Introduction to AI in Smart Factories and Industrial Automation Training Course

The Allen Bradley platform constitutes a widely utilized industrial automation ecosystem designed for configuring, controlling, and integrating PLCs, HMIs, and various networked devices.

This instructor-led live training, available in online or onsite formats, targets intermediate-level automation professionals seeking to interconnect and integrate Allen Bradley devices via Ethernet to ensure 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 using standard communication protocols.
• Deploy real-world network topologies for automation systems.
• Diagnose and resolve issues related to device connectivity and data exchange.

Course Format

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

Course Customization Options

• Tailored training versions can be arranged to address specific device models or network architectures.

This instructor-led, live training in Serbia (online or onsite) targets 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 utilizes machine learning and data analytics to anticipate equipment failures and optimize maintenance schedules. It shifts the paradigm from reactive to proactive strategies, enhancing equipment 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-based predictive maintenance solutions within industrial settings.

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

• Distinguish between predictive, reactive, and preventive maintenance strategies.
• Collect and structure machine data for AI-driven analysis.
• Apply machine learning models to identify anomalies and predict failures.
• Implement comprehensive workflows that transform sensor data into actionable insights.

Course Format

• Interactive lectures and discussions.
• Practical exercises and real-world case studies.
• Live demonstrations and hands-on data workflow practice.

Customization Options

• For a customized training session, please contact us to arrange specific requirements.

AI-driven process optimization leverages machine learning and data analytics to boost efficiency, quality, and throughput within manufacturing operations.

This instructor-led live training (available online or onsite) is designed for intermediate-level manufacturing professionals seeking to apply AI techniques to streamline operations, minimize downtime, and support continuous improvement initiatives.

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

• Comprehend AI concepts pertinent to manufacturing optimization.
• Collect and prepare production data for analysis.
• Apply machine learning models to identify bottlenecks and predict failures.
• Visualize and interpret results to support data-driven decisions.

Format of the Course

• Interactive lecture and discussion.
• Extensive 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.

AI for Quality Control leverages computer vision and machine learning to detect defects, anomalies, and deviations within production processes.

This instructor-led live training (available online or onsite) is designed for quality professionals ranging from beginner to intermediate levels who aim to utilize AI tools to automate inspections and enhance product quality in manufacturing settings.

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

• Grasping the application of AI in industrial quality control.
• Collecting and labeling image or sensor data from production lines.
• Applying machine learning and computer vision techniques to identify defects.
• Developing basic AI models for anomaly detection and yield forecasting.

Course Format

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

Customization Options

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

The integration of Artificial Intelligence into Supply Chain and Manufacturing Logistics leverages predictive analytics, machine learning, and automation to refine inventory management, optimize routing, and enhance demand forecasting.

This instructor-led live training, available both online and on-site, is designed for intermediate-level supply chain professionals seeking to deploy AI-driven tools. The goal is to improve logistics performance, achieve precise demand forecasting, and automate warehouse and transportation operations.

Upon completing this training, participants will be equipped to:

• Grasp the application of AI across various logistics and supply chain functions.
• Utilize machine learning models for predicting demand and managing inventory.
• Analyze and optimize transport routes using AI methodologies.
• Automate decision-making processes within warehouses and fulfillment centers.

Training Format

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

Customization Options

• For tailored training on this subject, please reach out to us to make arrangements.

Implementing AI Use Cases utilizes a hands-on, project-based methodology to apply machine learning, computer vision, and data analytics to address real-world industrial challenges by leveraging actual or simulated datasets.

This instructor-led, live training (available online or onsite) targets intermediate-level cross-functional teams aiming to collaboratively deploy AI use cases that align with their operational objectives while gaining practical experience with industrial data pipelines.

Upon completing this training, participants will be capable of:

• Identifying and defining practical AI use cases within operations, quality assurance, or maintenance.
• Collaborating across different roles to create machine learning solutions.
• Managing, cleaning, and analyzing varied industrial datasets.
• Demonstrating a functional prototype of an AI-powered solution based on a chosen use case.

Course Format

• Interactive lectures and discussions.
• Group exercises and project-based work.
• Hands-on implementation within a live laboratory environment.

Customization Options

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

Developed by Vector, CANoe is a robust software solution designed for the creation, evaluation, and examination of in-vehicle networks and ECUs, particularly those utilizing the CAN (Controller Area Network) protocol.

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

Upon completing this training, participants will be capable of:

• Installing and setting up CANoe along with its associated components
• Grasping the core principles of the CAN protocol and message framing
• Developing simulations for ECUs and CAN networks through CAPL scripting
• Effectively monitoring, analyzing, and troubleshooting CAN traffic

Digital Twins function as virtual counterparts to physical entities, augmented by live data feeds and artificial intelligence capabilities.

This instructor-led training, available online or in-person, targets intermediate-level professionals seeking to construct, implement, and optimize digital twin models through the application of real-time data and AI-driven analytics.

Upon completion of this program, participants will possess the ability to:

• Comprehend the architecture and constituent elements of digital twins.
• Employ simulation tools to construct models of intricate systems and environments.
• Incorporate real-time data streams into virtual representations.
• Utilize AI methodologies for predictive analysis and anomaly identification.

Course Format

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

Customization Opportunities

• For bespoke training arrangements, please reach out to us.

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 on-site, targets advanced embedded and IoT professionals seeking to implement AI-driven logic and control systems in manufacturing settings where speed, reliability, and offline capability are paramount.

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

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

Course Format

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

Customization Options

• To request a customized version of this course, please contact us to arrange.

The integration of artificial intelligence into industrial computer vision is revolutionizing the way manufacturers and quality assurance (QA) teams identify surface anomalies, verify component compliance, and automate visual inspection workflows.

This instructor-led training, available both online and onsite, targets intermediate to advanced QA professionals, automation engineers, and developers interested in designing and implementing AI-driven computer vision systems for defect detection and inspection.

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

• Grasping the architecture and core components of industrial vision systems.
• Developing AI models for visual defect detection utilizing deep learning techniques.
• Integrating real-time inspection pipelines with industrial cameras and hardware.
• Deploying and optimizing AI-enabled inspection systems for production environments.

Course Format

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

Customization Options

• For customized training arrangements, please contact us directly.

This instructor-led live training, held Serbia (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 Serbia (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 introduces the student to the basics of Programmable Logic Controllers (PLC). After the discussion of the fundamental concept of PLCs the basic Ladder Diagram instructions are learned and practiced in Industrial Automation tasks. Audience - Electrical Specialists - Mechanical Engineers - Programmers with interest in Industrial Automation

Intelligent robotics involves embedding artificial intelligence into robotic frameworks to enhance perception, decision-making capabilities, and autonomous control.

This instructor-led live training, available both online and onsite, is designed for robotics engineers, systems integrators, and automation leaders seeking to implement AI-driven perception, planning, and control solutions within smart manufacturing settings.

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

• Grasp and apply AI methods for robotic perception and sensor fusion.
• Create motion planning algorithms tailored for collaborative and industrial robots.
• Implement learning-based control strategies to facilitate real-time decision making.
• Seamlessly integrate intelligent robotic systems into smart factory operations.

Training Format

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

Customization Options

• For personalized training requests, please get in touch with us to arrange your specific needs.