Key “take away”
- Basic Statistics – 5 Steps and the significance of statistics in fundamental analysis using normal distribution (Minitab based)
- Introduction to Six Sigma – its history and present perspective
- Define Phase –Problem definition, Six Sigma Metric, base lining, time series analysis, improvement potential estimates and basics of data analysis (data types, location, variation, distribution). Fundamentals of Value Stream and using it for project pipeline development.
- Measure Phase – Data collection strategies, CLT application, MSA, capability analysis, identification product /process variables using multiple methods, Using Waste Analysis for immediate improvements, high & level prioritization (Cause & Effect Matrix) of impacting variables
- Analyze Phase – Detailed variable analysis using FMEA, Action planning for immediate gains, Data interpretation using various graphical analysis, correlation / regression, Hypothesis testing including Central Limit Theorem.
- Improve Phase – Validating highest impacting variables, Design of Experiments (2k, Full Factorial), Optimal Solution Identification. SMED techniques for cycle time reduction.
- Control Phase – Various Strategies of process control, Control Plan design, Training teams for new control plans, SPC, error proofing etc. Introducing Kanban. Project to Process Transition.