PMI CTT's Events

Training overview: 

Lean Six Sigma White, Yellow and Green Belt re-cap

Complex Root Cause Analysis Case Study 1

Complex Root Cause Analysis Case Study 2

Complex Root Cause Analysis Case Study 3

Practical Exercises for Six Sigma Statistics covered so far

Cause and Effect Matrix

Six Sigma re-cap

Trainees share their Complex Root Cause Analysis Problems and learn to use RCA Templates

Re-Cap of Process Capability (Short term and Long Term)

Lean Six Sigma Black Belt 

DMAIC, DMADV

DESIGN for X

Design for Manufacturability, Assembly and Maintenance

Strategic Alignment, Linking Projects with Organization Processes, ROI and Results

Advanced Six Sigma and Statistics – Histogram, Control Charts, Box and Whiskers Plot Diagram relationship, Population & Sampling and Central Limit Theorem

Group Facilitation Skills- Mind Mapping, WBS, Networking Diagram, Critical Path, Resource Allocation and More

Leadership development- True Colors and Personality Types

We will share one case practical case study to do into next level of Statistics

Define – 

Use of A3 Sheet,

RASCI Chart, 

Stakeholders Analysis, 

Re-Cap of VOC, Survey, Kano Model and CTQ,

Quality Function Deployment

Cost Metrics – Cost Benefit Analysis, Return on Investment, NPV, Pay Back Period and Cost Estimation

Cost of Quality and Cost of Poor Quality

Pareto Analysis and Deep Dive to select Priority Problems 

Business Case and Complex Charter 

Re-Cap of Swim Lane, SIPOC, Value Stream Mapping and other mapping tools 

5 W 2 H

Measure- 

Descriptive and Inferential Statistics

Statistics Vs. Parameter

Descriptive Graphical Representation- Frequency Distribution, Box Plot, Stem and Leaf Diagram and More

MINI TAB- Re-Cap of all the Statistics taught so far in White, Yellow and Green Belt on Minitab (Measure of Central Tendency, Measure of Dispersion, Box Plot, Histogram, Pareto, Scatter Diagram, Variance, Standard Deviation, Process Capability, X Bar R and X Bar S Charts)

Practical Exercises for the trainees to get accustomed to Minitab

Central Limit Theorem and Probability

Detailed SIPOC, y=f(x), Inputs Vs. Output, Cause & Effect Matrix & Fishbone Diagram

Funneling Effect (Numerous X to Critical X)

Validation Method and Data Collection Planning 

Quick Wins

Continuous Vs. Discrete Variable

Sampling

Data re-cap

Central Limit Theorem

FMEA

Control Plan

Cause and Effect Matrix 

Measurement Systems and Analysis- Bias, Stability and Linearity,

Gauge R&R,

Analyze- 

Probability

Normality Test

Sampling for Continuous Data

Hypothesis testing 

Basics- Null, Alternate CI, Risk

Types of Error, Type I and Type II

Z Test, Mean Test, One Sample Two Tail Test, One Sample One Tail,  T Test,  Two Sample T Test

ANOVA

Correlation

Regression

Residual Analysis

Design of Experiments

Specification Limit Vs. Control Limit

Improve- 

Design of Experiments

Control – 

Control Charts -N, p, np, c and u charts

Control Plan