Introduction to AI in Smart Factories and Industrial Automation Training Course

The Allen Bradley platform represents a prominent industrial automation ecosystem designed for configuring, controlling, and integrating PLCs, HMIs, and networked devices.

This instructor-led live training, available either online or onsite, targets intermediate-level automation professionals seeking to connect and integrate Allen Bradley automation devices using Ethernet to ensure seamless communication among 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 using standard communication protocols.
• Deploy real-world network topologies for automation systems.
• Troubleshoot connectivity and data exchange issues between devices.

Course Format

• Guided instruction accompanied by demonstrations using Allen Bradley tools.
• Hands-on integration exercises involving Ethernet-connected devices.
• Practical configuration and testing within a live-lab environment.

Course Customization Options

• Bespoke training versions can be arranged based on specific device models or network architectures.

This instructor-led, live training in Italy (online or onsite) is designed for beginner to intermediate 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-driven predictive maintenance leverages machine learning and data analytics to anticipate equipment failures and optimize maintenance schedules. It shifts maintenance strategies from reactive to proactive, enhancing uptime, reducing costs, and extending 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 in industrial settings.

Upon completing this training, participants will be able to:

• Distinguish predictive maintenance from reactive and preventive strategies.
• Gather and organize machine data for AI analysis.
• Utilize machine learning models to identify anomalies and predict failures.
• Develop complete workflows from sensor data to actionable insights.

Training Format

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

Customization Options

• For customized training arrangements, please contact us.

AI-driven process optimization involves applying machine learning algorithms and data analytics to boost efficiency, improve quality, and increase throughput within manufacturing environments.

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

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

• Grasp the AI concepts essential for manufacturing optimization.
• Gather and ready production data for in-depth analysis.
• Deploy machine learning models to pinpoint bottlenecks and anticipate failures.
• Visualize and interpret outcomes to facilitate data-informed decision-making.

Course Format

• Engaging lectures paired with interactive discussions.
• Extensive practical exercises and hands-on practice.
• Live-lab implementation for real-world application.

Customization Options

• For personalized training needs regarding this course, please reach out to us to make arrangements.

AI-driven Quality Control leverages computer vision and machine learning methodologies to identify defects, anomalies, and deviations within production processes.

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

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

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

Course Format

• Engaging lectures paired with interactive discussions.
• Extensive exercises and practical practice.
• Hands-on implementation within a live-lab environment.

Customization Options

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

AI in Supply Chain and Manufacturing Logistics leverages predictive analytics, machine learning, and automation to optimize inventory levels, routing efficiency, and demand forecasting.

This instructor-led live training (available online or onsite) is designed for intermediate-level supply chain professionals looking to apply AI-driven tools to improve logistics performance, forecast demand with greater accuracy, 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.

This workshop offers a hands-on, project-oriented methodology for applying machine learning, computer vision, and data analytics to address real-world industrial challenges, utilizing either live or simulated datasets.

Designed as an instructor-led live session (available online or on-site), this training targets intermediate-level cross-functional teams seeking to collaboratively implement AI initiatives aligned with their operational objectives while gaining practical experience with industrial data pipelines.

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

• Identify and define practical AI use cases within operations, quality assurance, or maintenance.
• Collaborate effectively across different roles to engineer machine learning solutions.
• Manage, clean, and analyze a variety of industrial datasets.
• Develop and present a functional AI-enabled prototype based on a chosen use case.

Course Format

• Interactive lectures and discussions.
• Collaborative exercises and group project work.
• Practical implementation within a live laboratory environment.

Customization Options

• To request a customized version of this course, please get in touch with us to arrange.

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

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

Upon completing this training, participants will be able to:

• Install and configure 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
• Monitor, analyze, and debug CAN traffic efficiently

Digital Twins are virtual replicas of physical systems enhanced by real-time data and AI-driven intelligence.

This instructor-led, live training (online or onsite) is aimed at intermediate-level professionals who wish to build, deploy, and optimize digital twin models using real-time data and AI-based insights.

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

• Understand the architecture and components of digital twins.
• Use simulation tools to model complex systems and environments.
• Integrate real-time data streams into virtual models.
• Apply AI techniques for predictive behavior and anomaly detection.

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.

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

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

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

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

Course Format

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

Customization Options

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

Artificial intelligence is revolutionizing industrial computer vision, enabling manufacturers and quality assurance teams to detect surface defects, verify part conformity, and automate visual inspection processes more effectively.

This instructor-led live training, available both online and onsite, is designed for QA teams, automation engineers, and developers at the intermediate to advanced level who aim to design and implement AI-driven computer vision systems for defect detection and inspection.

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

• Gaining a clear understanding of the architecture and key components of industrial vision systems.
• Developing AI models for visual defect detection using deep learning techniques.
• Integrating real-time inspection pipelines with industrial cameras and hardware.
• Deploying and optimizing AI-powered inspection systems within production environments.

Course Format

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

Customization Options

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

This instructor-led, live training in Italy (online or onsite) is aimed at intermediate-level automation engineers and control system designers who wish 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 Italy (online or onsite) is aimed at intermediate-level programmers who wish to enhance their skills in Omron PLC programming, HMI configuration, motion control, and safety systems.

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

• Configure and program Omron PLCs using Sysmac Studio.
• Understand and apply IEC concepts in ladder logic and structured text programming.
• Develop motion control programs for single-axis and coordinated movements.
• Create HMI interfaces using the NA series and integrate them with Sysmac controllers.
• Implement and simulate safety standards and programs using NX series safety hardware.

This course provides an introduction to the fundamentals of Programmable Logic Controllers (PLC). Following an overview of key PLC concepts, participants will learn and practice essential Ladder Diagram instructions through practical Industrial Automation exercises. Target audience: Electrical Specialists, Mechanical Engineers, and Programmers with an interest 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 either online or on-site, is designed for advanced robotics engineers, systems integrators, and automation leaders who aim to implement AI-driven perception, planning, and control within smart manufacturing settings.

Upon completing this training, participants will be capable of:

• Understanding and applying AI techniques for robotic perception and sensor fusion.
• Developing motion planning algorithms for both collaborative and industrial robots.
• Deploying learning-based control strategies to facilitate real-time decision making.
• Integrating intelligent robotic systems into smart factory workflows.

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 customized training for this course, please reach out to us to arrange the details.