4 Belts courses in Crook delivered Live Online

Lean Six Sigma Black Belt Certification Program: In-House Training This course is specifically for people wanting to become Lean Six Sigma Black Belts, who are already Lean Six Sigma practitioners. If advanced statistical analysis is needed to identify root causes and optimal process improvements, (Lean) Six Sigma Green Belts typically ask Black Belts or Master Black Belts to conduct these analyses. This course will change that. Green Belts wanting to advance their statistical abilities will have a considerable amount of hands-on practice in techniques such as Statistical Process Control, MSA, Hypothesis Testing, Correlation and Regression, Design of Experiments, and many others. Participants will also work throughout the course on a real-world improvement project from their own business environment. This provides participants with hands-on learning and provides the organization with an immediate ROI once the project is completed. IIL instructors will provide free project coaching throughout the course. What you Will Learn At the end of this program, you will be able to: Use Minitab for advanced data analysis Develop appropriate sampling strategies Analyze differences between samples using Hypothesis Tests Apply Statistical Process Control to differentiate common cause and special cause variation Explain and apply various process capability metrics Conduct Measurement System Analysis and Gage R&R studies for both discrete and continuous data Conduct and analyze simple and multiple regression analysis Plan, execute, and analyze designed experiments Drive sustainable change efforts through leadership, change management, and stakeholder management Successfully incorporate advanced analysis techniques while moving projects through the DMAIC steps Explain the main concepts of Design for Six Sigma including QFD Introduction: DMAIC Review IIL Black Belt Certification Requirements Review Project Selection Review Define Review Measure Review Analyze Review Improve Review Control Introduction: Minitab Tool Introduction to Minitab Minitab basic statistics and graphs Special features Overview of Minitab menus Introduction: Sampling The Central Limit Theorem Confidence Interval of the mean Sample size for continuous data (mean) Confidence Interval for proportions Sample size for discrete data (proportions) Sampling strategies (review) Appendix: CI and sample size for confidence levels other than 95% Hypothesis Testing: Introduction Why use advanced stat tools? What are hypothesis tests? The seven steps of hypothesis tests P value errors and hypothesis tests Hypothesis Testing: Tests for Averages 1 factor ANOVA and ANOM Main Effect Plots, Interaction Plots, and Multi-Vari Charts 2 factor ANOVA and ANOM Hypothesis Testing: Tests for Standard Deviations Testing for equal variance Testing for normality Choosing the right hypothesis test Hypothesis Testing: Chi Square and Other Hypothesis Test Chi-square test for 1 factor ANOM test for 1 factor Chi-square test for 2 factors Exercise hypothesis tests - shipping Non-parametric tests Analysis: Advanced Control Charts Review of Common Cause and Special Cause Variation Review of the Individuals Control Charts How to calculate Control Limits Four additional tests for Special Causes Control Limits after Process Change Discrete Data Control Charts Control Charts for Discrete Proportion Data Control Charts for Discrete Count Data Control Charts for High Volume Processes with Continuous Data Analysis: Non-Normal Data Test for normal distribution Box-Cox Transformation Box-Cox Transformation for Individuals Control Charts Analysis: Time Series Analysis Introduction to Time Series Analysis Decomposition Smoothing: Moving Average Smoothing: EWMA Analysis: Process Capability Process capability Discrete Data: Defect metrics Discrete Data: Yield metrics Process Capability for Continuous Data: Sigma Value Short- and long-term capabilities Cp, Cpk, Pp, Ppk capability indices Analysis: Measurement System Analysis What is Measurement System Analysis? What defines a good measurement system? Gage R&R Studies Attribute / Discrete Gage R&R Continuous Gage R&R Regression Analysis: Simple Correlation Correlation Coefficient Simple linear regression Checking the fit of the Regression Model Leverage and influence analysis Correlation and regression pitfalls Regression Analysis: Multiple Regression Analysis Introduction to Multiple Regression Multicollinearity Multiple Regression vs. Simple Linear Regression Regression Analysis: Multiple Regression Analysis with Discrete Xs Introduction Creating indicator variables Method 1: Going straight to the intercepts Method 2: Testing for differences in intercepts Logistic Regression: Logistic Regression Introduction to Logistic Regression Logistic Regression - Adding a Discrete X Design of Experiments: Introduction Design of Experiment OFAT experimentation Full factorial design Fractional factorial design DOE road map, hints, and suggestions Design of Experiments: Full Factorial Designs Creating 2k Full Factorial designs in Minitab Randomization Replicates and repetitions Analysis of results: Factorial plots Analysis of results: Factorial design Analysis of results: Fits and Residuals Analysis of results: Response Optimizer Analysis of results: Review Design of Experiments: Pragmatic Approaches Designs with no replication Fractional factorial designs Screening Design of Experiment Case Study Repair Time Blocking Closing: Organizational Change Management Organizational change management Assuring project sponsorship Emphasizing shared need for change Mobilizing stakeholder commitment Closing: Project Management for Lean Six Sigma Introduction to project management Project management for Lean Six Sigma The project baseline plan Work Breakdown Structure (WBS) Resource planning Project budget Project risk Project schedule Project executing Project monitoring and controlling and Closing Closing: Design for Lean Six Sigma Introduction to Design for Lean Six Sigma (DMADV) Introduction to Quality Function Deployment (QFD) Summary and Next Steps IIL's Lean Six Sigma Black Belt Certification Program also prepares you to pass the IASSC Certified Black Belt Exam (optional)

Lean Six Sigma Black Belt Certification Program: Virtual In-House Training This course is specifically for people wanting to become Lean Six Sigma Black Belts, who are already Lean Six Sigma practitioners. If advanced statistical analysis is needed to identify root causes and optimal process improvements, (Lean) Six Sigma Green Belts typically ask Black Belts or Master Black Belts to conduct these analyses. This course will change that. Green Belts wanting to advance their statistical abilities will have a considerable amount of hands-on practice in techniques such as Statistical Process Control, MSA, Hypothesis Testing, Correlation and Regression, Design of Experiments, and many others. Participants will also work throughout the course on a real-world improvement project from their own business environment. This provides participants with hands-on learning and provides the organization with an immediate ROI once the project is completed. IIL instructors will provide free project coaching throughout the course. What you Will Learn At the end of this program, you will be able to: Use Minitab for advanced data analysis Develop appropriate sampling strategies Analyze differences between samples using Hypothesis Tests Apply Statistical Process Control to differentiate common cause and special cause variation Explain and apply various process capability metrics Conduct Measurement System Analysis and Gage R&R studies for both discrete and continuous data Conduct and analyze simple and multiple regression analysis Plan, execute, and analyze designed experiments Drive sustainable change efforts through leadership, change management, and stakeholder management Successfully incorporate advanced analysis techniques while moving projects through the DMAIC steps Explain the main concepts of Design for Six Sigma including QFD Introduction: DMAIC Review IIL Black Belt Certification Requirements Review Project Selection Review Define Review Measure Review Analyze Review Improve Review Control Introduction: Minitab Tool Introduction to Minitab Minitab basic statistics and graphs Special features Overview of Minitab menus Introduction: Sampling The Central Limit Theorem Confidence Interval of the mean Sample size for continuous data (mean) Confidence Interval for proportions Sample size for discrete data (proportions) Sampling strategies (review) Appendix: CI and sample size for confidence levels other than 95% Hypothesis Testing: Introduction Why use advanced stat tools? What are hypothesis tests? The seven steps of hypothesis tests P value errors and hypothesis tests Hypothesis Testing: Tests for Averages 1 factor ANOVA and ANOM Main Effect Plots, Interaction Plots, and Multi-Vari Charts 2 factor ANOVA and ANOM Hypothesis Testing: Tests for Standard Deviations Testing for equal variance Testing for normality Choosing the right hypothesis test Hypothesis Testing: Chi Square and Other Hypothesis Test Chi-square test for 1 factor ANOM test for 1 factor Chi-square test for 2 factors Exercise hypothesis tests - shipping Non-parametric tests Analysis: Advanced Control Charts Review of Common Cause and Special Cause Variation Review of the Individuals Control Charts How to calculate Control Limits Four additional tests for Special Causes Control Limits after Process Change Discrete Data Control Charts Control Charts for Discrete Proportion Data Control Charts for Discrete Count Data Control Charts for High Volume Processes with Continuous Data Analysis: Non-Normal Data Test for normal distribution Box-Cox Transformation Box-Cox Transformation for Individuals Control Charts Analysis: Time Series Analysis Introduction to Time Series Analysis Decomposition Smoothing: Moving Average Smoothing: EWMA Analysis: Process Capability Process capability Discrete Data: Defect metrics Discrete Data: Yield metrics Process Capability for Continuous Data: Sigma Value Short- and long-term capabilities Cp, Cpk, Pp, Ppk capability indices Analysis: Measurement System Analysis What is Measurement System Analysis? What defines a good measurement system? Gage R&R Studies Attribute / Discrete Gage R&R Continuous Gage R&R Regression Analysis: Simple Correlation Correlation Coefficient Simple linear regression Checking the fit of the Regression Model Leverage and influence analysis Correlation and regression pitfalls Regression Analysis: Multiple Regression Analysis Introduction to Multiple Regression Multicollinearity Multiple Regression vs. Simple Linear Regression Regression Analysis: Multiple Regression Analysis with Discrete Xs Introduction Creating indicator variables Method 1: Going straight to the intercepts Method 2: Testing for differences in intercepts Logistic Regression: Logistic Regression Introduction to Logistic Regression Logistic Regression - Adding a Discrete X Design of Experiments: Introduction Design of Experiment OFAT experimentation Full factorial design Fractional factorial design DOE road map, hints, and suggestions Design of Experiments: Full Factorial Designs Creating 2k Full Factorial designs in Minitab Randomization Replicates and repetitions Analysis of results: Factorial plots Analysis of results: Factorial design Analysis of results: Fits and Residuals Analysis of results: Response Optimizer Analysis of results: Review Design of Experiments: Pragmatic Approaches Designs with no replication Fractional factorial designs Screening Design of Experiment Case Study Repair Time Blocking Closing: Organizational Change Management Organizational change management Assuring project sponsorship Emphasizing shared need for change Mobilizing stakeholder commitment Closing: Project Management for Lean Six Sigma Introduction to project management Project management for Lean Six Sigma The project baseline plan Work Breakdown Structure (WBS) Resource planning Project budget Project risk Project schedule Project executing Project monitoring and controlling and Closing Closing: Design for Lean Six Sigma Introduction to Design for Lean Six Sigma (DMADV) Introduction to Quality Function Deployment (QFD) Summary and Next Steps IIL's Lean Six Sigma Black Belt Certification Program also prepares you to pass the IASSC Certified Black Belt Exam (optional)

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We offer the most advanced “Certified Six Sigma Green Belt Course” as per the curriculum outline of The ASQ Body of Knowledge and accredited by top international Lean & Six Sigma accreditation bodies. Six Sigma Green Belt Deliverables: 22+ hours of Instructor-led interactive virtual classroom session on the weekend Access to 45+ hours of Module based Six Sigma lectures via LMS 100+ Toolkits and Project Templates for Analysis and Implementation Soft copy of Lean Six Sigma Green Belt Body of Knowledge Live Data-oriented project, with Scenario and Analysis Methodology 20+ Dummy Projects and Case studies for Lean Six Sigma Application Support via subject expert through telephonic discussion on the weekend Sample Questions and Examination Guide for Certification Preparation Pre and Post assignments for process groups and knowledge areas Project implementation support and Data visualization using MINITAB PRO CLSSGB certification examination anytime within the 90 days course duration Certification Validation Tool for third-party credentials validation PARTICULARS Duration (Hours) 1. Define Phase 22 2. Measure Phase 14 3. Analyse Phase 20 4. Improve Phase 7 5. Control Phase 7 Total Duration 70 (Hours) Introduction Become an expert in six sigma methodology by getting hands-on knowledge on DMAIC, Project Charter, Process Capability, FMEA, Sigma calculation, Test of Hypothesis, Control Charts, VSM, JIT using real case scenarios and real-life examples. Lean and DMAIC methodologies using live projects. The Six Sigma Certification is accredited by The Council for Six Sigma Certification. The certification also acknowledges the BOK outline of The American Society for Quality, USA. The course features world-class content with live projects and MINITAB PRO driven data analysis training with end to end support in project implementation by Master Black Belt Experts and Trainers. What is Six Sigma Certification? A person with Six Sigma certification has problem-solving abilities. Someone may gain Green Belt, Black Belt or Master Black Belt certification. The higher certification one attains, the more is the ability to solve complex organizational problems. Six Sigma certification is a process of individual’s knowledge validation using a classification system, generally referred to as "Belts" (Green Belt, Black Belt, Master Black Belt) This verification test individual commands over six sigma methodology and tools. The belt classification shows the position these certified individuals would occupy in an organizational structure and job roles. Six Sigma Green Belt training is especially for the future project leaders of Lean Six Sigma projects. We deliberately mix non-profit with profit participants. There will then be fun, useful discussions and knowledge exchanges during the training sessions. In addition, there are also many self-employed people who follow the LSS Green Belt training to increase their expertise as in a trimmer. What do you do to get the Six Sigma Green Belt certificate? Our Six Sigma Green Belt training consists of a number of components: Training: in an intensive training program you learn the background of Lean and Six Sigma and we put what we have learned into practice with different simulations. Extra: With our Body of Knowledge and whitepapers you place what you have learned in a theoretical framework. The program also contains various homework assignments, in which we focus, among other things, on the use of MINITAB PRO. Follow-up: During the training, you will receive an access code to an e-learning module. You can pass the substance again in an interactive way. Exam: On the last training day you will make the CLSSGB Green Belt exam. If you succeed, you will immediately receive the official Certified Lean Six Sigma Green Belt certification. Global Recognition of Your Certification: Agenda Overview of Six Sigma and the organizationSix Sigma and organizational goalsValue of six sigmaOrganizational goals and six sigma projectsOrganizational drivers and metricsLean principles in the organizationLean conceptsValue-streaming mappingDesign for six sigma (DFSS) methodologiesRoadmaps for DFSSBasic failure mode and effects analysis (FMEA)Design FMEA and process FMEA Define PhaseProject identificationProject SelectionProcess elementsBenchmarkingProcess inputs and outputsOwners and stakeholders Voice of the customer (VOC) Customer identificationCustomer dataCustomer requirements Project Management Basics Project charterProject scopeProject metricsProject planning toolsProject documentationProject risk analysisProject closureManagement and planning toolsBusiness results for projectsProcess performance CommunicationTeam dynamics and performanceTeam stages and dynamicsTeam roles and responsibilitiesTeam toolsTeam Communication Measure PhaseProcess analysis and documentationProbability and statisticsBasic probability conceptsCentral limit theorem, Statistical distributions, Collecting and summarizing dataTypes of data and measurement scalesSampling and data collection methodsDescriptive statisticsGraphical methodsMeasure Phase (contd E. Measurement system analysis (MSA) F. Process and performance capabilityProcess performance vs. process specificationsProcess capability studiesProcess capability (Cp, Cpk) and process performance (Pp, Ppk) indicesShort-term vs. long-term capability and sigma shift Analyze PhaseExploratory data analysisMulti-vari studiesCorrelation and linear regression B, Hypothesis testingBasics Tests for means, variances, and proportionsIntroduction to MINITAB Data analysis Improve Phase of Six SigmaDesign of experiments (DOE)Basic terms, DOE graphs, and plotsThe root cause analysisLean Tools 1. Waste elimination 2. Cycle-time reduction 3. Kaizen and kaizen blitz V1. Control PhaseStatistical process control (SPC)SPC BasicsRational subgroupingControl chartsControl planLean tools for process controlTotal productive maintenance (TPM)Visual factory Project Implementation & SupportMINITAB Practice and guidance for projectProject implementation supportTemplates and Toolkits application for Project workSupport on Data Project, Implementation and project completion BenefitsFrom the course Learn the principles and philosophy behind the Six Sigma technique Learn to apply statistical methods to improve business processes Design and implement Six Sigma projects in a practical scenario Learn the DMAIC process and various tools used in Six Sigma methodology Knowledge of Six Sigma Green Belt Professional enables you to understand real-world business problems, increase an organization's revenue by streamlining the process, and become an asset to an organization According to Villanova University, employers such as United Health Group, Honeywell, GE and Volkswagen have been actively seeking professionals with Six Sigma to fill a variety of positions The Training enhances your skills and enables you to perform roles like Quality Manager, Quality Analyst, Finance Manager, Supervisor, Quality Control, etc. According to Indeed.com, the national average salary for a Six Sigma Green Belt is $72,000 per year in the United States.   From the workshop Instructor LED training by Six Sigma Black Belt and Master Belt experts to make candidate learn the real scenario of six sigma tools and methodology Learn the principles and philosophy behind the Six Sigma method Dummy project by instructors to make candidate get a hands-on six sigma projects Downloadable Six Sigma PPT & Six Sigma PDF Industry Based case studies High-Quality training from an experienced trainer The Program extensively uses Minitab, specialized statistical software. It provides you with a thorough knowledge of Six Sigma philosophies and principles (including supporting systems and tools). Know about six sigma certification cost and six sigma green belt certification cost. Who should attend? The Six Sigma program is designed for professionals and students who want to develop the ability to lead process improvement initiatives. Six Sigma tools and process is widely used in all business processes. Six Sigma is applicable in all industry and in all functional areas. An indicative list of participants in our Green Belt program could include: Financial/business analyst Commodity manager Project manager Quality manager Production manager Production Engineer Business development manager Manufacturing process engineer Continuous improvement director Business managers or consultants Project manager/Program Manager Director or VP of operations CEO, CFO, CTO Certification On successful completion of the course and course requisites, the candidate will receive Internationally recognized Six Sigma Green Belt Certification. This course offers Six Sigma Certification Validation Tool for Employers Your Six Sigma Certification Validation Tool can be used by employers, clients and other stakeholders to validate the authenticity of your Six Sigma Certifications you have received. Using the programming code located on your certified LSSGB certification, one can see all your training and certification details online.