MAP022 – 120.00 Hours
Currently there are no scheduled classes for this course. However, in some cases a course can be scheduled to meet your organization’s specific needs. For more information about this course or to schedule a class, please contact Business & Cyber Solutions at or [email protected] to get the latest schedule.
LEAN SIX SIGMA = Two Powerful Initiatives, One Integrated Program
Lean Six Sigma Black Belt consists of four one-week long sessions held over a period of four months (one week per month).
Dramatically improve cost, quality, and delivery by combining the strengths of two powerful business process improvement initiatives through the systematic approach of the TMAC Lean Six Sigma (LSS) program. Integrated into the Define, Measure, Analyze, Improve, Control (DMAIC) project management structure, Lean Six Sigma results are impactful, robust, and sustainable.
Expect to be immersed in a hybrid learning environment of instruction, group exercises, hands-on simulations, teach-backs, project presentations and review of industry case studies. Experienced instructors emphasize practical application of tools and share lessons learned from hundreds of completed projects.
Learning doesn’t stop once training is over. Participants can access TMAC LSS Master Black Belts before, during and after training for coaching to rapidly apply what they learn.
Engage with more than 35 LSS tools.
Earn your LSS BB certification. Complete the course. Apply what you have learned on a project according to the TMAC certification guidelines. Become certified.
TMAC Black Belts experience a median financial impact of $150,000 per year. Registration includes course material including guide books, tool booklets, and binders for in-class materials.
Monday: 9am – 5:30pm
Tuesday – Thursday: 8am – 5:30pm
Friday: 8am – Noon
There are no prerequisites for this course.
Course Completion Requirements
Participants should come to the event with a defined problem description that is impacting the business. Instructors will assist participants in completing a project charter.
Participant Must Provide
- a laptop computer with MS Excel
- a Minitab loaded on their laptop with an active license
- a photo identification on the first day of class. See the Participant Handbook for approved forms of identification and additional guidelines.
Class attendance is an essential part of the education process and participants in TEEX courses are expected to attend all class sessions and field exercises. This course requires participants to attend a minimum of 80% of the class hours as a component of successful course completion. During the course, your instructor will review any additional attendance requirements, for example a field exercise that cannot be missed
Upon successful completion, you will be able to:
- LEAN PROCESS FLOW: 5S Workplace Organization, ABC Stratification, Analytical Batch Sizing, Kaizen Rapid Improvement Events, Mistake Proofing, Process Constraint Analysis, Process Flow and Balancing Improvement, Pull Systems and Kanbans (Generic and Replenishment), Rolled Throughput Yield, Setup Reduction (SMED), Stocking Strategy, The Value of Speed, Total Productive Maintenance (TPM), Value Stream Mapping (Single and Multi-plant), Visual Process Control Tools, Work Simplification
- PROJECT AND LEAN TOOLS: Evaluating Alternative Solutions (AHP, Pugh Matrix), Failure Modes and Effects Analysis (FMEA), Piloting the Solution, Process Control and Implementation Plans, Project Charters, Project Planning & Management, Root Cause Tools (Fishbone, Pareto, C&E Matrix), Solution Generation and Selection, Team Facilitation & Brainstorming Methods, Voice of Customer (VOC) Analysis
- STATISTICAL ANALYSIS: Analysis of Variance (ANOVA – One and Two way), Basic Statistics, Variation and Graphical AnalysisControl Charts (Variable and Attribute), Data Collection and Sampling Strategies, Dealing with Non-Normally Distributed Data, Design of Experiments (Planning, Design & Analysis), Hypothesis Testing (Continuous and Discrete), Process Capability (Continuous and Attribute), Regression (Simple and Multiple), Statistical Process Control (SPC)