Course Overview
This intensive course prepares the participant to better equip and prepare forQuality management through Six Sigma methodology and implementation. Six Sigma Black belt is responsible for projects Quality through tested techniques and detailed analysis. They not only educate about the concepts, tools and tips, but guide Green belts by mentoring. The objective of this course is to create Quality professionals who can carry complete execution on their shoulders and encounter any risks by anticipating and mitigating through early signs of defect or detect variances.
This course is a well-thought and comprehensively structured mix of theory and supporting practical simulating scenarios faced in the real-time complex situations. It greatly boosts the knowledge and equips every participant to step in to the global market with a profile thats packed with academic credentials, confidence and panache.
Define & Measure (Introduction to Statistical Analysis & Minitab)
Quality Functional Deployments & Kano Analysis
Statistical Concepts
Introduction to Minitab I & Data Manipulation
Introduction to Minitab II
Linking customer requirements to CTQs
Review the basic statistical concepts
Review the Minitab Environment
Using Minitab for Analysis
Analyze (Analysis of Variance)
ANOVA
SPAN
Lean Metrics, value, Value Stream Analysis, Flow and Pull
Measure (Measurement Systems Analysis)
Rational Sub grouping & Data Collection
Measurement Systems Analysis
Discrete Data Measurement & Application
Practical MSA
Stratify customers and determine what to measure
Minimize measurement error Statapult& GRR
Inspection Efficiency and Card drop Exercise
Exercises in Minitab and more Statapult
Analyze (Regression Analysis)
Introduction to Regression
Multiple Linear Regression
Logistic Linear Regression
Regression Issues
Measure (Sample Size and Confidence Intervals)
Focusing the Problem, Cause and Effect and FMEA
Determining Appropriate Business Measures
Sample Size & Confidence Intervals
Methods to focus the problem
What to measure?
Measurement essentials
Improve (Designs of Experiments)
Introduction to Designs of Experiments
2 by n Full Factorial Design of Experiments
Fractional Factorial Design of Experiments
Planning Designs
Analyze (Hypothesis Testing)
Hypothesis Testing Continuous Data
Hypothesis Testing Discrete Data
Hypothesis Testing Non Normal Data
Improve and Control (Selecting Solutions and Control Charting)
Creative Thinking
Solution Selection
Lean Solutions
Piloting Solutions
Control Chart Theory
Creating Control Charts
Specialty Control Charts
Improve and Control (Optimization of Solution)
Response Surface Analysis
Review and Close
Examination
Measure (Sample Size and Confidence Intervals)
Focusing the Problem, Cause and Effect and FMEA
Determining Appropriate Business Measures
Sample Size & Confidence Intervals
Methods to focus the problem
What to measure?
Measurement essentials