Course11010512363 lectures
Six Sigma
Prof. Jitesh J Thakkar · IIT Kharagpur
About
The course on Six-Sigma will focus on detailed strategic and operational issues of process improvement and variation reduction. Six-sigma is a measure of quality that strives for near perfection. It is a disciplined, data-driven approach for eliminating defects (driving towards six standard deviations between the mean and the nearest specification limit) in any process-from manufacturing to transactional and from product to service.
A Six-sigma defect is anything outside of customer specifications. To be tagged Six Sigma, a process must not produce more than 3.4 defects per million opportunities.
Six-sigma employs a systematic approach of DMAIC (Define, Measure, Analyze, Improve and Control) for the process improvement. This course will provide a detailed understanding on various issues specific to each phase of DMAIC.
The course is designed with a practical orientation and includes cases, industry examples and MINITAB software applications.
The course is designed to satisfy the need of both industry professionals and University students.
The content is beneficial to both manufacturing and service industry.
INTENDED AUDIENCE : Mechanical Engineering, MBA, Industrial Engineering
PREREQUISITES : Statistics
INDUSTRY SUPPORT : Manufacturing and Service Industry
Lectures
Week 1
- 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
- Lecture 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
- Lecture 14 : Six Sigma Project Identification, Selection and Definition
- Lecture 15 : Process characteristics and Monitoring
- Lecture 16 : Process characteristics and analysis
- Lecture 17 : Process Mapping: SIPOC
Week 4
- 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
- Lecture 24: Process capability analysis: Key Concepts
- Lecture 25: Process capability analysis: Measures and Indices
- Lecture 26: Process capability analysis: Minitab Application
- Lecture 27: Non-normal process capability analysis
Week 6
- 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
- Lecture 34 : One-Way ANOVA
- Lecture 35 : Two-Way ANOVA
- Lecture 36 : Multi-vari Analysis
- Lecture 37 : Failure Mode Effect Analysis (FMEA)
Week 8
- Lecture 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
- Lecture 43 : Factorial Design: Minitab Application
- Lecture 44 : Fractional Factorial Design: Minitab Application
- Lecture 45 : Taguchi Method: Key Concepts
- Lecture 46 : Taguchi Method: Illustrative Application
Week 10
- 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
- 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
Syllabus and materials
At NPTEL, as the course publishes them.
Credits and licence
- Institution
- IIT Kharagpur
- Department
- Management
- Teacher
- Prof. Jitesh J Thakkar
- Level
- Undergraduate
- Language
- English
- Subjects
- Business and management
- Source
- NPTEL
- Licence
- CC BY-NC-SA, as NPTEL states it. Non-commercial use only. NPTEL's terms
- Attribution
- NPTEL states: "Distributed under Creative Commons Attribution-ShareAlike / CC BY - NC - SA", beside a BY-NC-SA badge.
- Who can watch
- NPTEL gives no rating. Invisible Network shows it to Tweens profiles and older, judged from what the source says about it. How courses are placed