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16-DAY SIX SIGMA BLACK BELT

This program consists of over 60 interactive workshops that provide participants with the foundation for Six Sigma project success, including statistical and analytical tools, as well as change management, leadership, and project management skills.  Six Sigma Black Belts will be able to lead complex Six Sigma projects and apply advanced statistical tools to analyze process variation, and test design models that will enable greater process capability and process optimization.

Employing an Adult Learning Model, participants can apply newly-acquired Six Sigma tools and methods to actual process improvement projects over the course of training, enabling immediate benefit from your Six Sigma training investment.

The Six Sigma Black Belt curriculum consists of sixteen days of training that is conducted over a four month training cycle: Session 1 (4 days), Session 2 (4 days), Session 3 (4 days), Session 4 (4 days).  Trainees will be required spend time between sessions applying the concepts and tools learned to their assigned process improvement project, as well as preparing for their next training session.

At the end of each session of training, participants will develop an action plan for their projects, which will be reviewed by their Master Black Belt instructor.  If necessary, additional project coaching after the completion of Session 4 training can be arranged.

Session 1 Objectives: Define& Measure

Participants will be better able to define their project charters, as well as be prepared to complete the preliminary measurement and capability analysis for the process they will be improving.  They will also have a complete understanding of Six Sigma tools and methodology, as well as basic descriptive statistics which will provide the foundation for the course and Six Sigma project work to follow.  

• Explain Six Sigma fundamentals (program and concepts) 
• Establish & manage a project team 
• Complete and validate a project charter 
• Develop a Six Sigma project plan
• Effectively identify and resolve change management issues 
• Perform cost of poor quality assessments 
• Basic navigation of Minitab statistical analysis software 
• Identify and initiate benchmarking activities 
• Apply quality function deployment (QFD) methods 
• Complete a detailed process flow map 
• Construct and validate a value stream map 
• Construct a Cause & Effect diagram 
• Lean manufacturing process assessments 
• Use CSM or other forced ranking tools prioritize information 
• Prepare a Pareto analysis 
• Apply basic statistics to describe process under review 
• Prepare & interpret a histogram 
• Complete process variability, capability and yield studies 

Workshops - Session 1 

• Introduction to Six Sigma 
• Six Sigma Performance 
• Roles & Responsibilities 
• Project Charter 
• Project Team Selection 
• Project Management 
• Planning for Success - Project Closure 
• Change Management 
• Team Leadership & Facilitation Techniques 
• Cost of Poor Quality 
• Introduction to Minitab Statistical Analysis 
• Customer Focus 
• Customer Surveys 
• Benchmarking 
• Introduction to Quality Function Deployment 
• Process Flow Mapping 
• Value Stream Mapping 
• Input & Output Variables 
• Cause & Effect 
• Introduction to Lean Manufacturing 
• Interviewing Techniques 
• Process Variability 

Session 2 Objectives: Measure & Analyze
 

Participants will have completed their project charters, formally launched their improvement projects, and will also be prepared to complete the preliminary measurement and capability analysis for the process they will be improving.  Students will also have a better understanding of the statistical tools that will be used to provide enhanced insight into process behavior, and provide the knowledge base for sustained process improvement: 

• Use forced ranking systems 
• Construct Pareto charts 
• Analyze frequency distributions & histograms 
• Perform yield analysis 
• Assess process variation 
• Assign process capability measures 
• Determine sample sizes & calculate confidence intervals 
• Create data collection and sampling plans 
• Calculate and apply probability models 
• Risk assessments (FMEA, FTA) 
• Conduct measure systems analysis 

Session 2 Workshops 

• Affinity Diagrams 
• Characteristic Selection Matrix 
• Pareto Charts 
• Frequency Distributions 
• Histograms 
• Central Tendency Measures 
• Normal Distributions 
• Z Distribution 
• Central Limit Theorem 
• Complexity & Rolled Throughput
• DPU, DPMO, & Z 
• Measures of Variability 
• Shift & Drift 
• Populations & Samples 
• Sampling & Sample Sizes 
• Data Collection Planning 
• Basic Probability
• Characterizing a Defect 
• Common & Special Cause 
• Introduction to Control Charts 
• Process Capability 
• Failure Mode & Effects Analysis 
• Fault Tree Analysis 
• MSA: Gauge & Attribute R&R 

Session 3 Objectives: Analyze

Trainees will have a complete understanding of the analytical tools that can be applied to achieve an in-depth understanding of the processes that they are improving, and the participants will already have some indication as to the direction their process improvement efforts are taking them.  Students will have spent a significant portion of this week exploring the advanced statistical and analytical tools that will be leveraged for the breakthrough process improvements they are looking for in their projects. 

• Assess data normality and apply non-normal transforms 
• Understand & apply Binomial distribution models 
• Understand & apply Poisson distribution models 
• Explain basic hypothesis testing 
• Perform hypothesis tests for means and variance 
• Conduct non-parametric tests 
• Construct Chi-Square analysis 
• Carry out a regression analysis 
• Perform binary logistic regression 
• Conduct ANOVA & interpret results 

Session 3 Workshops

• Normality Testing 
• Data Transformation 
• Binomial Distribution 
• Poisson Distribution 
• Introduction to Hypothesis Testing 
• Proportions Testing 
• Non-parametric Testing 
• Sample t-Test
• Sample Variance F-Test 
• Z Test 
• Chi-Square 
• Scatter Plots 
• Regression 
• Binary Logistic Regression 
• Analysis of Variance (ANOVA & ANOM) 

Session 4 Objectives: Improve & Control

This fourth week of training is dedicated to completing the in-depth analyses of processes being improved, as well as the improvements that are being applied.  The focus will also shift to “Control” whereby long-term sustainability of processes, including robust design, can be achieved.  At the end of this final week of training, students will be able to apply their learning so that successful project closure can be achieved, and that a long-term control plan is set in place. 

• Plan and execute Design of Experiments (DOE) 
• Conduct a Historical DOE 
• Apply Harrington 12-Step process Rationalization 
• Update process maps and associated metrics 
• Design control plans and supporting control charts 
• Prepare project recommendations & closing reports 

Session 4 Workshops

• Session 3 analysis tools review 
• Introduction to Design of Experiments (DOE) 
• Full Factorial DOE 
• Fractional Factorial DOE 
• Historical DOE 
• Process Rationalization (Harrington) 
• Control Charts & Control Plans 
• Project Recommendations & Closing Reports