Introduction to AI in Smart Factories and Industrial Automation Training Course

The Allen Bradley platform serves as a prominent industrial automation ecosystem, enabling professionals to configure, control, and integrate PLCs, HMIs, and various networked devices.

This instructor-led training, available both online and onsite, targets intermediate-level automation experts seeking to interconnect and integrate Allen Bradley devices via Ethernet for seamless communication across PLCs, HMIs, servers, and routers.

Upon completing this training, participants will be equipped to:

• Configure Ethernet-based communication within the Allen Bradley ecosystem.
• Integrate PLCs, HMIs, servers, and routers using standard communication protocols.
• Deploy practical network topologies for automation systems.
• Troubleshoot connectivity and data exchange challenges.

Course Format

• Guided instruction with demonstrations using Allen Bradley tools.
• Hands-on integration exercises involving Ethernet-connected devices.
• Practical configuration and testing in a live-lab setting.

Customization Options

• Tailored training sessions can be organized based on specific device models or network architectures.

This instructor-led, live training in Nigeria (online or on-site) is aimed at beginner to intermediate-level engineers and technicians who wish to master the fundamentals of AB PLCs and apply them to real-world manufacturing scenarios.

By the end of this training, participants will be able to:

• Understand the role and applications of AB PLCs in the manufacturing industry.
• Program AB PLCs using RSLogix 5000/Studio 5000.
• Troubleshoot common issues and perform maintenance on PLC systems.
• Design and implement a PLC-controlled system for a manufacturing process.
• Demonstrate proficiency in PLC programming through a practical project.

AI-powered predictive maintenance leverages machine learning and data analytics to anticipate equipment failures and optimize maintenance schedules. It shifts organizations from reactive maintenance models to proactive strategies, resulting in improved uptime, reduced costs, and extended asset lifespan.

This instructor-led live training (available online or onsite) is designed for intermediate-level professionals seeking to implement AI-driven predictive maintenance solutions within industrial environments.

Upon completing this training, participants will be able to:

• Distinguish predictive maintenance from reactive and preventive maintenance strategies.
• Collect and structure machine data for AI-driven analysis.
• Apply machine learning models to detect anomalies and predict failures.
• Implement end-to-end workflows transforming sensor data into actionable insights.

Course Format

• Interactive lectures and discussions.
• Hands-on exercises and case studies.
• Live demonstrations and practical data workflows.

Customization Options

• To request customized training for this course, please contact us to make arrangements.

AI for Process Optimization involves applying machine learning and data analytics to boost efficiency, quality, and throughput within manufacturing operations.

This instructor-led live training, available both online and onsite, is designed for intermediate-level manufacturing professionals aiming to utilize AI techniques to streamline operations, minimize downtime, and foster continuous improvement initiatives.

Upon completing this training, participants will be able to:

• Grasp AI concepts pertinent to manufacturing optimization.
• Gather and prepare production data for analysis.
• Deploy machine learning models to pinpoint bottlenecks and predict potential failures.
• Visualize and interpret results to facilitate data-driven decision-making.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical practice.
• Hands-on implementation within a live laboratory environment.

Customization Options for the Course

• To request a customized training for this course, please contact us to arrange.

AI-driven quality control involves applying computer vision and machine learning to detect defects, anomalies, and deviations within production workflows.

This instructor-led training, available either online or onsite, is designed for beginner to intermediate quality professionals seeking to utilize AI tools for automating inspections and enhancing product quality in manufacturing settings.

Upon completion of this course, participants will be equipped to:

• Grasp the application of AI in industrial quality control.
• Gather and annotate image or sensor data from manufacturing lines.
• Employ machine learning and computer vision techniques to identify defects.
• Construct basic AI models for anomaly detection and yield forecasting.

Course Format

• Engaging lectures and discussions.
• Extensive exercises and practical practice.
• Hands-on implementation within a live laboratory environment.

Customization Options

• For tailored training requests, please reach out to us to make arrangements.

AI in Supply Chain and Manufacturing Logistics is the application of predictive analytics, machine learning, and automation to optimize inventory, routing, and demand forecasting.

This instructor-led, live training (online or onsite) is aimed at intermediate-level supply chain professionals who wish to apply AI-driven tools to enhance logistics performance, forecast demand accurately, and automate warehouse and transport operations.

By the end of this training, participants will be able to:

• Understand how AI is applied across logistics and supply chain activities.
• Use machine learning models for demand forecasting and inventory control.
• Analyze routes and optimize transport using AI-based techniques.
• Automate decision-making in warehouses and fulfillment processes.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Implementing AI Use Cases is a hands-on, project-based methodology for applying machine learning, computer vision, and data analytics to address real-world industrial challenges using actual or simulated datasets.

This instructor-led, live training (available online or onsite) is designed for intermediate-level cross-functional teams who want to collaboratively deploy AI solutions aligned with their operational goals and gain practical experience with industrial data pipelines.

By the conclusion of this training, participants will be able to:

• Identify and scope practical AI applications within operations, quality, or maintenance.
• Collaborate across different roles to build machine learning solutions.
• Manage, clean, and analyse diverse industrial datasets.
• Present a functional prototype of an AI-enabled solution based on a chosen application.

Course Format

• Interactive lectures and discussions.
• Group exercises and project work.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request customized training for this course, please contact us to arrange.

CANoe is a robust software solution created by Vector, designed for the development, testing, and analysis of in-vehicle networks and ECUs, particularly those operating on the CAN (Controller Area Network) protocol.

This instructor-led live training (available online or onsite) targets beginner to intermediate automotive engineers and testers who want to utilize CANoe to simulate, test, and analyze CAN-based communication systems.

Upon completion of this training, participants will be able to:

• Install and set up CANoe along with its associated components
• Grasp the fundamentals of the CAN protocol and message framing
• Develop simulations for ECUs and CAN networks using CAPL scripting
• Effectively monitor, analyze, and debug CAN traffic

Digital Twins serve as virtual representations of physical systems, augmented by live data and artificial intelligence-driven insights.

This trainer-led course, available either online or in-person, is designed for mid-level professionals looking to construct, implement, and refine digital twin models leveraging real-time data and AI-based analytics.

Upon completion of this training, attendees will be capable of:

• Grasping the structure and key elements of digital twins.
• Utilising simulation software to represent complex systems and environments.
• Merging live data feeds into virtual models.
• Applying AI methods for predicting outcomes and identifying anomalies.

Course Format

• Engaging lectures and group discussions.
• Numerous exercises and practical sessions.
• Practical implementation within a live-lab setting.

Customisation Options

• For tailored training requests, please reach out to us to make arrangements.

Edge AI involves deploying artificial intelligence models directly onto devices and machinery at the network's edge, facilitating real-time decision-making with minimal latency.

This instructor-led, live training (available online or onsite) targets advanced-level embedded and IoT professionals looking to implement AI-driven logic and control systems in manufacturing settings where speed, reliability, and offline operation are paramount.

Upon completing this training, participants will be capable of:

• Grasp the architecture and advantages of edge AI systems.
• Construct and refine AI models for deployment on embedded devices.
• Utilize tools such as TensorFlow Lite and OpenVINO for low-latency inference.
• Merge edge intelligence with sensors, actuators, and industrial protocols.

Course Format

• Interactive lectures and discussions.
• Numerous exercises and practical practice sessions.
• Hands-on implementation within a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

The integration of AI into industrial computer vision is reshaping how manufacturers and quality assurance teams identify surface defects, verify part conformity, and automate visual inspection processes.

This instructor-led live training, available both online and onsite, targets intermediate to advanced-level QA teams, automation engineers, and developers who aim to design and deploy computer vision systems for defect detection and inspection using AI techniques.

Upon completing this training, participants will be equipped to:

• Comprehend the architecture and key components of industrial vision systems.
• Construct AI models for visual defect detection utilizing deep learning.
• Integrate real-time inspection pipelines with industrial cameras and devices.
• Deploy and optimize AI-powered inspection systems within production environments.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request customized training for this course, please contact us to arrange it.

This instructor-led, live training session (available online or onsite) is designed for intermediate-level automation engineers and control system designers who aim to implement motion control solutions using Omron PLCs.

By the end of this training, participants will be able to:

• Understand fundamental motion control concepts and their applications.
• Configure motion hardware and software in Sysmac Studio.
• Program and optimize single-axis and multi-axis motion control.
• Implement coordinated motion strategies, including interpolation and synchronization.

This instructor-led, live training in Nigeria (online or onsite) is aimed at automation engineers and control system designers who wish to configure, program, and commission Omron Sysmac systems covering NJ/NX controllers, EtherCAT networking, G5/1S/1SA servo drives, NA Series HMI, and NX safety hardware.

This course provides learners with an understanding of Programmable Logic Controllers (PLC) fundamentals. Following an exploration of core PLC concepts, students will learn and apply essential Ladder Diagram instructions to solve Industrial Automation challenges. Target Audience: Electrical Specialists, Mechanical Engineers, and Programmers interested in Industrial Automation.

Smart Robotics involves the integration of artificial intelligence into robotic systems to enhance perception, decision-making, and autonomous control.

This instructor-led live training (available online or onsite) targets advanced robotics engineers, systems integrators, and automation leads who wish to implement AI-driven perception, planning, and control in smart manufacturing environments.

By the end of this training, participants will be able to:

• Understand and apply AI techniques for robotic perception and sensor fusion.
• Develop motion planning algorithms for collaborative and industrial robots.
• Deploy learning-based control strategies for real-time decision making.
• Integrate intelligent robotic systems into smart factory workflows.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.