SF-01: Six Sigma Black Belt
Course Code: SF-01 (Six Sigma Black Belt (Duration: 15 Days))
Six Sigma emphasizes quality improvement, but it is more than statistics and tools. The proven Six Sigma methodology is a systematic application that is focused on achieving significant financial results. When properly deployed on carefully selected business projects, this methodology can lead to a significant reduction—and in many cases, elimination—of defects and out-of-control processes, which saves valuable corporate resources. That translates into immediate—and dramatic— financial profitability. Six Sigma Black Belt training teaches and prepares change agents and technical leaders within an organization to implement the principles, practices, and techniques of Six Sigma in order to deliver breakthrough business improvement results time after time.
- Define scope and execute DMAIC projects.
- Apply the DMAIC methodology to business issues and transition projects from phase to phase.
- Apply basic and more advanced statistical analyses to determine the relationship between key inputs and process outputs.
- Effectively manage team dynamics and understand how to work with multiple levels of leadership to remove barriers and achieve project success.
- Close projects and hand over control to process owners. Present projects to instructors, peers and managers.
Course Outline: Week 1
- Fundamental Quality Management Approaches.
- Fundamental of Six Sigma Methodology.
- Six Sigma Calculations.
- Introduction to DMAIC Methodology.
- Six Sigma Frame Work.
- Project CTQ’s (VOC, From VOC to CTQ’s, Business Goals, Defects/Problem).
- Voice of Customer & Voice of Process (VOC & VOP).
- Project Charter (Project title, business case, problem statement, goals, primary and secondary metrics, project team, communication plan), Project selection guidelines.
- Affinity Diagram, Kano Model, Process Mapping, Quality Function Deployment (QFD), SIPOC Diagram.
- Data Collection (Identification of KPOVs, data collection plan, types of data), Descriptive statistics (Mean, median, mode, standard deviations, range etc.), Cause & Effect Matrix.
- Pareto Chart, Histogram.
- Process Capability Analysis
- Process Capability for normal data, Process Capability for non-normal Data, Process Capability for attribute data.
- Advance Measurement System Analysis and Gage R&R
- MSA for Variable Data, MSA for Attribute Data.
- Probability Distributions & Applications
- Normal Distribution, Binomial Distribution, Poison Distribution, Exponential Distribution.
- Cause & Effect Diagram, Why Why Analysis.
- Inferential Statistics, Confidence Interval Studies , Hypothesis Testing (Variable & Attribute data).
- Mean & Variance Testing (1 sample Z test, 1 sample T test, 2 sample T test, Pair T test),Chi square testing.
- Graphical Analysis Tools.
- Dot plot, Interval plots, Box plot, Interval plots,
- Analysis of Variance (ANOVA)
- One-way ANOVA, Two-Way ANOVA.
- Correlation study.
- Regression Analysis
- Simple Regression Analysis, Multiple Regression Analysis.Best Subset Regression Analysis, Polynomial Regression Analysis.
- Failure Mode Effect Analysis (FMEA).
- Sample Size SelectionO
- One sample z-test, One sample t-test ,Two sample t- test, One sample proportion test, Two sample proportion test.
- Introduction to Design of Experiment (DoE).
- Full Factorial Design of Experiments (Planning, Analysis and Improvement).
- Fractional Factorial Design of Experiments, General Full Factorial Design, Plaket Burman Design.
- Fold Over Design, Process Optimization Design Response Surface Methodology (RSM), Evolutionary Operations (EVOP).
- Introduction to Statistical Process Control Application of Process Control Charts for Variable Data, X bar range chart, X bar sigma chart, Individual Moving Range Chart Application of Process Control Charts for Attribute Data, p-chart, np-chart, c- chart, u-chart Control Plan development, Project Conclusion & Documentation Project transformation tools to process owner.
- Written Exam (Two Hrs)