Introduction

The Advanced DMAIC Methodology in Manufacturing Training Course is designed to equip professionals with cutting-edge Lean Six Sigma, process optimization, and data-driven decision-making skills. This training emphasizes the structured DMAIC framework to eliminate defects, reduce variation, and drive continuous improvement in modern manufacturing environments. Participants gain hands-on expertise in statistical process control (SPC), root cause analysis (RCA), value stream mapping (VSM), and real-time production analytics, enabling them to lead high-impact operational excellence projects across diverse industrial settings.

In today’s competitive manufacturing landscape, organizations demand professionals who can deliver cost reduction, product quality enhancement, and process efficiency improvements using advanced methodologies. This course integrates Industry 4.0 principles, smart manufacturing tools, and lean production systems to build mastery in solving complex production challenges. Learners will work on real-world case studies from automotive, FMCG, pharmaceutical, and heavy engineering sectors to develop actionable improvement strategies that align with global quality standards such as ISO 9001, IATF 16949, and Six Sigma Black Belt practices

Programme Curriculum

Advanced DMAIC Methodology in Manufacturing Training Course

Introduction

Course Duration

10 days

Course Objectives

Master Advanced DMAIC Lean Six Sigma Framework
Apply Statistical Process Control (SPC) in Manufacturing
Conduct Root Cause Analysis (RCA) for Defect Elimination
Implement Continuous Process Improvement Strategies
Optimize Manufacturing Cycle Time Reduction Techniques
Enhance Production Yield and Quality Performance Metrics
Utilize Data Analytics for Process Optimization
Develop expertise in Lean Manufacturing Waste Reduction (7 Wastes)
Improve Operational Efficiency using Value Stream Mapping
Strengthen Quality Control and Assurance Systems
Deploy Industry 4.0 Smart Manufacturing Tools
Achieve Cost Optimization and Productivity Enhancement
Lead Cross-Functional Process Improvement Projects

Target Audience

Manufacturing Engineers
Quality Assurance / Quality Control Managers
Production Supervisors & Plant Managers
Industrial Engineers
Lean Six Sigma Practitioners
Operations Managers
Process Improvement Consultants
Supply Chain & Production Planning Professionals

Course Modules

Module 1: Introduction to DMAIC & Lean Six Sigma

DMAIC framework fundamentals
Lean manufacturing principles
Six Sigma overview
Manufacturing quality evolution
KPI-based performance systems
Case Study: Reducing defect rates in an automotive assembly line

Module 2: Define Phase - Problem Identification

Problem statement development
Project charter creation
VOC (Voice of Customer) analysis
CTQ (Critical to Quality) mapping
Stakeholder alignment
Case Study: Defining bottlenecks in FMCG packaging process

Module 3: Measure Phase - Data Collection Systems

Data collection planning
Measurement system analysis (MSA)
Process capability analysis
Baseline performance metrics
Sampling techniques
Case Study: Measuring production variation in textile manufacturing

Module 4: Statistical Process Control (SPC)

Control charts (X-bar, R, P charts)
Process stability analysis
Variation monitoring
Outlier detection
Real-time quality tracking
Case Study: SPC implementation in pharmaceutical production

Module 5: Analyze Phase - Root Cause Analysis

Fishbone diagram (Ishikawa)
5 Whys technique
Pareto analysis
Hypothesis testing
Failure mode identification
Case Study: Analyzing downtime in metal fabrication plant

Module 6: Hypothesis Testing & Statistical Tools

T-tests and ANOVA
Regression analysis
Correlation studies
Data validation methods
Experimental design basics
Case Study: Quality variation in injection molding process

Module 7: Improve Phase -Solution Development

Brainstorming techniques
Kaizen implementation
Lean improvement tools
Pilot testing methods
Risk assessment
Case Study: Improving throughput in beverage production line

Module 8: Lean Manufacturing Optimization

7 wastes elimination
Just-in-Time (JIT) production
Kanban systems
5S workplace organization
Flow optimization
Case Study: Lean transformation in electronics assembly plant

Module 9: Value Stream Mapping (VSM)

Current state mapping
Future state design
Bottleneck identification
Lead time reduction
Process flow analysis
Case Study: VSM in automotive supply chain

Module 10: Control Phase - Sustainability Systems

Control plans development
SOP standardization
Audit mechanisms
KPI dashboards
Continuous monitoring
Case Study: Sustaining quality in food processing industry

Module 11: Advanced Quality Management Systems

ISO 9001 integration
IATF 16949 standards
Compliance frameworks
Documentation control
Audit readiness
Case Study: QMS implementation in auto component manufacturing

Module 12: Industry 4.0 in Manufacturing

Smart factory concepts
IoT in production
AI-based quality control
Predictive maintenance
Digital transformation
Case Study: Smart manufacturing in robotic assembly line

Module 13: Production Cost Optimization

Cost of poor quality (COPQ)
Resource utilization analysis
Energy efficiency improvement
Waste cost reduction
Budget optimization
Case Study: Cost reduction in steel manufacturing plant

Module 14: Advanced Data Analytics in Manufacturing

Big data applications
Dashboard reporting tools
Predictive analytics
Machine learning basics
Real-time monitoring systems
Case Study: Predicting machine failure in CNC operations

Module 15: Capstone DMAIC Project

End-to-end DMAIC execution
Cross-functional collaboration
Real industrial problem solving
Performance evaluation
Final presentation & reporting
Case Study: End-to-end defect elimination in automotive OEM plant

Training Methodology

This course employs a participatory and hands-on approach to ensure practical learning, including:

Interactive lectures and presentations.
Group discussions and brainstorming sessions.
Hands-on exercises using real-world datasets.
Role-playing and scenario-based simulations.
Analysis of case studies to bridge theory and practice.
Peer-to-peer learning and networking.
Expert-led Q&A sessions.
Continuous feedback and personalized guidance.

Register as a group from 3 participants for a Discount

Send us an email: info@fineskilltrainingcenter.org or call +254769199797

Certification

Upon successful completion of this training, participants will be issued with a globally- recognized certificate.

Tailor-Made Course

We also offer tailor-made courses based on your needs.

Key Notes

a. The participant must be conversant with English.

b. Upon completion of training the participant will be issued with an Authorized Training Certificate

c. Course duration is flexible and the contents can be modified to fit any number of days.

d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.

e. One-year post-training support Consultation and Coaching provided after the course.

f. Payment should be done at least a week before commence of the training, to Fineskill Training Center account, as indicated in the invoice so as to enable us prepare better for you.

Skills & Software Covered

Process improvement Six Sigma tools Data-driven analysis Quality optimization

Programme Fee

Duration: 10 Days

Method: Online or Physical

Online Price: $2,000

Physical Price: $3,000

Certification: Accredited Certificate

View Available Dates 📄 Download Course Outline (PDF)

Available Sessions

Location

Month

Year

Oct 19 2026

19 Oct — 30 Oct 2026

💻 Online / Virtual session

Online $2,000