ARLVET30 Coupon Code for 30% Discount

Lean Six Sigma Black Belt Certification Training Course in Columbus, OH, United States

Learners : 6513

With this Lean Six Sigma Black Belt training, you can be members of Certified Lean Six Sigma Black Belts group of 2000 professionals worldwide. This Six Sigma Black Belt certification, being the final stage of the Master's program, gives you knowledge in the execution of concepts such as Total Productive Maintenance (TPM), Six Sigma Define, Measure, Analyse, Improve and Control (DMAIC), and Lean, Design for Six Sigma (DFSS).

Course Images Download LSSBB Brochure

Our Promise Of Lean Six Sigma Black Belt Certification Training course

  • 48 hours of instructor-led training
  • 21 hours of high-quality e-learning content
  • 3 Lean Six Sigma Black Belt simulation exams
  • Course completion certificate IASSC Exam Voucher included (Except for India)
  • 35 PDUs offered & 6 chapter-end quizzes
  • Money Back Guarantee
Course Workshop Date Course Type Price (USD) Enroll
3 Months FREE Access to all our E-learning courses when you buy any course with us.
Group Discount upto 15 %

LEAN SIX SIGMA BLACK BELT TRAINING COURSE DESCRIPTION IN COLUMBUS, OH

The Lean Innovation Six Sigma Black belt program will cover the most contemporary process improvement practices adopted by leading organizations and proponents of Lean Six Sigma in service industry as well as engineering firms within the DMAIC (Define, Measure, Analyse, Improve, & Control), DFSS (Design for Six Sigma) and IDOV (Identify, Design, Optimize and Verify) frameworks.

LEAN SIX SIGMA BLACK BELT TRAINING COURSE AGENDA IN COLUMBUS, OH

With Lean Innovation Six Sigma Black belt program, Participants will be exposed to latest concepts such as (but not limited to):

  • Project management practices related to project selection, resource management, change management, financial management and other applicable areas
  • Data analytic tools and practices that are fast yet effective even in constrained environments where quantity and quality of data is an issue
  • Insights on how simple tools of Six Sigma, that are at times ignored by practitioners, that yield fast and effective results in the process improvement journey
  • Lean or Toyota Production System (TPS) insights that go beyond the introductory concepts related to types of waste and Value Stream Mapping (VSM). Some of these concepts have been lost over time in the translation of text from Japanese to English language
  • TRIZ or Theory of Inventive Problem Solving insights for accelerated thinking in generating sustainable and win-win solutions. These concepts will also be useful for those who wish to practice Design for Six Sigma (DFSS) at a later stage of their career
  • Insights on identifying value creation opportunities that are being adopted for product portfolio design by leading organizations such as Motorola, P&G amongst others
  • Systems thinking tools that reveal the core issues to be tackled in complex real world situations

LEAN SIX SIGMA BLACK BELT TRAINING COURSE PREREQUISITES IN COLUMBUS, OH

For attending the LSSBB program a participant must be LSSGB certified. However, senior professionals with more than 6 years of relevant experience can attend after their application has been scrutinized by QAI.

Our Learners Are

Our Learners
Our Learners
Our Learners
Our Learners
Our Learners
Our Learners
Our Learners
Our Learners
Our Learners

LEAN SIX SIGMA BLACK BELT TRAINING COURSE WHO SHOULD ATTEND IN COLUMBUS, OH

  • Senior Management (especially if the company intends to implement Lean Six Sigma)
  • Team Leaders
  • Software Professionals
  • Project Managers
  • Quality Assurance Engineers
  • Software Quality Assurance Team Members
  • Management Students

LEAN SIX SIGMA BLACK BELT TRAINING COURSE CURRICULUM IN COLUMBUS, OH

Section 00 - Six Sigma Black Belt

  • Welcome
  • Six Sigma Black Belt
  • Agenda
  • What is SSBB
  • Accreditation Institute
  • Target Audience
  • SSBB Exam Format
  • AR Learners LSSBB Course Offer
  • Thank You

Section 01 - Overview

  • Welcome
  • Overview
  • Agenda
  • Lesson 1 About LSSBB
  • Agenda
  • What is Six Sigma
  • Six Sigma Roles and Responsibilities
  • About SSBB
  • LSSBB Roles and Responsibilities
  • Summary
  • Lesson 2 Organizational Roadblocks
  • Agenda
  • Traditional Organization versus Customer Driven Organization
  • Types of Organizational Roadblocks
  • Types of Organizational Roadblocks(Contd.)
  • Types of Organizational Roadblocks(Contd.)
  • Types of Organizational Roadblocks(Contd.)
  • Types of Organizational Roadblocks(Contd.)
  • Types of Organizational Roadblocks(Contd.)
  • Types of Organizational Roadblocks(Contd.)
  • Change Resistance Curve
  • Change Resistance Curve(Contd.)
  • Change Resistance Curve(Contd.)
  • Common Resistance Points
  • Common Resistance Points(Contd.)
  • Overcoming Resistance Points
  • Force Field Analysis
  • Force Field Analysis(Contd.)
  • Force Field Analysis(Contd.)
  • Force Field Analysis(Contd.)
  • Summary
  • Lesson 3 Role of Communication and Selection Criteria in Black Belt
  • Agenda
  • Black Belt Role Summary
  • Black Belt Communication Expectations
  • Black Belt Selection Criteria
  • Summary
  • Lesson 4 Overview of Continuous Improvement
  • Agenda
  • Continual Improvement Process
  • Continuous versus Continual Improvement
  • Kaizen Continual Improvement
  • Kaizen Continual Improvement(Contd.)
  • Summary
  • Lesson 5 Lean An Overview
  • Agenda
  • What is Lean
  • History of Lean
  • Principles of Lean
  • Key Benefits of Implementing Lean
  • Key Benefits of Implementing Lean(Contd.)
  • Why Lean before Six Sigma
  • Summary
  • Lesson 6 Lean Concepts Explained
  • Agenda
  • Warusa Kagen
  • Warusa Kagen(Contd.)
  • 3Ms
  • 8 Types of Waste (TIMWOODS)
  • Mottainai
  • Hoshin Kanri
  • Hoshin Kanri(Contd.)
  • Hoshin Kanri(Contd.)
  • Takt Time
  • Takt Time(Contd.)
  • Cycle Time
  • Lead Time
  • Lead Time Assignment
  • Lead Time Assignment(Contd.)
  • Production Cycle Efficiency
  • Batch Size
  • Every Part Every Interval(EPEI)
  • EPEI(Contd.)
  • EPEI(Contd.)
  • EPEI Calculation Spreadsheet
  • Batch Size Assignment
  • Batch Size Assignment(Contd.)
  • Batch Size Assignment(Contd.)
  • Batch Size Assignment(Contd.)
  • Batch Size Assignment(Contd.)
  • Crew Size
  • Crew Size Assignment
  • Crew Size Assignment(Contd.)
  • Crew Size Assignment(Contd)
  • Standardized Working Progress(SWIP)
  • Summary
  • Lesson 7 Lean Tools Explained
  • Agenda
  • 5S
  • 5S(Contd.)
  • 5S Audit Worksheet
  • SMED
  • SMED(Contd.)
  • Heijunka
  • Heijunka An Example
  • Genchi Genbutsu
  • Value Stream Mapping(VSM)
  • VSM Symbols
  • Value Stream Mapping(Contd.)
  • Value Stream Mapping(Contd.)
  • Summary

Section 02 - DFSS, Pre-define and Define (DMAIC)

  • Welcome
  • Agenda
  • DFSS Pre Define and Define(DMAIC)
  • DFSS Design for Six Sigma and DMAIC versus DFSS
  • Agenda
  • Agenda(Contd.)
  • Design for Six Sigma(DFSS)
  • DFSS Approach to Problem Solving
  • DMAIC Approach to Problem Solving
  • DMAIC versus DFSS
  • DFSS Tools
  • Toll Gate Review
  • Benchmarking
  • MSA
  • VOC
  • Needs Vs Requirements
  • KJ Diagram
  • Quality Function Deployment(QFD)
  • Kano Model
  • Kano Model(Contd.)
  • Kano Model(Contd.)
  • HOQ
  • HOQ(Contd.)
  • HOQ(Contd.)
  • AHP
  • AHP(Contd.)
  • Pugh Matrix for Concept Selection
  • Pugh Matrix for Concept Selection(Contd.)
  • Sample Pugh Matrix
  • Monte Carlo Simulation
  • Design for X
  • Summary
  • Lesson 2 Pre Define Activities
  • Agenda
  • Prerequisites of a Six Sigma Project
  • Qualifications of a Six Sigma Project
  • Cornerstones of a Six Sigma Project
  • Six Sigma Deployment Cycle Plan
  • 10 Point Ongoing Project Evaluation
  • Project Prioritization Matrix
  • Project Prioritization Matrix(Contd.)
  • Enterprise Wide versus LOB View
  • Enterprise Wide Roles and Responsibilities
  • NPV(Net Present Value)
  • Internal Rate of Return(IRR)
  • NPV and IRR An Example
  • NPV and IRR An Example(Contd.)
  • Summary
  • Lesson 3 Define
  • Agenda
  • Define Key Objectives
  • Voice of Customer
  • Voice of Business
  • Voice of Process
  • VOC VOB and VOP
  • Kano Model
  • Assignment
  • Translation to Project Y
  • Quality Function Deployment
  • Quality Function Deployment(Contd.)
  • Quality Function Deployment An Example
  • Process Map
  • Y Baseline Performance
  • Y Baseline Performance(Contd.)
  • SIPOC
  • Project Charter
  • The Problem Statement and the Goal Statement
  • RACI Matrix
  • Business Metrics
  • Business Metrics(Contd.)
  • Project Deliverables
  • Project Scheduling
  • Team Selection
  • Define Roles and Responsibilities
  • Define Tools Summary
  • Lesson 3 Summary

Section 03 - Measure

  • Measure
  • Introduction to MEASURE
  • Agenda
  • Pre Measure Considerations and Tools
  • Agenda
  • Define Phase Toll Gate Review
  • DFMEA
  • DFMEA(Contd.)
  • DFMEA(Contd.)
  • DFMEA(Contd.)
  • DFMEA(Contd.)
  • Cause and Effect Matrix(CE Matrix)
  • Cause and Effect Matrix(Contd.)
  • Cause and Effect Matrix(CE Matrix)(Contd.)
  • Cause and Effect Matrix(CE Matrix)(Contd.)
  • Cause and Effect Matrix(CE Matrix)(Contd.)
  • Cause and Effect Matrix(Contd.)
  • Summary
  • Types of Data and Measurement Scales
  • Agenda
  • Objectives of Measure Phase
  • What is a Process
  • Flowcharts
  • SIPOC
  • SIPOC(Contd.)
  • SIPOC(Contd.)
  • Metrics
  • Measurement Scales
  • Measurement Scales(Contd.)
  • Measurement Scales(Contd.)
  • Types of Data
  • Types of Data(Contd.)
  • Summary
  • Central Tendency and Dispersion
  • Agenda
  • Central Tendency and Dispersion Introduction
  • Mean
  • Mean(Contd.)
  • Median
  • Mode
  • Range
  • Variance
  • Standard Deviation
  • Mean Deviation
  • Summary
  • Measurement System Analysis
  • Agenda
  • Purpose of Measurement System Analysis
  • Measurement System Errors
  • Measurement System Errors(Contd.)
  • Measurement System Errors(Contd.)
  • Properties of Good Measurement Systems
  • Measurement System Errors Illustrated
  • Measurement System Discrimination
  • Bias
  • Bias(Contd.)
  • Measurement System Analysis Process Flow
  • Part Variation
  • Measurement System Analysis Formulas
  • Measurement Systems Analysis Example
  • Measurement Systems Analysis Example(Contd.)
  • Measurement Systems Analysis Graphs
  • Measurement Systems Analysis Graphs(Contd.)
  • Measurement Systems Analysis Graphs(Contd.)
  • Assignment
  • Attribute RR
  • Attribute RR(Contd.)
  • Attribute RR(Contd.)
  • Attribute RR(Contd.)
  • Attribute RR(Contd.)
  • Attribute RR(Contd.)
  • Attribute RR(Contd.)
  • Attribute RR(Contd.)
  • Attribute RR(Contd.)
  • Attribute RR(Contd.)
  • When to Do Measurement System Analysis
  • Data Collection Plan
  • Data Collection Plan Template and Example
  • Summary
  • Stability Conditions
  • Agenda
  • Controlled Process and Variation
  • Special Causes of Variation
  • Common Causes of Variation
  • Common Causes of Variation(Contd.)
  • Stability Introduction and SPC
  • Stability Check with Minitab
  • Stability Check with Minitab(Contd.)
  • Stability Check with Minitab(Contd.)
  • Stability Check with Minitab(Contd.)
  • Stability Check using Run Charts
  • Stability Conditions
  • Central Limit Theorem
  • Summary
  • Capability Metrics
  • Agenda
  • Process Capability Pre Considerations
  • Process Capability Pre Considerations(Contd.)
  • Process Capability Pre Considerations(Contd.)
  • Process Capability Pre Considerations(Contd.)
  • Process Capability Pre Considerations(Contd.)
  • Process Capability Pre Considerations(Contd.)
  • Process Capability Pre Considerations(Contd.)
  • Process Capability Pre Considerations(Contd.)
  • Process Capability Pre Considerations(Contd.)
  • Process Capability Indices for Continuous Data
  • Process Capability Indices for Continuous Data(Contd.)
  • Process Capability Indices for Continuous Data(Contd.)
  • Process Capability Indices Interpretation
  • Process Capability for Discrete Data
  • Process Capability for Discrete Data(Contd.)
  • Process Capability for Discrete Data(Contd.)
  • Non Normal Capability Analysis
  • Non Normal Capability Analysis(Contd.)
  • Non Normal Capability Analysis(Contd.)
  • Non Normal Capability Analysis(Contd.)
  • Non Normal Capability Analysis(Contd.)
  • Non Normal Capability Analysis(Contd.)
  • Assignment
  • Summary
  • Variations Variability Capability and Process Conditions
  • Agenda
  • Variations and Variability
  • Variations and Variability(Contd.)
  • Variations and Variability(Contd.)
  • Capability and Process Conditions
  • Summary
  • Data Distributions
  • Agenda
  • Permutations and Combinations
  • Permutations and Combinations(Contd.)
  • Frequency and Cumulative Distributions
  • Binomial Distribution
  • Binomial Distribution(Contd.)
  • Binomial Distribution(Contd.)
  • Binomial Distribution(Contd.)
  • Poisson Distribution
  • Poisson Distribution(Contd.)
  • Poisson Distribution(Contd.)
  • Normal Distribution
  • Normal Distribution(Contd.)
  • Exponential Distribution
  • Exponential Distribution
  • Summary
  • Sigma Shift Mean Shift and Reducing Variations
  • Agenda
  • Sigma Shift
  • Mean Shift or Reducing Variations
  • Mean Shift or Reducing Variations(Contd.)
  • Baseline Data
  • Summary
  • Measure Phase Summary
  • Measure Activity Summary
  • Measure Tools Summary

Section 04 - Analyze

  • Welcome
  • Analyze
  • Agenda
  • Lesson 1 Pre Analyze Considerations
  • Agenda
  • Analyze Phase Introduction
  • Pre Analyze Considerations
  • Pre Analyze Considerations(Contd.)
  • Objectives of Analyze
  • Visually Displaying Data
  • Summary
  • Lesson 2 Value Stream Analysis
  • Agenda
  • Value Waste and NVA Activities
  • What is a Value Stream
  • Value Stream Example
  • Value Stream Analysis Muda
  • Value Stream Analysis Muda(Contd.)
  • Value Stream Map
  • Value Stream Map(Contd.)
  • Spaghetti Charts
  • Spaghetti Chart As Is
  • Spaghetti Chart Should Be
  • Spaghetti Charts(Contd.)
  • Summary
  • Lesson 3 Sources of Variation
  • Agenda
  • Sources of Variation
  • Sources of Variation(Contd.)
  • Cause and Effect Diagram
  • Cause and Effect Diagram(Contd.)
  • Cause and Effect Diagram(Contd.)
  • Cause and Effect Diagram(Contd.)
  • Affinity Diagram
  • Box Plot
  • Box Plot(Contd.)
  • Box Plot(Contd.)
  • Box Plot(Contd.)
  • Box Plot(Contd.)
  • Summary
  • Lesson 4 Regression
  • Agenda
  • Objectives of Regression Analysis
  • Concepts of Regression Analysis
  • Concepts of Regression Analysis(Contd.)
  • Simple Linear Regression
  • Simple Linear Regression(Contd.)
  • Simple Linear Regression(Contd.)
  • Simple Linear Regression(Contd.)
  • Simple Linear Regression(Contd.)
  • Simple Linear Regression(Contd.)
  • Multiple Linear Regression
  • Multiple Linear Regression(Contd.)
  • Multiple Linear Regression(Contd.)
  • Multiple Linear Regression(Contd.)
  • Multiple Linear Regression(Contd.)
  • Multiple Linear Regression(Contd.)
  • Multiple Linear Regression(Contd.)
  • Multiple Linear Regression(Contd.)
  • Multiple Linear Regression(Contd.)
  • Best Subsets Regression and Stepwise Regression
  • Summary
  • Lesson 5 Confidence Intervals
  • Agenda
  • Concepts of Confidence Intervals and Confidence Intervals Testing
  • Concepts of Confidence Intervals and Confidence Intervals Testing(Contd.)
  • Concepts of Confidence Intervals and Confidence Intervals Testing(Contd.)
  • Concepts of Confidence Intervals and Confidence Intervals Testing(Contd.)
  • Confidence Intervals for Difference between Two Means
  • Confidence Intervals Working
  • Confidence Intervals Working(Contd.)
  • Confidence Intervals Impactors
  • Chi Square Confidence Intervals for Variances
  • Chi-Square Confidence Intervals for Variances(Contd.)
  • Z Confidence Intervals for Proportions
  • Chi Square and Probability
  • T Distribution Confidence Intervals
  • Summary
  • Lesson 5 Parametric Hypothesis Testing
  • Agenda
  • Agenda(Contd.)
  • Hypothesis Testing Objective
  • Hypothesis Testing Concepts
  • Null and Alternate Hypothesis
  • Type 1 Error
  • Type II Error
  • Significance Level (?)
  • Significance Level (?) (Contd.)
  • Type II Error (Contd.)
  • ? and Power
  • P Value, and Acceptance and Rejection Conditions
  • Sample Size Determination for Tests
  • 1 Sample z Test
  • 1 Sample z Test(Contd.)
  • 1 Sample z Test(Contd.)
  • 2 Sample z test
  • f Test of Equality of Variances
  • 1 Sample t Test
  • 1 Sample t Test(Contd.)
  • 2 Sample t Test
  • 2 Sample t Test
  • 2 Sample t Test
  • Paired t Test
  • Paired t Test(Contd.)
  • Paired t Test Interpretation
  • Paired t Test(Contd.)
  • Paired t Test(Contd.)
  • ANOVA
  • One Way ANOVA
  • Two Way ANOVA with Replication
  • Two Way ANOVA with Replication(Contd.)
  • Two Way ANOVA with Replication(Contd.)
  • Two Way ANOVA with Replication(Contd.)
  • Summary
  • Lesson 7 Nonparametric Hypothesis Testing
  • Agenda
  • Nonparametric Testing Conditions
  • Mann Whitney Test
  • Mann Whitney Test(Contd.)
  • 1 Sample Sign
  • Wilcoxon Sign Rank Test
  • Kruskal Wallis
  • Moods Median
  • Friedman ANOVA
  • Friedman ANOVA(Contd.)
  • Summary
  • Lesson 8 Analyze Additionals Categorical Data and Current Reality Tree
  • Agenda
  • Categorical Data Analysis
  • Categorical Data Analysis(Contd.)
  • Categorical Data Analysis(Contd.)
  • Categorical Data Analysis(Contd.)
  • Current Reality Tree
  • Current Reality Tree(Contd.)
  • Summary
  • Activity Summary Analyze
  • Tools Summary Analyze

Section 05 - Improve

  • Welcome
  • Section V Improve
  • Agenda
  • Section V Lesson 1
  • Agenda
  • Pre Improve Considerations
  • Model Adequacy Checking
  • Model Adequacy Checking(Contd.)
  • Model Adequacy Checking(Contd.)
  • Multi Vari Charts
  • 7M Tools
  • Activity Network Diagram
  • Point and Interval Estimation
  • Porter s Five Forces
  • Porter s Five Forces (Contd.)
  • Pugh Analysis
  • Lean 5S
  • Summary
  • Section V Lesson 2 Design of Experiments Theory
  • Agenda
  • Introduction to DOE
  • Introduction to DOE(Contd.)
  • Introduction to DOE(Contd.)
  • Introduction to DOE(Contd.)
  • Introduction to DOE(Contd.)
  • Introduction to DOE(Contd.)
  • Types of Designed Experiments
  • Main and Interaction Effects
  • Main and Interaction Effects(Contd.)
  • Main and Interaction Effects(Contd.)
  • Main and Interaction Effects(Contd.)
  • Replication
  • Randomization
  • Blocking
  • Confounding
  • Coding and other DOE Terms
  • Sum of Squares Analysis
  • Sum of Squares Analysis(Contd.)
  • Sum of Squares Analysis(Contd.)
  • Sum of Squares Analysis(Contd.)
  • Sum of Squares Analysis(Contd.)
  • Sum of Squares Analysis(Contd.)
  • Sum of Squares Analysis(Contd.)
  • Summary
  • Section V Lesson 3 Design of Experiments Practice 32
  • Agenda
  • Introduction to 2 Factor Factorial Design
  • Introduction to 2 Factor Factorial Design(Contd.)
  • Introduction to 2 Factor Factorial Design(Contd.)
  • 2? Design
  • 2? Design(Contd.)
  • 2? Design(Contd.)
  • 2? Design(Contd.)
  • 2? Design(Contd.)
  • 2? Design(Contd.)
  • 2? Design(Contd.)
  • 2? Design(Contd.)
  • 2? Design(Contd.)
  • 2? Design(Contd.)
  • 2? Design(Contd.)
  • 2? Design(Contd.)
  • 2? Design(Contd.)
  • 2? Design(Contd.)
  • 2? Design(Contd.)
  • 2? Design(Contd.)
  • 2? Design Summary
  • General 2k Design
  • General 2k Design(Contd.)
  • General 2k Design(Contd.)
  • General 2k Design(Contd.)
  • General 2k Design(Contd.)
  • General 2k Design(Contd.)
  • General 2k Design(Contd.)
  • General 2k Design(Contd.)
  • General 2k Design(Contd.)
  • General 2k Design(Contd.)
  • Single Replicate of 2k Design
  • Half Fractional 2k-1 Design
  • Half Fractional 2k-1 Design(Contd.)
  • Half Fractional 2k-1 Design(Contd.)
  • Half Fractional 2k-1 Design(Contd.)
  • Half Fractional 2k-1 Design(Contd.)
  • Half Fractional 2k-1 Design(Contd.)
  • Half Fractional 2k-1 Design(Contd.)
  • Quarter Fractional 2k-2 Design
  • Quarter Fractional 2k-2 Design(Contd.)
  • Quarter Fractional 2k-2 Design(Contd.)
  • Quarter Fractional 2k-2 Design(Contd.)
  • 3k Factorial Design
  • 3k Factorial Design (Contd.)
  • Response Surface Designs
  • Response Surface Designs(Contd.)
  • Response Surface Designs(Contd.)
  • Response Surface Designs(Contd.)
  • Response Surface Designs(Contd.)
  • Response Surface Designs(Contd.)
  • Response Surface Designs(Contd.)
  • Response Surface Designs(Contd.)
  • Response Surface Designs(Contd.)
  • Nested Designs
  • Split Plot Designs Introduction
  • Taguchi's Designs
  • Taguchi's Designs (Contd.)
  • Taguchi's L4 Design
  • Taguchi's L4 Design Graphs
  • Taguchi's L8 Design
  • Taguchi's L8 Design(Contd.)
  • Taguchi's L8 Design(Contd.)
  • Taguchi's L8 Design(Contd.)
  • Plackett Burman's Design
  • Plackett Burman's Designs(Contd.)
  • Quality Function Deployment(House of Quality)
  • Summary
  • Section V Lesson 4 Brainstorming Solutions Prioritization and Cost Benefit Analysis
  • Agenda
  • Brainstorming
  • Multi Voting
  • Brainstorming Prioritization and Cost Benefit Analysis
  • Brainstorming Prioritization and Cost Benefit Analysis(Contd.)
  • Brainstorming Prioritization and Cost Benefit Analysis(Contd.)
  • Brainstorming Prioritization and Cost Benefit Analysis(Contd.)
  • Brainstorming Prioritization and Cost Benefit Analysis(Contd.)
  • Brainstorming Prioritization and Cost Benefit Analysis(Contd.)
  • Brainstorming Prioritization and Cost Benefit Analysis(Contd.)
  • Poka Yoke
  • Summary
  • Section V Lesson 5 Piloting Validating and FMEA
  • Agenda
  • Pilot Solutions
  • Piloting Tools
  • Piloting Tools (Contd.)
  • Paired t Test
  • Paired t Test(Contd.)
  • Paired t Test Interpretations
  • Paired t Test(Contd.)
  • Paired t Test(Contd.)
  • Improve Next Steps
  • Failure Mode Effects Analysis
  • Failure Mode Effects Analysis(Contd.)
  • Failure Mode Effects Analysis(Contd.)
  • Failure Mode Effects Analysis(Contd.)
  • Failure Mode Effects Analysis(Contd.)
  • Summary
  • Improve Activity Summary

Section 06 - Control

  • Welcome
  • Section VI Control
  • Agenda
  • SectionVI Lesson 1 Pre Control Considerations
  • Agenda
  • Pre Control Considerations
  • Assessing the Results of Process Improvement
  • Rational Subgrouping
  • Summary
  • Section VI Lesson 2 Variables and Attributes Control Charts
  • Agenda
  • Concepts of Variables Control Charts
  • Concepts of Variables Control Charts(Contd.)
  • Concepts of Variables Control Charts (Contd.)
  • Concepts of Variables Control Charts (Contd.)
  • Concepts of Variables Control Charts (Contd.)
  • Variables Control Charts 43
  • Variables Control Charts(Contd.)
  • Variables Control Charts(Contd.)
  • Variables Control Charts (Contd.)
  • Variables Control Charts (Contd.)
  • Variables Control Charts(Contd.)
  • Variables Control Charts(Contd.)
  • Variables Control Charts(Contd.)
  • Variables Control Charts(Contd.)
  • Variables Control Charts(Contd.)
  • Variables Control Charts(Contd.)
  • Variables Control Charts(Contd.)
  • Variables Control Charts(Contd.)
  • Variables Control Charts(Contd.)
  • Variables Control Charts (Contd.)
  • EWMA Charts
  • EWMA Charts(Contd.)
  • Cusum Charts
  • Attribute Control Charts
  • Attribute Control Charts(Contd.)
  • Attribute Control Charts(Contd.)
  • Attribute Control Charts (Contd.)
  • Attribute Control Charts(Contd.)
  • Attribute Control Charts(Contd.)
  • Attribute Control Charts(Contd.)
  • Summary
  • VI Lesson 3 Measurement System Analysis Control Plan and Project Closure
  • Agenda
  • Measurement System Analysis
  • Control Plan
  • Control Plan(Contd.)
  • Control Plan(Contd.)
  • Control Plan(Contd.)
  • Project Closure
  • Summary
  • Section VI Lesson 4 Introduction to Total Productive Maintenance
  • Agenda
  • Total Productive Maintenance(TPM)
  • Total Productive Maintenance(TPM)(Contd.)
  • Total Productive Maintenance(TPM)(Contd.)
  • Total Productive Maintenance(TPM)(Contd.)
  • Total Productive Maintenance(TPM)(Contd.)
  • Total Productive Maintenance(TPM)(Contd.)
  • Total Productive Maintenance(TPM)(Contd.)
  • Summary
  • Tools to Refer

LEAN SIX SIGMA BLACK BELT CERTIFICATION TRAINING FAQS IN COLUMBUS, OH

Lean Six Sigma is a methodology that relies on a collaborative team effort to improve performance by systematically removing waste; combining lean manufacturing/lean enterprise and Six Sigma to eliminate the eight kinds of waste: defects, overproduction, waiting, non-utilized talent, transportation, inventory, motion, extra-processing.

This 1-day hands-on instructor-led training focuses on the final preparation for the LSSBB Exam including:

  • Solving of a Mock exam
  • Exam Question analysis and
  • Doubt clearing

It provides an intense learning environment to the attendees for their exam preparation and is scheduled once every month. You will be provided with a link to attend the session.

The different levels of Lean Six Sigma are:

  • Lean Six Sigma Black Belt
  • Lean Six Sigma Green Belt
  • Lean Six Sigma Yellow Belt

All exam questions are multiple choice and true/false. Candidates are allowed up to 4 hours for the IASSC Certified Black Belt Exam. There is no limitation or time restriction on examination retakes. The cost of IASSC Lean Six Sigma Black Belt Exam is USD 395

You can click on the Enroll for this course button at the top of this page and make a payment using Credit Card/Debit Card/Internet Banking/Paypal. You can also contact us via email (support@arlearners.net).

All PDU E-Certificates will reach participants within 2 business days after the training.

Quick Enquiry

CORPORATE TRAINING

Customized to your team's needs
  • Customized learning delivery model
  • The Latest Curriculum, from Industry Experts
  • High Engagement, Outcome-Centric Learning
  • Provide hands-on applied learning critical for new hires
  • 24x7 learner assistance and support
CONTACT US

Categories

Related Courses

Testimonials

James Noah

James Noah

Really Appreciate the teaching, I did PMP training in AR Learners. The trainer Mr. James Parker was really good having vast Knowledge and had patience in answering questions.

Andrew Jones

Andrew Jones

I like this platform. Content is made easily accessible and the instructors are willing to help you if you are having trouble with anything. A great way to pick up new Data Science skills or to just keep yourself sharp regarding the foundations. I believe the future of education is heading in this direction.

Christiana Julie

Christiana Julie

John is an excellent teacher. His knowledge about the topic made the class fun and interesting! I am glad that I chose AR Learners to attend this training.

Mohammad Ali

Mohammad Ali

I had a pleasant experience with the AR Learners team and their mentors. Value for money courses on variety of topics. The service is fast and reliable. I will recommend this to everyone.

Zainab Fathima

Zainab Fathima

Got PMP certified through AR Learners. Over all a very good experience. I really liked their mock exams and quizzes which helped me in clearing my exam.

Ivor kellock

Ivor kellock

It was a great experience for accomplishing ITIL Expert certification through AR Learners. Alway ready to help for any kind of queries. Although online training materials are good, but i would recommend these should be further improved from content perspective. Overall, I am fully satisfied with the services and would recommend everyone to join and experience the learning services through them.

Michael Smith

Michael Smith

As I am starting from PMP Course, I had a very good learning experience in AR Learners with the live classes, examples, platform, support and projects. It does help you get into the subject. Thanks.

Jasenka Marko

Jasenka Marko

Attended a 2-day weekend course by AR Learners for the Prince2 certification. The instructor was very knowledgeable and engaging. Overall it was an excellent experience and nice Guidence.

Laura Thomas

Laura Thomas

AR Learners is awesome. They have so many ways of learning. First, there are videos to prepare you for the class. Then there are live lectures, with quick quizzes to check your understanding. Finally, you have a final exam and a final project. When you get done with the class, you know your stuff, you are an expert in that field.

OTHER TRAINING COURSES

Project Management

Project Management

READ MORE
IT Service Management

IT Service Management

READ MORE

Quality Management

READ MORE
Agile and Scrum

Agile & Scrum

READ MORE
Big Data

Big Data

READ MORE