Digital Manufacturing and Industry 4.0 Technologies
Course provided by Model Institute of Engineering & Technology
7 modules
Explore the fundamentals of Cyber Physical Systems
5 Level NCrF
National Credit Framework
90 Hours
Flexible Learning
Beginner Level
No prior experience required
Diploma Program
03 Credits
Course Overview
This course introduces learners to Digital Manufacturing within the Industry 4.0 ecosystem, focusing on smart production, value chain optimization, and real-time decision-making. Participants learn to model and evaluate industrial value chains using frameworks like Porter’s model, and leverage CAD, Digital Twins, and simulation tools for design and prototyping. The curriculum integrates IIoT and sensor data for monitoring and optimizing manufacturing processes. Real-world case studies highlight digital transformation in supply chains, smart factories, and process optimization, equipping learners to drive innovation and efficiency in modern manufacturing systems.
Key Learning Highlights
Explore Digital Manufacturing principles within the Industry 4.0 ecosystem.
Model and evaluate industrial value chains using Porter’s framework.
Apply CAD, Digital Twins, and simulation tools for smart design and prototyping.
Utilize IIoT and sensor data for real-time monitoring and decision-making.
Analyze digital transformation use-cases in supply chains, smart shops, and process optimization.
Tools & Platform Used
Learning Outcome
By the end of this course, learners will be able to:
Explain the role of Digital Manufacturing in modern industrial systems.
Model and assess value chains to identify opportunities for efficiency improvements.
Design and prototype products using CAD, Digital Twins, and simulation tools.
Integrate IIoT and sensor data into manufacturing workflows for informed decision-making.
Evaluate real-world examples of digital transformation in factories, supply chains, and smart shops.
Master the course with just 7 Modules
This course guides learners through the foundations and applications of Digital Manufacturing in Industry 4.0. Starting with an introduction to digital manufacturing, its evolution, benefits, and challenges, learners then explore smart factories, cyber-physical systems, digital threads, and digital twins. The curriculum covers CAD tools and virtual prototyping for design optimization, value chain mapping using Porter’s model, and IIoT sensor integration for real-time data-driven decisions. Advanced modules include cloud platforms and AI for predictive analytics and decision-making, culminating in case studies highlighting digital transformation across automotive, heavy industry, and supply chain environments.
Introduction to Digital Manufacturing
- Overview of digital manufacturing principles and evolution from traditional methods.
- Benefits such as cost reduction, efficiency, and customization.
- Challenges including high investment and skill requirements.
Industry 4.0 Foundations
- Smart factories, cyber-physical systems (CPS), digital threads, and digital twins.
- Integration of connected, intelligent, and adaptive manufacturing ecosystems.
- Role of Industry 4.0 technologies in transforming production processes.
CAD Tools and Virtual Prototyping
- Rapid design iteration and optimization of products before physical manufacturing.
- Simulation environments for testing performance and feasibility.
- Enhancing efficiency and reducing errors in prototyping and design.
Value Chain Mapping
Analysis of industrial processes using Porter’s model.
Digital workflows to enhance collaboration and streamline operations.
Identifying key areas for efficiency improvement across value chains.
IIoT and Sensor Integration
- Device architecture and communication layers for industrial IoT.
- Real-time data collection, transmission, and analysis for manufacturing systems.
- Improving decision-making and predictive maintenance through sensor integration.
Cloud Platforms & AI in Manufacturing
- Storing and analyzing industrial data using cloud platforms.
- Implementing AI for predictive analytics and intelligent decision-making.
- Leveraging digital tools for optimization and proactive maintenance.
Case Studies
- Real-world examples from automotive and heavy industry digital transformation.
- Supply Chain 4.0 applications to enhance visibility, efficiency, and responsiveness.
- Lessons learned and best practices for scaling digital manufacturing solutions.
Roles
- Digital Manufacturing Engineer
- Industry 4.0 Consultant
- Smart Factory Analyst
- IIoT Integration Specialist
- Manufacturing Process Optimization Engineer
- Automation and Robotics Engineer
