3 Educators providing Six Sigma courses in Elland

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 Green Belt Certification Program: In-House Training This learning series is designed to enable participants to fulfill the important role of a Lean Six Sigma Green Belt and to incorporate the Lean Six Sigma mindset into their leadership skills. Green Belt is not just a role, it is also a competency required for leadership positions at many top companies. This learning series is designed to enable participants to fulfill the important role of a Lean Six Sigma Green Belt and to incorporate the Lean Six Sigma mindset into their leadership skills. With a real-world project focus, the series will teach the fundamental methodology, tools, and techniques of the Define, Measure, Analyze, Improve and Control Process Improvement Methodology. This course is delivered through sixteen 3-hour online sessions. What you Will Learn At the end of this program, you will be able to: Identify strategies for effectively leading high performing process improvement teams Analyze whether projects align with business strategy Apply process improvement methodologies to DMAIC steps, based on real world scenarios Explain ways to appropriately respond to process variation Distinguish among best practice problem solving methodologies Evaluate and effectively communicate data-driven decisions, based on real world scenarios Introduction Lean Six Sigma & quality The vision The methodologies The metric Project Selection Why Projects Random idea generation Targeted idea generation CTQs (Critical to Quality) & projects Project screening criteria Quick improvements Introduction to Define Project Planning Developing the core charter Developing a project charter Facilitation Process Management Business process management Top-down process mapping Voice of the Customer Voice of Customer Stakeholder analysis Communication planning Kicking off the project Define Summary Introduction to Measure Data Collection Fact-based decision making Data sampling Operations definitions Data collection plan Measurement system analysis Graphical Statistics for Continuous Data Meet Six SigmaXL Graphical & statistical tools Data stratification Graphical Statistics for Discrete Data Pareto analysis Dot plots Plotting data over time: Looking for patterns Variation Concepts Variation is reality Special Cause and Common Cause variation Example of standard business reporting Individuals Control Chart Process Capability Genesis of process capability Calculating the metrics of Six Sigma Yield metrics: Measuring process efficiency Cost of Poor Quality The Cost of Poor Quality (COPQ) Cost of Quality categories Calculating the Cost of Poor Quality Measure Summary Introduction to Analyze Process Analysis Introduction to process analysis Value-added analysis Cycle time analysis WIP & pull systems Analyzing bottlenecks and constraints Cause & Effect Analysis Fishbone/Ishikawa diagram 5-Whys analysis Graphical & statistical tools Advanced Analysis Why use hypothesis rests? Hypothesis tests Correlation and regression analysis Analyze Summary Introduction to Improve Solutions Creativity techniques Generating alternative solutions Solution selection techniques Introduction to Design of Experiments Introduction to DOE DOE activity Error Proofing Failure mode & effect analysis Poka-Yoke Project Management Fundamentals Successful teams Project roles Conflict management Standardization Standardization The Visual Workplace 5S Piloting & Verifying Results What is a pilot? Evaluating results Improve Summary Introduction to Control Statistical Process Control Review of Special & Common Cause variation Review of Individual Control Chart P-Chart for discrete proportion data Transition Planning Control plan Project closure Control Summary Summary and Next Steps

Lean Six Sigma Yellow Belt Certification Program: In-House Training This course is designed to instill an in-depth understanding of Lean Six Sigma and a clear sense of what is required to define high-impact improvement projects, establish Lean Six Sigma measurements, and complete Lean Six Sigma projects using the systematic and proven Define, Measure, Analyze, Improve, and Control (DMAIC) methodology. This course is designed to instill an in-depth understanding of Lean Six Sigma and a clear sense of what is required to define high-impact improvement projects, establish Lean Six Sigma measurements, and complete Lean Six Sigma projects using the systematic and proven Define, Measure, Analyze, Improve, and Control (DMAIC) methodology. Participants will learn basic tools and techniques of Lean Six Sigma and those who pass a thirty-question exam (70% or above) will become a Certified Lean Six Sigma Yellow Belt. This course is delivered through four 3-hour online sessions. What you Will Learn You'll learn how to: Establish the structure that supports and sustains Lean Six Sigma Quality Identify and calculate key Lean Six Sigma Measurements (Sigma, DPMO, and Yield) Select successful, high-impact projects that match strategic objectives Document, measure, and improve key processes using the DMAIC (Define, Measure, Analyze, Improve, and Control) Methodology Utilize data-based thinking to make key business decisions Introduction to the Fundamentals and Vision of Lean Six Sigma Lean Six Sigma's focus on the customer, on quality, and on results The costs of poor quality Critical factors to consider when deploying Lean Six Sigma Lean Six Sigma as a process improvement methodology Lean Six Sigma metrics Why do it - ROI and payback for Lean Six Sigma Business Process Management Critical Lean Six Sigma roles and responsibilities Main aspects of managing the organizational change Project selection Metrics of Lean Six Sigma and the DMAIC Model How to strategically align business metrics and projects within an organization How to identify and measure quality characteristics which are critical to customers What does the customer (internal or external) really want from our products and services? Establishing appropriate teams and setting those teams up to be successful What defines a good measurement system? How are we doing (learning the secret to measuring the right things, right)? How to improve output measures by understanding and measuring the process Where are there defects (how to properly select and scope high-impact projects)? Where is the process broken (the Lean Six Sigma version of root cause analysis)? How to determine the process efficiency, or value add, of a process The appropriate use of quality tools Understanding the concept of variation and how to reduce knee-jerk reactions How to achieve breakthrough results for any key measure How can we ensure the identified improvements will be sustainable (the basics of process control)?

About this Virtual Instructor Led Training (VILT) Preventive and Predictive maintenance are not new concepts. Both have been used across industry all over the world and when done properly, can yield impressive results (cost reductions of 20% or greater and a leap forward in equipment reliability and performance are very achievable). However, for every company using these concepts effectively, there are many others who are not. This 8 half-day Virtual Instructor Led Training (VILT) course has been derived from the Plant Performance Improvement Road Map developed by practitioners that guarantee the reliability of your operations. The VILT training focuses on how to improve profitability of any business by identifying the right maintenance strategy for any equipment. The aim of the VILT training is to help practitioners run programmes that will deliver real benefits as fast as possible with minimum zero wasted effort. The VILT training will also cover the core principles of Reliability Centred Maintenance, Total Productive Maintenance and Six Sigma and the increasingly important role of operations in achieving optimised asset performance. This is a certified course with the option of sitting for a short exam on the final day of the course to give participants the opportunity to gain a Certificate from petroEDGE and the Carcharodon Maintenance Academy. Training Objectives Master the critical skills by acquiring the following: An understanding of how maintenance can add profit The ability to develop improvement programmes that deliver maximum benefit in the shortest time A fundamental understanding of the principles of Preventive, Predictive and other maintenance types A practical understanding of the latest methods of solving problems at root cause level An appreciation of maintenance methodologies such as Reliability Centred Maintenance Strategies for ensuring your company gets value for money from your Contractors How to use the Maintenance Model of Excellence and Plant Performance Improvement Road Map Target Audience This VILT course has been designed for maintenance managers and engineers, reliability professionals, planners, project engineers, operations team members, and functional specialists. Training Methods The VILT course will be delivered online in 8 half-day sessions comprising 4 hours per day, with 2 breaks of 10 minutes per day. Course Duration: 8 half-day sessions, 4 hours per session (32 hours in total). Trainer Your expert course leader is an award-winning consultant and trainer with 30 years' experience in maintenance and reliability improvement. He has worked across five continents, in a wide variety of environments from the world's largest oil refinery to a small drinks production line. He has 10 years of maintenance management experience in the process industry, so he brings a very practical approach to training. He moved into consulting with ABB Eutech as their global maintenance specialist where he led maintenance and reliability best practice panels, delivered a wide range of maintenance improvement projects and trained other consultants. He is a fully qualified CMRP professional, an approved SMRP* Proctor, authorised to conduct CMRP exams and a globally respected maintenance consultant and best practice trainer. He founded his consultancy and training business in 2002 to focus on maintenance and reliability improvement. As part of this, he developed a range of maintenance 'models of excellence' with inputs from authors, international lecturers and some of the world's leading consultants and operators. His work has been recognised as being at the leading edge of industry best practice, winning independent awards such as the UK Chemical Industries Association 'Excellence in Engineering' award. He remains close to the industry as a respected specialist helping operating companies to achieve changes in performance. This ongoing field work enables him to continue to refine and extend best practice and the learning from this is continually fed into his training. His unique experience of facilitating two major turnarounds when the Coronavirus escalated into lockdown have given him a unique insight into how events of this type can disrupt maintenance. Moreover, his involvement in developing management processes and leading a Coronavirus response on a major industrial asset means he can talk with direct experience about how to cope and innovate in this global pandemic. *SMRP refers to Society of Maintenance and Reliability Professionals. PetroEdge is not affiliated with SMRP POST TRAINING COACHING SUPPORT (OPTIONAL) To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster. Request for further information about post training coaching support and fees applicable for this. Accreditions And Affliations

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