Industry 4.0 Curriculum

Smart manufacturing and Industry 4.0 are a huge shift in how industrial processes work. While the core skills are similar, the introduction of new advanced technologies, the extensive use of communications, advanced integration, and modern software and computing capabilities changes the environment significantly.

Technicians, operators, engineers and managers need to upskill and be proficient in additional areas of expertise specific to Industry 4.0.

Intelitek Industry 4.0 Curriculum offer learners expertise in the broader ecosystem as well as new Industry 4.0 technology innovations.

  • Introductory to advanced curriculum focused on Industry 4.0 concepts and technology
  • Provides students detailed knowledge of how Industry 4.0 will affect their role and work environment
  • Students will understand and learn the benefits of smart maintenance, operational efficiency, remote monitoring and flexible mass production.

Intelitek Smart Series curriculum augment existing advanced manufacturing programs introducing students in different roles to Industry 4.0 theories and technology.

  • Tiered program for technician, operator and integrator level students
  • Specialized curriculum can augment existing advanced manufacturing training programs
  • Instructor led or self paced learning programs include instructor aids, class management, assessments and hands-on labs
  • Aligned to emerging Industry 4.0 Certifications

Level 1

Introduction to Industry 4.0 offers a window into the impact of the Fourth Industrial Revolution and its accompanying technologies on the modern manufacturing industry. Using examples and analogies from real-world enterprises, the course explores Industry 4.0 concepts, processes, and technologies, and testifies to how these components interconnect together in order to grow the manufacturing industry of the future.

Course Outline

  • What is Industry 4.0?
  • Technologies that Drive Industry 4.0
  • Challenges for Industry 4.0
  • Quality 4.0
  • Supply Chain 4.0
  • Data Standardization
  • Internet and Ethernet
  • The Internet of Things
  • Industrial Control Systems and IIoT
  • Big Data
  • Automation & Software Technologies
  • VR, AR, and AI
  • Maintenance 4.0
  • Flexible Production
  • Maturity Models for Industry 4.0

Introduction to the Internet of Things and Connectivity focuses on the vast network of smart sensors and devices and their impact on the manufacturing world. This course also explores topics related to the interconnection of IoT and industrial devices, such as SCADA systems, cloud computing, edge computing, and machine vision systems.

Course Outline

  • Introduction to Sensors, Smart Sensors, and Actuators
  • Introduction to PLCs
  • IoT and IIoT
  • IIoT Opportunities, Risks, and Challenges
  • The Potential of Connectivity in IIoT
  • How a Sensor Connects to the Cloud
  • Introduction to Edge Computing
  • SCADA Systems
  • Vision Systems
  • Architecture of Smart Manufacturing Systems
  • Introduction to Communication Protocols
  • Tracking Methods


Overview of networking and cyber-security in IT / OT systems, including network fundamentals, identification of cyber threats and cyber-protection.

Course Outline

  • Introduction to Digital Manufacturing
  • Basics of Data Networking
  • Cyber Awarence
  • Cyber Attacks
  • IIoT Cybersecurity Basics
  • Cloud Security Basics
  • Federal Cybersecurity Resources


The curriculum explores the modern world of data, including its collection, processing, management, visualization, and ultimately, its uses. The course also delves into big data implementation in cutting-edge manufacturing, and machine learning, predictive analytics, modeling, simulation, improvement of processes and progress indicators.

Course Outline

  • Introduction to Big Data
  • Characteristics of Big Data and Dimensions of Scalability
  • Intelligent Decision Making and Getting Value Out of Big Data
  • Data Collection and Management
  • Algorithms, Computing, and Descriptive Statistics
  • Data Analysis
  • Visualization of Data
  • Predictive Analytics and Modeling
  • Machine Learning
  • Introduction to KPIs
  • Improving KPIs with Big Data
  • Database Fundamentals
  • Data Warehousing
  • Data Mining
  • Cloud Computing for Big Data
  • Data-Driven Innovation

Level 2

Advanced course covering the Architecture and Protocols of Industry 4.0 systems

Prerequisite: Intro to Industry 4.0 (lvl 1)

Course Outline

  • Components & architecture of I4.0 systems
  • Integrated systems approach
  • Diversified Manufacturing techniques
  • CyberPhysical Systems (Cloud, Simulation, Twinning, VR/AR, Digital Twinning)
  • Digitization (Smart sensors, IoT, Asset/ Inventory tracking)

Advanced IIoT and Connectivity for Industry 4.0 focuses on the vast network of smart sensors and devices that is the Internet of Things (IoT) and how such systems are integrated and deployed in today’s industrial environments.Building on the introductory course, Advanced IIoT and Connectivity delves deeper into the workings of industrial operation technologies (OT) and information technologies (IT).

Prerequisite: Intro to IoT and Connectivity (lvl 1)

Course Outline

  • Smart Sensors – Part 1
  • Smart Sensors – Part 2
  • PLC Functions and Applications
  • Machine to Machine (M2M) Communication
  • Cloud Connectivity – Part 1
  • Cloud Connectivity – Part 2
  • SCADA Systems – Part 1
  • SCADA Systems – Part 2
  • Implementing IoT
  • Design Modularity in Smart Factories
  • Industrial IoT Reference Architecture (IIRA)
  • IoT Protocols and Standards – Part 1
  • IoT Protocols and Standards – Part 2
  • Material Identification – Part 1
  • Material Identification – Part 2
  • Driving Manufacturing with IIoT

Curriculum with Hands-on lab for Cybersecurity focused on how to Identify, Protect, Detect, Respond, & Recover from cyber threats in Industry 4.0 systems

Prerequisite: Intro to Cybersecurity (lvl 1)

Course Outline

  • Recognizing breaches & use of Cyber monitoring tools
  • Basic Firewall Protection Settings
  • Basic Switch protection settings
  • Virusses and Malware
  • Secure provisioning of operating systems, software, and configuring security
    • Lab includes: Configuration and test of firewall, switch
    • Installation of software & security s/w
    • Performing a DoS Attack
    • Hacking a file (flag) in a Remote Network
    • Performing steps to Establish Persistence in a Compromised network or Device

Overview of the Software technologies and applications that transform traditional production lines into Smart Production lines.

Course Outline

  • Industry 4.0 Software Tools and Digital technologies
  • Digital information management
    • System Management ERP – Enterprise Resource Planning systems
    • MES – Manufacturing Execution Systems
    • APS – Advanced supply chain & planning systems
  • System visualization tools Virtual reality
    • Augmented Reality
    • Digital Twinning/Simulation apps
  • AI – Artificial Intelligence and Machine Learning

Level 3

Advanced course covering Data Science concepts and ways to benefit from the info that is collected from a Smart factory system.

Course Outline

  • Data warehousing
  • Data mining
  • Data driven innovation (DDI)
  • One Matrices That Matter (OMTM)
  • KPIs of Big Data
  • Deep Learning & Machine Learning, AI
  • Working with Analytics Kit – lab
  • I. – Deep learning tools – Lab

High level look at the Industry 4.0 Smart manufacturing in industry and the trends and use cases for technology

Course Outline

  • Industry 4.0 – The super infrastructure for the future of manufacturing (market trends)
  • Requirements for a factory to be Industry 4.0 (technology trends)
  • Industry 4.0 and Business processes (Flexible Mass Production) Real time business processes
    • Enhanced customer experience
    • Competitive industrial production
    • Customized mass production
    • Maintaining production (improved reliability/quality)

A look at industry 4.0 from the business perspective. The course will look at the benefits and justifications for manufacturing.

Course Outline

  • Outcomes of Industry 4.0
    • Customer satisfaction
    • Information transparency
    • Customized mass production
    • Intelligent decision making
    • Asset management

Use cases examples (Case Studies)

  • Business with industry 4.0
    • Business 4.0 (business efficiency)
    • Supply chain 4.0
    • Quality 4.0
    • Maintenance 4.0
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