Lean Six Sigma Black Belt by GreyCampus

LSSBB

What you'll learn

Understand the objective of Lean Six Sigma and its application in process improvement.

Gain detailed knowledge of DMAIC: Define, Measure, Analyze, Improve, and Control phases in Lean Six Sigma projects.

Apply DMAIC effectively in Lean Six Sigma projects to achieve process improvements.

Identify opportunities for Lean Six Sigma projects and apply data analysis techniques to make informed decisions.

Learn hypothesis testing and its application in making data-driven inferences for process improvement.

Acquire expertise in root cause analysis and the application of various tools and techniques in Lean Six Sigma projects at an advanced level of proficiency.

Requirements

There is no mandatory eligibility requirement to sit for the LSSBB certification exam. Prior knowledge of statistics is recommended, but the required knowledge of statistics is covered in this course. Additionally, knowledge of Minitab will be beneficial but not mandatory to execute example scenarios.

Description

Lean Six Sigma Black Belt Training & CertificationBlack belt level training geared towards enabling advanced expertise in Lean Six Sigma. The course is accredited by IASSC*, and aligned to IASSC's Lean Six Sigma Black Belt Body of Knowledge.1. Course OverviewLearning ObjectivesIASSC LSSBB CertificationCourse Contents2. FoundationLean Six Sigma IntroductionSix Sigma OverviewDMAIC MethodologyLean Enterprise3. DefineDefine Phase OverviewVoice of Customer (VOC)Critical to Quality (CTQ)SIPOCStakeholder AnalysisProject Charter4. MeasureMeasure Phase OverviewAs-is Process Review (Process Definition)Data Collection and Analysis (Basic Statistics)Data Accuracy and Precision (Measurement System Analysis-MSA)Process Capability and Stability5. Analyze• Analyze Phase - Overview• Patterns of Variation• Inferential Statistics• Hypothesis Testing• Hypothesis Testing with Normal Data• Hypothesis Testing with Non-normal Data6. Improve• Improve Overview• Potential Solutions Generation• Lean Solutions/Tools• Mistake-Proofing• Select the Best Solution• Pilot Implementation• Simple Linear Regression• Multiple Regression Analysis (MRA)• Designed Experiments or Design of Experiments (DOE)• Full Factorial Experiments• Fractional Factorial Experiments7. ControlControl OverviewLean ControlsStatistical Process ControlSix Sigma Control planSimulated Exams2 simulated exams to help you experience the type of questions you would actually get in your IASSC certification exam. These are available in the Online Learning Platform and include fully worked-out solutions.

Overview

Section 1: Course Overview

Lecture 1 Lean Six Sigma and Process Issues

Lecture 2 Learning Objectives

Lecture 3 Course Contents

Section 2: Foundation

Lecture 4 Lean Six Sigma Introduction

Lecture 5 Six Sigma Overview

Lecture 6 DMAIC Methodology

Lecture 7 Lean Enterprise

Section 3: Define

Lecture 8 Define Phase Overview

Lecture 9 Voice of Customer (VOC)

Lecture 10 Critical to Quality (CTQ)

Lecture 11 SIPOC

Lecture 12 Stakeholder Analysis

Lecture 13 Project Charter

Lecture 14 Process Map Overview-1

Section 4: Measure

Lecture 15 Value Stream Mapping (VSM)

Lecture 16 Measure Phase Overview

Lecture 17 VSM - Creation

Lecture 18 As-is Process Review (Process Definition)

Lecture 19 VSM Common Metrics

Lecture 20 Data Collection and Analysis(Basic Statistics)

Lecture 21 Value Add Flow Analysis 1

Lecture 22 Data Accuracy & Precision(Measurement System Analysis-MSA)

Lecture 23 Process Capability & Stability

Section 5: Analyze

Lecture 24 Analyze Phase - Overview

Lecture 25 Patterns of Variation

Lecture 26 Inferential Statistics

Lecture 27 Hypothesis Testing

Lecture 28 Hypothesis Testing with Normal Data

Lecture 29 Example-Create Factorial Design

Lecture 30 Hypothesis Testing with Non-normal Data

Lecture 31 Example-Analyze Factorial Design-V1

Lecture 32 Example-Analyze Factorial Design-V2

Section 6: Improve

Lecture 33 Example-Analyze Factorial Design-V3

Lecture 34 Improve Overview

Lecture 35 Example-Analyze Factorial Design-V4

Lecture 36 Potential Solutions Generation

Lecture 37 Example-Factorial Plots

Lecture 38 Lean Solutions/Tools

Lecture 39 Example-Cube Plot

Lecture 40 Mistake-Proofing

Lecture 41 Example-Surface Plot

Lecture 42 Select the Best Solution

Lecture 43 Example-Contour Plot

Lecture 44 Pilot Implementation

Lecture 45 Example-Contour Plot of Cost

Lecture 46 Simple Linear Regression

Lecture 47 Example-Response Optimizer

Lecture 48 Multiple Regression Analysis (MRA)

Lecture 49 Fractional Factorial Designs

Lecture 50 Designed Experiments or Design of Experiments (DOE)

Lecture 51 Confounding effect

Lecture 52 Full Factorial Experiments

Lecture 53 Experimental Resolutions

Lecture 54 IP_EoM Summary

Section 7: Control

Lecture 55 Control Overview

Lecture 56 Lean Controls

Lecture 57 Statistical Process Control

Lecture 58 Six Sigma Control plan

Section 8: Value Adds

Lecture 59 IASSC Reference Document

Section 9: Class Deck

Lecture 60 Define Phase

Lecture 61 Measure Phase

Lecture 62 Analyze Phase

Lecture 63 Improve Phase

Lecture 64 Control Phase

Section 10: Simulated Exams

People working in the Quality Management domain. Ex- Quality System Managers, Engineers, Supervisors, Analysts, Auditors, Green Belts, Yellow Belts etc.