This training is jointly organized by BASIS Institute of Technology & Management(BITM) & Hypertag Solutions Ltd

Training will be held in Hypertag Solutions Ltd.

Course Curriculum

Define Phase

The Basics of Six Sigma

Meanings of Six Sigma

Difference between Lean & Six Sigma

General History of Six Sigma & Continuous Improvement

Deliverables of a Six Sigma Six Sigma Project

The Problem Solving Strategy Y = f(x)

Voice of the Customer, Business and Employee

Six Sigma Roles & Responsibilities

 

The Fundamentals of Six Sigma

 Defining a Process

 Critical to Quality Characteristics (CTQ’s)

 Cost of Poor Quality (COPQ)

 Pareto Analysis (80:20 rule)

 Basic Six Sigma Metrics - including DPU, DPMO, FTY, RTY Cycle Time

 

Selecting Six Sigma Six Sigma Projects

 Building a Business Case & Project Charter

 Developing Project Metrics

 Financial Evaluation & Benefits Capture

 

 

Basic Lean Tools

 The Seven Elements of Waste - Overproduction, Correction, Inventory, Motion, Over processing, Conveyance, Waiting.

5S - Straighten, Shine, Standardize, Self-Discipline, Sort

 Process Mapping, SIPOC, Value Stream Map

 

Measure Phase

 Process Definition

Cause & Effect / Fishbone Diagrams

 X-Y Diagram

 Failure Modes & Effects Analysis (FMEA)

 

Six Sigma Statistics

 Basic Statistics

 Descriptive Statistics

Normal Distributions & Normality

Graphical Analysis

Sample Size Calculation

Sample Size for Continuous Y

Sample Size for Discrete Y

Sampling Methodology

Population based approach

Process based approach

Measurement System Analysis

 Precision & Accuracy

 Bias, Linearity & Stability

 Gage Repeatability & Reproducibility

 Variable & Attribute MSA

 

Process Capability

Capability Analysis

Concept of Stability

 Attribute & Discrete Capability

 Monitoring Techniques

Analyze Phase

 Patterns of Variation

 Multi-Vari Analysis

Classes of Distributions

 Inferential Statistics

 Understanding Inference

 Sampling Techniques & Uses

 Central Limit Theorem

 Hypothesis Testing

 General Concepts & Goals of Hypothesis Testing

 Significance; Practical vs. Statistical

 Risk; Alpha & Beta

 Types of Hypothesis Test

Hypothesis Testing with Normal Data

 1 & 2 sample t-tests

 1 sample variance

 One Way ANOVA. Including Tests of Equal Variance, Normality Testing and Sample Size calculation, performing tests and interpreting results.

Improve Phase

 Simple Linear Regression

 Correlation

 Regression Equations

 Residuals Analysis

Multiple Regression Analysis

 Non- Linear Regression

 Multiple Linear Regression

 Confidence & Prediction Intervals

 Residuals Analysis

 Data Transformation, Box Cox

Improvement Validation & Cost Benefit Analysis

Pre & Post Analysis

Stakeholder Approval – Full Scale Implementation

Control Phase

Six Sigma Control Plan

Control Methods for 5S

Kanban

Poka-Yoke (Mistake Proofing)

Statistical Process Control (SPC)

 Data Collection for SPC

 I-MR Chart

Xbar-R Chart

 U Chart

 P Chart

C Chart

NP Chart

 X-S chart

 Control Chart Anatomy

 

Curriculum