Lean Six Sigma Master Black Belt

Lean Six Sigma Master Black Belt

What is Lean Six Sigma Master Black Belt ?

  • Master Black Belts are responsible for training Black, Green, and Yellow Belts in Six Sigma methodologies and overseeing Six Sigma projects within the organization.

Who should attend?

  • Certified Black Belts seeking advanced problem-solving and leadership skills
  • Professionals aspiring for Lean Six Sigma leadership roles
  • Leaders aiming for MBB certification
  • Individuals planning to become independent Lean Six Sigma trainers/coaches
  • Quality professionals pursuing senior strategic roles

Lean Six Sigma Advanced Master Tools

  • Business Excellence – Strategy towards Shareholder value creation
  • LSS Deployment Planning & Kick -off
  • Achieving CEO commitment towards Business Excellence
  • Design For Six Sigma Framework and TRIZ

 Design Thinking & Agile Methodology

  • Integrating designer’s Mindset and customer’s Mindset
  • Design thinking for problem solving
  • Project Management Tools & Agile Methodology (information flow Processes)
  • Design thinking for problem solving

 Data Visualization

  • New Age CI Levers: Industry 4.0 (RPA
    Automation/ Interconnected
    /Intelligence) IOT
  • Data Visualization – Data Studio & Power Bi

 Leadership

  • Stability & Capability Exercise: Normal, Binomial, and Poisson distribution
  • Leadership Development, Remote Project Execution & Monitoring Framework
  • People Capability Building: Training Plan and Implementation. Mentoring and Coaching Framework

 Lean Master

  • Advanced lean tools- Sustainability VSM, Ergo VSM, Energy VSM
  • Architecture of Integrating Lean with Industry 4.0 concepts
  • Sustainability 7S
  • Integrating lean manufacturing paradigms with sustainability.

 Data Analytics

  • Stability & Capability Exercise: Normal, Binomial, and Poisson distribution
  • Advanced Data Analytics: Predictive Statistics
  • Advanced Data Analytics: Descriptive and Inferential
  • Advanced Data Analytics: Design of Experiments. Response Optimizer
  • Advanced Data Analytics: Descriptive and Inferential
  • Data Science Simplified

Skills Acquired :

✔ Advanced problem-solving and decision-making techniques

✔ Expertise in coaching and mentoring Six Sigma teams

✔ Leadership in driving business excellence initiatives

✔ Mastery of statistical and analytical tools

✔ Strategic planning and process optimization

✔ Implementation of high-impact improvement projects

✔ Effective change management and stakeholder engagement

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Environmental, Social, and Governance (ESG)

What is ESG?

  • ESG stands for Environmental, Social, and Governance – three key factors used to measure how responsible and sustainable a business or organization is.

    • Environmental (E): How a company impacts the planet – including energy use, carbon emissions, waste management, and resource conservation.
    • Social (S): How a company treats people – employees, customers, communities, and society at large. This includes diversity, human rights, workplace safety, and community engagement.
    • Governance (G): How a company is managed – covering ethical practices, leadership, transparency, board accountability, and compliance.

Who should attend?

    • Business Leaders & Executives
    • Sustainability Professionals
    • Risk & Compliance Officers
    • CSR & Governance Teams
    • Investors & Financial Analysts

Fundamentals of ESG:

  • Main Approaches for ESG indicators in India 
  • Nine Principles of Business Reporting 
  • Linking ESG Framework with SDGs
  • Linking Business Principles with ESG
  • Existing international standards for ESG reporting 
  • Comparative Analysis of Existing Framework
  • COP 21 -Paris Agreement (2015)
  • The growing demand of ESG and Status of ESG in India 
  • Existing of different types of Laws in India
  • Industry based Applicable Laws
  • ISO Certifications: Popular Standards pertaining to ESG

Environmental related issues, Challenges & Implementation strategies of ESG:

  • Definition of Environment Aspects in ESG
  • Environmental Management Systems 
  • Water & Energy Management Systems
  • Waste Management [including EPR]
  • Circular Economy
  • Green logistics & Water Footprint
  • Net zero – GHG Emission Carbon Footprint
  • Carbon credit eco system

Social related issues & Challenges in ESG:

  • Definition: Social Aspects of ESG
  • Existing of different types of Laws in India
  • Main Approaches for social ESG indicators in India 
  • Operational Difficulties within the Company 
  • Operation Difficulties outside the company
  • Human Resource Management – Inside & Outside Stake Holders in a Company
  • Internal ‘Social’ Element in ESG (Employees) and External ‘Social’ Element in ESG (Community)The Difference between CER & CSR
  • Un addressed Issue & Challenges of SOCIAL in ESG

Governance related issues & Challenges in ESG:

  • Meaning & Definitions 
  • Elements of Governances
  • Sharing Experience of Governance in Industries 
  • Governance Indicators in Industries
  • Corporate Governance Framework In India 
  • Role of Governance with SDGs

A way forwarded – ESG reporting, Operational Difficulties & Probable Solutions:

  • Operational Challenges of ESG 
  • Advocating ESG in context to SDG
  • Classification of Interventions/Activities under UN SDGs indicators
  • Progress of ESG Framework for reporting 
  • Business Responsibility & Sustainability Reporting (BRSR) Format
  • Matrix for Evaluation of Industries under ESG Reporting Framework
  • Recommendations and Conclusions for ESG Scheme in context of INDIA

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Artificial Intelligence

What is Artificial Intelligence?

Artificial Intelligence (AI) is the science of building smart machines that can think, learn, and act like humans. From voice assistants and chatbots to predictive analytics and self-driving cars, AI is transforming the way businesses and people work, communicate, and make decisions.

Who should attend?

  • Managers & Business Leaders
  • IT specialists
  • Software Developers
  • Engineers
  • Business Analysts

Introduction to AI:

  • AI & Intelligence
  • Machine Learning
  • Cognitive Computing

AI used in Analytics:

  • Descriptive & Predictive Analytics 
  • Pattern Recognition

AI vs Traditional Analytics:

  • AI vs Statistics
  • Decision Trees
  • Correlation vs Causation

Foundation of AI:

  • Supervised and Unsupervised Learning
  • Regression & Classification

AI- powered Data Handling and Analytics:

  • Regression Analysis
  • ANOVA
  • Predictive Modelling

Use of ChatGPT and Copilot:

  • Prompt Engineering
  • SOP Automation
  • Control Plans & Documentation AI

Data privacy & Ethical use of AI:

  • Ethics & Transparency
  • GDPR & Responsible AI

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Total Productive Maintenance (TPM)

What is Total Productive Maintenance (TPM)?

Total Productive Maintenance (TPM) is a systematic approach to improving productivity, efficiency, and equipment reliability in organizations. It focuses on empowering employees at all levels to take ownership of equipment, processes, and workplace practices to minimize downtime, reduce waste, and enhance overall performance.

Who should attend?

  • Production & Operations Managers
  • Maintenance Engineers & Technicians
  • Quality Managers & Supervisors
  • Plant Heads & Manufacturing Leaders
  • Health & Safety Officers
  • Lean Six Sigma & Continuous Improvement Teams

Overview of TPM:

  • What is TPM?
  • TPM Principles and it support to Lean Transformation
  • Zero BAD (Breakdown, Accident and Defect) concept.
  • TPM Policies, Goals and Eight Pillars of TPM
  • TPM Organisation structure

TPM Foundations: 5S & Visual Management

  • 5S Principles, Sort: Identifying Red-tag Targets
  • Sort: Disposal Methods, Set In Order: Making Things Easy to Find
  • Shine – Practice Tips & Check Sheet
  • TPM Manager Model Machine and Kick off
  • 5S & Equipment Maintenance
  • Visual Control management

TPM Tools:

  • Small Group Activities
  • Suggestion System and Kaizen
  • Proactive and Reactive approach
  • SMED, VTR study (Video Tape Recording) One-Point Lesson and Activity Board
  • Loss tree/Cost tree analysis
  • Tag register, SOC (Source of Contamination) and HTA (Hard to Access) areas

8 Pillars of TPM & Pillar Management:

  • Autonomous Maintenance
  • Planned Maintenance
  • Focused Improvement
  • Education & Training
  • Early Equipment Management
  • Quality Maintenance
  • Office TPM
  • Safety, Health & Environment

Equipment Loss & Overall Equipment Effectiveness:

  • 3 Key Components of OEE
  • Six Big Equipment Losses
  • Equipment Losses & OEE
  • Breakdown Losses
  • 16 losses in TPM
  • Setup & Adjustment Losses, Minor Stoppage Losses
  • Speed Loss, Quality Defect & Rework Losses
  • Start-up (Yield) Losses
  • Strategies for Zero Breakdowns (downtime)

TPM Implementation:

  • TPM Implementation Master Plan
  • Example of TPM Implementation Structure
  • Roles and Responsibilities of the team
  • 12 Steps of TPM Implementation method
  • How to Sustain TPM and Critical Success Factors

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