief overview of the course
  3. 3 Lecture 2: Quality concepts and definition
  4. 4 Lecture 03: History of continuous improvement
  5. 5 Lecture 4: Six Sigma Principles and Focus Areas (Part 1)
  6. 6 Lecture 5: Six Sigma Principles and Focus Areas (Part 2)
  7. 7 Lecture 6: Six Sigma Applications
  8. 8 Lecture 07 : Quality Management: Basics and Key Concepts
  9. 9 Lecture 8: Fundamentals of Total Quality Management
  10. 10 Lecture 9: Cost of quality
  11. 11 Lecture 10: Voice of customer
  12. 12 Lecture 11: Quality Function Deployment (QFD)
  13. 13 Lecture 12: Management and Planning Tools (Part 1)
  14. 14 Lecture 13: Management and Planning Tools (Part 2)
  15. 15 Lecture 14: Six Sigma Project Identification, Selection and Definition
  16. 16 Lecture 15: Project Charter and Monitoring
  17. 17 Lecture 16: Process characteristics and analysis
  18. 18 Lecture 17: Process Mapping: SIPOC
  19. 19 Lecture 18: Data Collection and Summarization (Part 1)
  20. 20 Lecture 19: Data Collection and Summarization (Part 2)
  21. 21 Lecture 20: Measurement systems: Fundamentals
  22. 22 Lecture 21: Measurement systems analysis: Gage R&R study
  23. 23 Lecture 22: Fundamentals of statistics
  24. 24 Lecture 23: Probability theory
  25. 25 Lecture 24: Process capability analysis: Key Concepts
  26. 26 Lecture 25: Process capability analysis: Measures and Indices
  27. 27 Lecture 26: Process capability analysis: Minitab Application
  28. 28 Lecture 27: Non-normal process capability analysis
  29. 29 Lecture 28: Hypothesis testing: Fundamentals
  30. 30 Lecture 29: Hypothesis Testing: Single Population Test
  31. 31 Lecture 30: Hypothesis Testing: Two Population Test
  32. 32 Lecture 31: Hypothesis Testing: Two Population: Minitab Application
  33. 33 Lecture 32: Correlation and Regression Analysis
  34. 34 Lecture 33: Regression Analysis: Model Validation
  35. 35 Lecture 34: One-Way ANOVA
  36. 36 Lecture 35: Two-Way ANOVA
  37. 37 Lecture 36: Multi-vari Analysis
  38. 38 Lecture 37: Failure Mode Effect Analysis (FMEA)
  39. 39 Lecture 38: Introduction to Design of Experiment
  40. 40 Lecture 39: Randomized Block Design
  41. 41 Lecture 40: Randomized Block Design: Minitab Application
  42. 42 Lecture 41: Factorial Design
  43. 43 Lecture 42: Factorial Design: Minitab Application
  44. 44 Lecture 43: Fractional Factorial Design
  45. 45 Lecture 44: Fractional Factorial Design: Minitab Application
  46. 46 Lecture 45: Taguchi Method: Key Concepts
  47. 47 Lecture 46: Taguchi Method: Illustrative Application
  48. 48 Lecture 47: Seven QC Tools
  49. 49 Lecture 48: Statistical Process Control: Key Concepts
  50. 50 Lecture 49: Statistical Process Control: Control Charts for Variables
  51. 51 Lecture 50: Operating Characteristic ,(OC)
  52. 52 Lecture 51: Statistical Process Control: Control Charts for Attributes
  53. 53 Lecture 52: OC, Curve for Attribute control chart
  54. 54 Lecture 53: Statistical Process Control: Minitab Application
  55. 55 Lecture 54: Acceptance Sampling: Key Concepts
  56. 56 Lecture 55: Design of Acceptance Sampling Plans for Attributes (Part 1)
  57. 57 Lecture 56: Design of Acceptance Sampling Plans for Attributes (Part 2)
  58. 58 Lecture 57: Design of Acceptance Sampling Plans for Variables
  59. 59 Lecture 58: Acceptance Sampling: Minitab Application
  60. 60 Lecture 59: Design for Six Sigma (DFSS): DMADV, DMADOV
  61. 61 Lecture 60: Design for Six Sigma (DFSS): DFX
  62. 62 Lecture 61: Team Management
  63. 63 Lecture 62: Six Sigma: Case study
  64. 64 Lecture 63: Six Sigma: Summary of key concepts

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