Sale!

Lean Six Sigma Green Belt Program-LUANDA

$599.00 $549.00

Lean Six Sigma Green Belt course focuses on providing students with an understanding of the various Six Sigma and Lean tools and techniques useful to improve the production process and minimize defects in the end product with a greater focus on the practical implementation of these tool and techniques in the organization.

The course integrates Lean and DMAIC methodologies as defined by IASSC using case studies and examples which help you implement,perform and interpret and apply Lean Six Sigma at high level of proficiency

Mode Of Learning: Instructor Led
Duration: 4 days
Dates: 15th, 16th  December

 

Categories: ,

Description

Six sigma is a set of techniques that follows a methodological approach for bringing process improvements by aligning organizational goals. Organizations worldwide seek experts who understand the strategic objectives of businesses, critical requirements and operational goals to drive improvement.

The Lean Six Sigma Green Belt Expert training course is designed to provide knowledge and skills to become a successful Process excellence expert. It starts with the fundamental concepts of Understanding VOC, Converting them into potential projects, Base-lining measure to advance topics of Analyzing data, Improving process/ metric and ensure consistency.

Lean Six Sigma Green Belt course focuses on providing students with an understanding of the various Six Sigma and Lean tools and techniques useful to improve the production process and minimize defects in the end product with a greater focus on the practical implementation of these tool and techniques in the organization.

The course integrates Lean and DMAIC methodologies as defined by IASSC using case studies and examples which help you implement,perform and interpret and apply Lean Six Sigma at high level of proficiency

 

COURSE OVERVIEW

 What is included

• Two Days (16 hours) intensive classroom training• Contemporary case study based teaching and study materials
• One to one interaction with the trainer
• 1 year E-Learning Access including videos,practice test & pdfs
• Three simulated exams
• Networking (opportunity to meet professional from other fields)
• Certificate Of Participation

COURSE CONTENTS

1.0 DEFINE PHASE

1.1 THE BASICS OF SIX SIGMA

1.1.1 Meanings of Six Sigma

1.1.2 General History of Six Sigma & Continuous Im-provement

1.1.3 Deliverables of a Lean Six Sigma Project

1.1.4 The Problem Solving Strategy Y = f(x)

1.1.5 Voice of the Customer, Business and Employee

1.1.6 Six Sigma Roles & Responsibilities

1.2 THE FUNDAMENTALS OF SIX SIGMA

1.2.1 Defining a Process

1.2.2 Critical to Quality Characteristics (CTQ’s)

1.2.3 Cost of Poor Quality (COPQ)

1.2.4 Pareto Analysis (80:20 rule)

1.2.5 Basic Six Sigma Metrics

  1. including DPU, DPMO, FTY, RTY Cycle Time, deriving these metrics

1.3 SELECTING LEAN SIX SIGMA PROJECTS

1.3.1 Building a Business Case & Project Charter

1.3.2 Developing Project Metrics

1.3.3 Financial Evaluation & Benefits Capture

1.4 THE LEAN ENTERPRISE

1.4.1 Understanding Lean

1.4.2 The History of Lean

1.4.3 Lean & Six Sigma

1.4.4 The Seven Elements of Waste

  1. Overproduction, Correction, Inventory, Motion, Overprocessing, Conveyance, Waiting.

1.4.5 5S

  1. Straighten, Shine, Standardize, Self-Discipline & Sort

2.0 MEASURE PHASE

2.1 PROCESS DEFINITION

2.1.1 Cause & Effect / Fishbone Diagrams

2.1.2 Process Mapping, SIPOC, Value Stream Map

2.1.3 X-Y Diagram

2.1.4 Failure Modes & Effects Analysis (FMEA)

2.2 SIX SIGMA STATISTICS

2.2.1 Basic Statistics

2.2.2 Descriptive Statistics

2.2.3 Normal Distributions & Normality

2.2.4 Graphical Analysis

2.3 MEASUREMENT SYSTEM ANALYSIS

2.3.1 Precision & Accuracy

2.3.2 Bias, Linearity & Stability

2.3.3 Gage Repeatability & Reproducibility

2.3.4 Variable & Attribute MSA

2.4 PROCESS CAPABILITY

2.4.1 Capability Analysis

2.4.2 Concept of Stability

2.4.3 Attribute & Discrete Capability

2.4.4 Monitoring Techniques

3.0 ANALYZE PHASE

3.1 PATTERNS OF VARIATION

3.1.1 Multi-Vari Analysis

3.1.2 Classes of Distributions

3.2 INFERENTIAL STATISTICS

3.2.1 Understanding Inference

3.2.2 Sampling Techniques & Uses

3.2.3 Central Limit Theorem

3.3 HYPOTHESIS TESTING

3.3.1 General Concepts & Goals of Hypothesis Testing

3.3.2 Significance; Practical vs. Statistical

3.3.3 Risk; Alpha & Beta

3.3.4 Types of Hypothesis Test

3.4 HYPOTHESIS TESTING WITH NORMAL DATA

3.4.1 1 & 2 sample t-tests

3.4.2 1 sample variance

3.4.3 One Way ANOVA

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

3.5 HYPOTHESIS TESTING WITH NON-NORMAL DATA

3.5.1 Mann-Whitney

3.5.2 Kruskal-Wallis

3.5.3 Mood’s Median

3.5.4 Friedman

3.5.5 1 Sample Sign

3.5.6 1 Sample Wilcoxon

3.5.7 One and Two Sample Proportion

3.5.8 Chi-Squared (Contingency Tables)

  1. Including Tests of Equal Variance, Normality Test-ing and Sample Size calculation, performing tests and interpreting results.

4.0 IMPROVE PHASE

4.1 SIMPLE LINEAR REGRESSION

4.1.1 Correlation

4.1.2 Regression Equations

4.1.3 Residual Analysis 

4.2 MULTIPLE REGRESSION ANALYSIS

4.2.1 Non-Linear Regression

4.2.2 Multiple Linear Regression

4.2.3 Confidence & Prediction Intervals

4.2.4 Residual Analysis

4.2.5 Data Transformation, Box Cox

5.0 CONTROL PHASE

5.1 LEAN CONTROLS

5.1.1 Control Methods for 5S

5.1.2 Kanban

5.1.3 Poka-Yoke (Mistake Proofing)

5.2 STATISTICAL PROCESS CONTROL (SPC)

5.2.1 Data Collection for SPC

5.2.2 I-MR Chart

5.2.3 Xbar-R Chart

5.2.4 U Chart

5.2.5 P Chart

5.2.6 NP Chart

5.2.7 X-S chart

5.2.8 CumSum Chart

5.2.9 EWMA Chart

5.2.10 Control Chart Anatomy

5.3 SIX SIGMA CONTROL PLANS            

5.3.1 Cost Benefit Analysis

5.3.2 Elements of the Control Plan

5.3.3 Elements of the Response Plan

 

 

 

TARGET AUDIENCE

Professionals working in the manufacturing, telecom, pharmaceuticals, IT industries especially in Product & Quality Management. There is no formal prerequisite for this course.