Six Sigma Green Belt Certification Training

Learning Objectives: In this module, you will understand baselining the metric of Improvement, the types of data and Data Collection plan.

Topics: Process analysis & mapping, Identifying the detailed AS-IS processes, Understanding the tools to create a process map, Dos & Don’ts of process mapping, SIPOC, Understanding data, Types of data & characteristics, Basic statistics - Mean, Median, Mode, Standard deviation & Variation, Data collection techniques, Understanding data sampling and techniques, Defining a unit and evaluating DPU, DPO, DPMO, Computing process sigma for discrete & continuous data type.

Learning Objectives: In this module, you will understand the Data driven approach of analyzing data and use of various statistical techniques to infer results.

Topics: Data analysis techniques, Tools used for data analysis, Pareto Chart, Fishbone, FMEA.

Statistical hypothesis to validate the assumption ( Assumption based on P-value), Understanding Type I and Type II error, Analysis of Means using variation (ANOVA), Analyzing the statistical significance of 2 data sets using Correlation, Usage of Regression models to predict & estimate Y’s with X inputs.

Interpreting Chi-Square to determine statistical significance.

Learning Objectives: Various improvement methodologies to improve the process, prioritizing Root causes and shortlisting solutions.

Topics: Understanding Value, Evaluating Value added & Non value added activities using Value stream mapping, 5S ( Set, Sort, Straighten, Strengthen, Stabilize),Muda, Driving Kaizen events

Learning Objectives: In this module, you will learn to develop control mechanism. You will also learn about tools like Control Charts, which will be used depending on the type of data and sustenance measures.

Topics: Establishing Control Plans to sustain gains, Introduction to Statistical process Control (SPC) Charts, Identifying special and common causes, etc. ,Selection and application of right control charts, Application of the following types of Control charts: X bar R, X bar S, individual and moving range (ImR/ Xmr),NP,P,C and U.

Analysis of Control Charts- Interpret control charts results, common & special causes using rules for determining statistical control. Controlling the changes using poka yoke (mistake proofing), Analyzing new process capability and defining control plans