Digital Manufacturing and Industry 4.0 Technologies

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Course provided by Model Institute of Engineering & Technology

7 modules

Explore the fundamentals of Cyber Security

5.5 Level NCrF 

National Credit Framework

90 Hours 

Flexible Learning

Beginner Level 

No prior experience required

Certificate Program

03 Credits

Course Overview

This course introduces learners to the principles and practices of Digital Manufacturing within the Industry 4.0 ecosystem. Students gain the ability to model and assess value chains, leverage CAD, Digital Twins, and simulation tools for intelligent design, and utilize sensor data with IIoT for real-time decision-making. The program also explores digital transformation use cases in supply chains, smart factories, and process optimization, preparing learners to drive efficiency and innovation in modern manufacturing.

Key Learning Highlights

  • Explore the role of Digital Manufacturing in Industry 4.0 and its impact on modern enterprises.
  • Model and analyze value chains using strategic frameworks like Porter’s model.
  • Apply CAD, Digital Twin, and simulation tools for smart product design and prototyping.
  • Leverage IIoT and sensor-driven data for real-time decision-making in manufacturing.
  • Study industry case studies on supply chain digitalization, smart shops, and process optimization.

Tools & Platform Used

Learning Outcome

By the end of this course, students will be able to:

  • Explain the role of Digital Manufacturing within the Industry 4.0 ecosystem.
  • Model and evaluate value chains using strategic frameworks.
  • Apply CAD, Digital Twin, and simulation tools for design and prototyping.
  • Use IIoT and sensor data for real-time decision-making in manufacturing.
  • Analyze digital transformation case studies in supply chains and smart factories.

Master the course with just 7 Modules

The course begins with an introduction to Digital Manufacturing, its evolution, benefits, and challenges, followed by the foundations of Industry 4.0, including smart factories, cyber-physical systems, digital threads, and twins. Learners gain hands-on exposure to CAD tools and virtual prototyping for design and simulation, along with value chain mapping using Porter’s model and digital workflows. The course further explores IIoT and sensor integration for real-time data, cloud platforms, and AI-driven analytics for predictive manufacturing. Finally, real-world case studies from automotive, heavy industry, and Supply Chain 4.0 demonstrate practical applications of digital transformation in manufacturing ecosystems.

Introduction to Digital Manufacturing

  • Understand the evolution of manufacturing from manual to Industry 4.0.

  • Explore key benefits such as cost reduction, efficiency, and customization.

  • Examine challenges like high investment, integration, and skill requirements.

  • Learn about smart factories and their role in connected production.

  • Understand cyber-physical systems, digital threads, and digital twins.

  • Explore adaptive manufacturing ecosystems and interoperability.

  • Apply CAD tools for product design and rapid iterations.

  • Use simulation environments for performance validation before manufacturing.

  • Optimize product development through virtual prototyping techniques.

  • Study Porter’s model to identify and optimize value-creating activities.
  • Analyze digital value chains for improved efficiency and collaboration.
  • Understand digital workflows that streamline business processes.

  • Learn about IIoT device architecture and sensor technologies.

  • Explore layered communication systems for real-time industrial data.

  • Apply sensor integration for monitoring and smart decision-making.

  • Understand the role of cloud platforms for data storage and sharing.
  • Use AI and analytics for predictive maintenance and smart systems.
  • Explore integration of cloud and AI in digital manufacturing processes.

  • Examine digital transformation in automotive and heavy industries.

  • Explore real-world adoption of smart technologies in manufacturing.

  • Study Supply Chain 4.0 practices for efficiency, visibility, and agility.

Roles

  • Digital Manufacturing Engineer
  • Industry 4.0 Specialist
  • CAD/CAM Engineer
  • Simulation & Digital Twin Engineer
  • IIoT Engineer
  • Smart Factory Analyst
  • Automation Engineer
  • Supply Chain Digital Transformation Specialist

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