Certification focuses on testing students on their comprehensive understanding of the various Six Sigma tools and techniques. ( Online- 60 hrs, detail will be declared soon )
Overview of Six Sigma Methodology-
Identification, Prioritization and Selection of Improvement opportunities, Roles and responsibilities in Six Sigma implementation.
Overview of Six Sigma Project execution (DMAIC)(Define- Measure- Analyze- Improve & Control) and Gate Review Questionnaire.
Development of Project Team and Charter, Define and Map Processes to be improved(SIPOC-Supplier, Input, Process, Output, Customer), Identification of Critical To Customer/Critical To Business(CTQ/CTB) characteristics, Concept of tree diagram, Voice of Customer.
Types of Data, Statistical distributions-
Binomial, Poisson and Normal; Prioritization Matrix, FMEA and their use in Data Collection Planning. Introduction to various software packages for data display & analysis like Excel, Minitab, JMP etc.-understanding in usage & interpretation of output along with each topic, Measurement System Evaluation for measurable (Gauge R&R) as well as for attribute data (Kappa Value and Confidence interval for agreement with expert); Understanding variation-Special causes vs. Common causes (like Dot Plots, Box Plots, Histogram and Control Charts),
Stratification methods (like Pareto, Bar Diagrams, Stratified Dot Plot, Stratified Scatter Plot, Box Plot, Multi Vari Charts etc), Normality test of a data, and concept of confidence interval; Evaluation of Process Capability for Data, Concept of Short Term, Long Term Process Capability and assessment of Sigma level.
Tools & techniques-
Identification of Value-Added and Non-Value-Added activities, Value Stream Mapping (VSM) (use of lean concept), Organizing for potential causes using Cause-& Effect diagram, FMEA& Tree Diagram; Verification/ validation of causes using work place investigation (GEMBA), Concept of correlation and Regression and use of the same in validating causes; Concept of Test of Hypothesis like 2 Sample t, ChiSquare, ANOVA etc and use of the same invalidating the causes; Sample Size determination for a given confidence level; Concept of Multiple Regression and Logistic regression and use of the same in validating the causes; Concepts of Exploratory Data Analysis.