Introduction to AI in Smart Factories and Industrial Automation Training Course

The Allen Bradley platform represents a prevalent industrial automation ecosystem utilized for the configuration, control, and integration of PLCs, HMIs, and networked devices.

This instructor-led live training, available either online or onsite, targets intermediate-level automation professionals seeking to interconnect and integrate Allen Bradley automation devices via Ethernet to achieve seamless communication across PLCs, HMIs, servers, and routers.

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

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

Course Format

• Guided instruction accompanied by demonstrations using Allen Bradley tools.
• Practical integration exercises involving Ethernet-connected devices.
• Real-world configuration and testing conducted in a live-lab environment.

Course Customization Options

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

This instructor-led live training the Netherlands (online or onsite) targets beginner to intermediate-level engineers and technicians seeking 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-driven predictive maintenance leverages machine learning and data analytics to anticipate equipment failures and optimize maintenance scheduling. This approach 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-powered predictive maintenance solutions within industrial settings.

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

• Distinguish between reactive, preventive, and predictive maintenance strategies.
• Collect and structure machine data for effective AI analysis.
• Utilize machine learning models to identify anomalies and predict potential failures.
• Establish end-to-end workflows that transform sensor data into actionable insights.

Course Format

• Interactive lectures and discussions.
• Practical exercises and case studies.
• Live demonstrations with hands-on data workflows.

Customization Options

• To arrange a tailored training session for this course, please contact us directly.

AI for Process Optimization involves leveraging machine learning and data analytics to improve efficiency, quality, and throughput within manufacturing environments.

This instructor-led live training, available either online or on-site, is designed for intermediate-level professionals in the manufacturing sector who aim to utilize AI techniques to streamline operations, minimize downtime, and facilitate continuous improvement efforts.

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

• Comprehending AI concepts applicable to manufacturing optimization.
• Gathering and preparing production data for analytical purposes.
• Implementing machine learning models to detect bottlenecks and forecast failures.
• Visualizing and interpreting outcomes to inform data-driven decision-making.

Format of the Course

• Interactive lectures accompanied by discussions.
• Numerous exercises and practical sessions.
• Practical implementation within a live-lab environment.

Course Customization Options

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

AI-driven quality control leverages computer vision and machine learning algorithms to identify defects, anomalies, and deviations within production processes.

This instructor-led live training, available online or onsite, is designed for beginner to intermediate-level quality professionals seeking to implement AI tools to automate inspections and enhance product quality in manufacturing settings.

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

• Grasp the application of AI in industrial quality control.
• Collect and annotate image or sensor data from production lines.
• Utilize machine learning and computer vision techniques for defect detection.
• Construct simple AI models for anomaly detection and yield forecasting.

Course Format

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

Customization Options

• To arrange customized training for this course, please reach out to us to make the necessary arrangements.

AI in Supply Chain and Manufacturing Logistics involves leveraging predictive analytics, machine learning, and automation to streamline inventory management, optimize routing, and enhance demand forecasting.

This instructor-led live training, available either online or onsite, targets intermediate-level supply chain professionals looking to utilize AI-driven tools to improve logistics performance, achieve accurate demand forecasts, and automate warehouse and transportation operations.

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

• Grasping the application of AI across logistics and supply chain activities.
• Employing machine learning models for demand forecasting and inventory control.
• Analyzing and optimizing transport routes using AI-based methodologies.
• Automating decision-making processes within warehouses and fulfillment operations.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical 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.

AI application implementation follows a hands-on, project-based methodology that applies 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) targets intermediate-level cross-functional teams seeking to collaboratively implement AI applications aligned with their operational goals and gain experience working with industrial data pipelines.

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

• Identify and scope practical AI applications within operations, quality, or maintenance functions.
• Collaborate across different roles to develop machine learning solutions.
• Manage, clean, and analyze varied industrial datasets.
• Deliver a working prototype of an AI-enabled solution based on a selected application.

Course Format

• Interactive lectures and discussions.
• Group-based exercises and project work.
• Practical implementation in a live laboratory environment.

Customization Options for the Course

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

Developed by Vector, CANoe is a robust software solution designed for the development, testing, and analysis of in-vehicle networks and Electronic Control Units (ECUs), with a particular focus on those utilizing the CAN (Controller Area Network) protocol.

This instructor-led live training (available online or onsite) targets automotive engineers and testers ranging from beginner to intermediate levels who aim to leverage CANoe for simulating, testing, and analyzing CAN-based communication systems.

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

• Install and configure CANoe along with its associated components
• Grasp the fundamental concepts of the CAN protocol and message framing
• Develop simulations for ECUs and CAN networks using CAPL scripting
• Monitor, analyze, and debug CAN traffic with high efficiency

Digital Twins serve as virtual representations of physical systems, powered by real-time data and artificial intelligence.

This instructor-led live training, available either online or on-site, targets intermediate professionals seeking to create, deploy, and optimize digital twin models utilizing real-time information and AI-driven insights.

Upon completing this course, participants will be capable of:

• Comprehending the architecture and key components of digital twins.
• Employing simulation tools to model intricate systems and environments.
• Integrating live data streams into virtual models.
• Applying AI techniques for predictive analysis and anomaly detection.

Course Format

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

Customization Options

• For tailored training options, please contact us to arrange.

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

This instructor-led, live training (available online or on-site) is designed for 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 completion of this training, participants will be capable of:

• Grasping the architecture and advantages of edge AI systems.
• Constructing and optimizing AI models for deployment on embedded hardware.
• Utilizing tools such as TensorFlow Lite and OpenVINO for low-latency inference.
• Integrating edge intelligence with sensors, actuators, and industrial protocols.

Course Format

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

Customization Options

• To request customized training for this course, please get in touch with us to arrange.

AI-enhanced industrial computer vision is revolutionizing the way manufacturers and quality assurance teams identify surface defects, verify part compliance, and automate visual inspection workflows.

This instructor-led live training, available online or onsite, is designed for intermediate to advanced quality assurance teams, automation engineers, and developers looking to design and implement computer vision systems for defect detection and inspection using artificial intelligence.

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

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

Course Format

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

Customization Options

• For customized training on this topic, please contact us to make arrangements.

This guided, live training in the Netherlands (available online or on-site) is designed for intermediate-level automation engineers and control system designers aiming to implement motion control solutions with Omron PLCs.

Upon completion 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 the Netherlands (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 an introduction to the fundamentals of Programmable Logic Controllers (PLC). Following a discussion on core PLC concepts, participants will learn and apply basic Ladder Diagram instructions to practical Industrial Automation tasks. Target Audience: Electrical Specialists, Mechanical Engineers, and Programmers interested in Industrial Automation.

Smart Robotics involves integrating artificial intelligence into robotic systems to enhance perception, decision-making capabilities, and autonomous control.

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

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

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

Course Format

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

Customization Options

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