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Six Sigma Green Belt Training Programme

Enhance your skills and knowledge with our comprehensive Six Sigma Green Belt Training Program.

  • Category Project Management
Six Sigma Green Belt Training Programme

What you'll learn

  • The fundamentals of Lean .Six Sigma and its business impact
  • Understanding DMAIC methodology and key problem-solving tools.
  • How to identify customer requirements and translate them into Critical-to-Quality (CTQ) factors.
  • Application of statistical tools, hypothesis testing, and process capability analysis.
  • Understanding and implementing Lean principles, waste reduction techniques, and Kaizen methodologies.
  • How to monitor Statistical Process Control (SPC) and ensure process sustainability.

Requirements

  • Good Wifi
  • Laptop

Description

Six Sigma Green Belt Training Programme

The Six Sigma Green Belt Training provides a comprehensive understanding of Six Sigma tools and methodologies, equipping professionals with the skills to lead process improvement projects effectively. This course follows the DMAIC (Define, Measure, Analyze, Improve, Control) methodology, helping participants understand data-driven decision-making, root cause analysis, and process optimization strategies. Through real-world examples, statistical techniques, and practical case studies, learners will gain expertise in Lean principles, quality tools, hypothesis testing, and Minitab usage. By the end of the course, participants will be prepared to identify inefficiencies, improve processes, reduce costs, and enhance customer satisfaction using Six Sigma methodologies.

  • The Six Sigma Green Belt Training offers a comprehensive understanding of Six Sigma tools and methodologies, empowering professionals to effectively lead process improvement projects..
  • This course follows the DMAIC (Define, Measure, Analyze, Improve, Control) methodology, aiding participants in grasping data-driven decision-making, root cause analysis, and process optimization strategies..
  • This course follows the DMAIC (Define, Measure, Analyze, Improve, Control) methodology, aiding participants in grasping data-driven decision-making, root cause analysis, and process optimization strategies..
  • This course follows the DMAIC (Define, Measure, Analyze, Improve, Control) methodology, aiding participants in grasping data-driven decision-making, root cause analysis, and process optimization strategies..

Who this course is for:

  • Professionals working in Quality, Operations, Manufacturing, Process Improvement, or Business Excellence.
  • Managers and Team Leaders who want to drive data-driven decision-making.
  • Engineers, Analysts, and Process Owners looking to enhance their problem-solving skills.
  • MBA graduates, students, and individuals aspiring for careers in Six Sigma, Lean, or Quality Management.
  • Anyone who wants to gain expertise in Lean Six Sigma methodologies and lead improvement projects.

Meet your instructors

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Namita Rani

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Namita is Six Sigma Black Belt Certified professional with over 17 years of experience in Operations, Quality, Finance, and Consulting across difference industries. Holding an MBA in Finance, Six Sigma Black Belt and ISO 9001 Lead Auditor Certification, she has successfully led process improvement...

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Why enroll in this course?

Lead digital transformation in your organization by mastering the core concepts of generative artificial intelligence and its potential impact.

Master and integrate prompt engineering to optimize day-to-day tasks and automate workflows.

Foster an “AI friendly” culture in your organization by understanding the ethical aspects and the risks associated with the implementation of this technology.

Explore tools such as ChatGPT, as well as other emerging technologies, to improve productivity.

Interact with MIT experts, instructors, and peers in live synchronous sessions for a more comprehensive learning experience.

Access to rich supplementary resources provides additional materials and content for a more thorough educational journey.

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Course Syllabus

  • History & Evolution of Six Sigma
  • Concept of Six Sigma & Lean
  • Cost of Poor Quality (COPQ) & Process Variation
  • Introduction to DMAIC Methodology

  • Identifying Customers & Stakeholders
  • Establishing Voice of the Customer (VOC) to Critical-to-Quality (CTQ)
  • Creating Process Maps (Flowcharts, SIPOC)
  • Understanding KANO Model & RACI Matrix
  • Developing a Project Charter

  • Data Types & Classification
  • Creating a Data Collection Plan
  • Sampling Strategies & Techniques
  • Understanding Basic Statistics (Mean, Median, Mode, Standard Deviation, Variance)
  • Normal Distribution Curve & Normality Testing
  • Introduction to Minitab for Statistical Analysis
  • Process Capability Analysis
  • Measurement System Analysis (MSA) - Accuracy, Precision & Gage R&R

  • Defects Per Opportunity (DPO), Defects Per Unit (DPU), and Defects Per Million Opportunities (DPMO)
  • Rolled Throughput Yield (RTY)
  • 7 QC Tools for Problem-Solving
  • Hypothesis Testing (T-Test, Correlation & Regression Analysis)
  • Understanding Alpha & Beta Risks
  • Data Visualization - Histogram, Dot Plot, Box Plot, Time Series Plot

  • Developing Improvement Strategies
  • Failure Modes and Effects Analysis (FMEA)
  • Implementing Lean Tools: Kaizen (Continuous Improvement), Poka-Yoke (Error Proofing), KANBAN (Visual Workflow Management), 5S (Workplace Organization), Just-in-Time (JIT) & Takt Time, 7 Types of Waste & How to Eliminate Them

  • Statistical Process Control (SPC) & Control Charts
  • Developing a Control Plan to sustain improvement
  • Cost-Benefit Analysis for Project Validation
  • Project Closure & Documentation Best Practices

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