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Description of  Lean Six Sigma Black Belt by GreyCampus

Published 12/2023 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 549.39 MB | Duration: 1h 27m 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. Analyzea?? Analyze Phase - Overviewa?? Patterns of Variationa?? Inferential Statisticsa?? Hypothesis Testinga?? Hypothesis Testing with Normal Dataa?? Hypothesis Testing with Non-normal Data6. Improvea?? Improve Overviewa?? Potential Solutions Generationa?? Lean Solutions/Toolsa?? Mistake-Proofinga?? Select the Best Solutiona?? Pilot Implementationa?? Simple Linear Regressiona?? Multiple Regression Analysis (MRA)a?? Designed Experiments or Design of Experiments (DOE)a?? Full Factorial Experimentsa?? 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.