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Manufacturing
Industrial Internet of Things (IIoT) in Manufacturing Training Course
Introduction
The Industrial Internet of Things in Manufacturing Training Course is designed to equip professionals with cutting-edge skills in smart manufacturing, Industry 4.0 transformation, predictive analytics, and connected industrial systems. As global industries rapidly shift toward automation and data-driven operations, IIoT has become a core enabler of intelligent factories, real-time monitoring, and operational efficiency optimization.
This course provides a deep dive into sensor integration, industrial connectivity protocols, edge and cloud computing, AI-powered predictive maintenance, and digital twin technologies. Participants will learn how to design, implement, and manage scalable IIoT ecosystems that enhance productivity, reduce downtime, improve asset utilization, and strengthen cyber-physical production systems (CPPS) in modern manufacturing environments.
Programme Curriculum
Industrial Internet of Things (IIoT) in Manufacturing Training Course
Introduction
The Industrial Internet of Things in Manufacturing Training Course is designed to equip professionals with cutting-edge skills in smart manufacturing, Industry 4.0 transformation, predictive analytics, and connected industrial systems. As global industries rapidly shift toward automation and data-driven operations, IIoT has become a core enabler of intelligent factories, real-time monitoring, and operational efficiency optimization.
This course provides a deep dive into sensor integration, industrial connectivity protocols, edge and cloud computing, AI-powered predictive maintenance, and digital twin technologies. Participants will learn how to design, implement, and manage scalable IIoT ecosystems that enhance productivity, reduce downtime, improve asset utilization, and strengthen cyber-physical production systems (CPPS) in modern manufacturing environments.
Course Duration
5 days
Course Objectives
Understand Industry 4.0 architecture and IIoT ecosystem frameworks
Implement smart sensors and industrial data acquisition systems
Master PLC, SCADA, and OPC UA integration in manufacturing systems
Apply MQTT and industrial communication protocols for real-time data flow
Develop skills in edge computing and fog computing for low-latency processing
Enable predictive maintenance using AI and machine learning models
Build and manage cloud-based IIoT platforms (AWS IoT, Azure IoT)
Design digital twin models for production simulation and optimization
Strengthen knowledge of OT/IT convergence in smart factories
Implement industrial cybersecurity and IIoT risk mitigation strategies
Optimize production using real-time analytics and big data in manufacturing
Deploy automation systems for smart factory transformation
Enhance decision-making through data-driven manufacturing intelligence
Target Audience
Manufacturing Engineers
Automation & Control Engineers
Industrial IoT Developers
Plant Managers & Operations Managers
Data Analysts in Manufacturing
Maintenance & Reliability Engineers
IT/OT Integration Specialists
Engineering Students & Research Professionals
Course Modules
Module 1: Introduction to IIoT & Smart Manufacturing
Industry 4.0 evolution and smart factory concepts
IIoT architecture layers and ecosystem components
Cyber-Physical Systems (CPS) in manufacturing
Industrial transformation from automation to autonomy
Real-time data-driven production systems
Case Study: A automotive plant reduces downtime by 35% using IIoT-based monitoring of assembly lines.
Module 2: Industrial Sensors & Data Acquisition Systems
Types of industrial IoT sensors (temperature, vibration, pressure)
PLC integration with sensor networks
SCADA systems for industrial monitoring
Data acquisition and signal processing techniques
OPC UA for interoperability
Case Study: A food processing factory improves quality control using real-time sensor-based temperature monitoring.
Module 3: Industrial Connectivity & Communication Protocols
MQTT, CoAP, and AMQP protocols in IIoT
Industrial Ethernet and wireless communication systems
5G applications in smart manufacturing
Edge device connectivity setup
Secure machine-to-machine (M2M) communication
Case Study: A textile industry improves production speed by 40% using 5G-enabled IoT machines.
Module 4: Edge Computing & Real-Time Data Processing
Edge vs cloud computing in manufacturing
Fog computing architecture
Low-latency industrial data processing
Edge AI for real-time decision-making
Data filtering and preprocessing at the edge
Case Study: A steel plant reduces defects using edge-based real-time quality inspection systems.
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.