Corso di formazione Introduction to AI in Smart Factories and Industrial Automation

Questo corso di formazione dal vivo con istruttore in Italia (online o in loco) è rivolto a ingegneri e tecnici di livello principiante e intermedio che desiderano padroneggiare i fondamenti dei PLC AB e applicarli a scenari di produzione reali.

Al termine di questa formazione, i partecipanti saranno in grado di:

• Comprendere il ruolo e le applicazioni dei PLC AB nell'industria manifatturiera.
• Programmazione di PLC AB utilizzando RSLogix 5000/Studio 5000.
• Risolvi i problemi più comuni ed esegui la manutenzione sui sistemi PLC.
• Progettare e implementare un sistema controllato da PLC per un processo di produzione.
• Dimostrare competenza nella programmazione PLC attraverso un progetto pratico.

AI-powered predictive maintenance applies machine learning and data analytics to forecast equipment failures and optimize maintenance schedules. It transforms reactive maintenance models into proactive strategies, enabling better uptime, cost reduction, and asset longevity.

This instructor-led, live training (online or onsite) is aimed at intermediate-level professionals who wish to implement AI-driven predictive maintenance solutions in industrial environments.

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

• Understand how predictive maintenance differs from reactive and preventive maintenance strategies.
• Collect and structure machine data for AI-powered analysis.
• Apply machine learning models to detect anomalies and predict failures.
• Implement end-to-end workflows from sensor data to actionable insights.

Format of the Course

• Interactive lecture and discussion.
• Hands-on exercises and case studies.
• Live demonstration and practical data workflows.

Course Customization Options

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

AI for Process Optimization is the application of machine learning and data analytics to enhance efficiency, quality, and throughput in manufacturing operations.

This instructor-led, live training (online or onsite) is aimed at intermediate-level manufacturing professionals who wish to apply AI techniques to streamline operations, reduce downtime, and support continuous improvement initiatives.

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

• Understand AI concepts relevant 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.
• 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.

AI for Quality Control is the use of computer vision and machine learning techniques to identify defects, anomalies, and deviations in production processes.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level quality professionals who wish to apply AI tools to automate inspections and improve product quality in manufacturing environments.

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

• Understand how AI is applied in industrial quality control.
• Collect and label image or sensor data from production lines.
• Use machine learning and computer vision to detect defects.
• Develop simple AI models for anomaly detection and yield forecasting.

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.

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.

AI Use Case Implementation is a hands-on, project-driven approach to applying machine learning, computer vision, and data analytics to solve real-world industrial challenges using actual or simulated datasets.

This instructor-led, live training (online or onsite) is aimed at intermediate-level cross-functional teams who wish to collaboratively implement AI use cases aligned with their operational goals and gain experience working with industrial data pipelines.

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

• Select and scope practical AI use cases from operations, quality, or maintenance.
• Work collaboratively across roles to develop machine learning solutions.
• Handle, clean, and analyze diverse industrial datasets.
• Present a working prototype of an AI-enabled solution based on a selected use case.

Format of the Course

• Interactive lecture and discussion.
• Group-based exercises and project work.
• Hands-on implementation in a live-lab environment.

Course Customization Options

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

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 is the deployment of artificial intelligence models directly on devices and machines at the edge of the network, enabling real-time decision-making with minimal latency.

This instructor-led, live training (online or onsite) is aimed at advanced-level embedded and IoT professionals who wish to deploy AI-powered logic and control systems in manufacturing environments where speed, reliability, and offline operation are critical.

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

• Understand the architecture and benefits of edge AI systems.
• Build and optimize AI models for deployment on embedded devices.
• Use tools like TensorFlow Lite and OpenVINO for low-latency inference.
• Integrate edge intelligence with sensors, actuators, and industrial protocols.

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.

Industrial computer vision with AI is transforming how manufacturers and QA teams detect surface defects, verify part conformity, and automate visual inspection processes.

This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level QA teams, automation engineers, and developers who wish to design and implement computer vision systems for defect detection and inspection using AI techniques.

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

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

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.

Questo corso introduce lo studente alle basi dei controllori logici programmabili (PLC). Dopo la discussione sul concetto fondamentale di PLC, le istruzioni di base del diagramma ladder vengono apprese e praticate nelle attività di Industrial Automation . Pubblico - Specialisti elettrici - Ingegneri meccanici - Programmatori con interesse per Industrial Automation

Questa formazione dal vivo con istruttore in Italia (online o in loco) è rivolta a ingegneri dell'automazione e progettisti di sistemi di controllo di livello intermedio che desiderano implementare soluzioni di controllo del movimento utilizzando PLC Omron.

Al termine di questa formazione, i partecipanti saranno in grado di:

• Comprendere i concetti fondamentali del controllo del movimento e le loro applicazioni.
• Configurare hardware e software di movimento in Sysmac Studio.
• Programmare e ottimizzare il controllo del movimento monoasse e multiasse.
• Implementare strategie di movimento coordinate, tra cui interpolazione e sincronizzazione.

Questo corso di formazione dal vivo con istruttore in Italia (online o in loco) è rivolto a programmatori di livello intermedio che desiderano migliorare le proprie competenze nella programmazione PLC Omron, nella configurazione HMI, nel controllo del movimento e nei sistemi di sicurezza.

Al termine di questo corso di formazione, i partecipanti saranno in grado di:

• Configura e programma i PLC Omron utilizzando Sysmac Studio.
• Comprendere e applicare i concetti IEC nella logica ladder e nella programmazione di testo strutturato.
• Sviluppa programmi di controllo del movimento per movimenti monoassiali e coordinati.
• Crea interfacce HMI utilizzando la serie NA e integrale con i controller Sysmac.
• Implementa e simula gli standard e i programmi di sicurezza utilizzando l'hardware di sicurezza della serie NX.

Questo corso live guidato dal formatore in Italia (online o sul posto) è rivolto a ingegneri di automazione principianti ed entusiasti che desiderano imparare i fondamenti della programmazione a gradini dei PLC e applicarli in progetti industriali e personali.

Al termine del corso, i partecipanti saranno in grado di:

• Capire i concetti di base ed le applicazioni dei PLC nei sistemi di automazione.
• Scrivere programmi a gradini semplici e avanzati utilizzando funzioni logiche e gestione della memoria.
• Integrare i PLC con reti per applicazioni di sistema più ampie.
• Applicare le competenze acquisite per creare ed eseguire scenari di automazione reali.

Un robot intelligente è un sistema in grado di imparare dal suo ambiente e dalla sua esperienza e di sviluppare le sue capacità sulla base di tale conoscenza. Smart Robots può collaborare con gli esseri umani, lavorando al loro fianco e imparando dal loro comportamento. Inoltre, hanno la capacità non solo di svolgere lavori manuali, ma anche di svolgere compiti cognitivi. Oltre ai robot fisici, Smart Robots può anche essere puramente basato su software, risiedendo in un computer come un'applicazione software senza parti mobili o interazione fisica con il mondo.

In questo corso di formazione dal vivo con istruttore, i partecipanti impareranno le diverse tecnologie, framework e tecniche per la programmazione di diversi tipi di meccanica Smart Robots, quindi applicheranno queste conoscenze per completare i propri progetti Smart Robot.

Il corso è diviso in 4 sezioni, ciascuna composta da tre giorni di lezioni, discussioni e sviluppo pratico di robot in un ambiente di laboratorio dal vivo. Ogni sezione si concluderà con un progetto pratico per consentire ai partecipanti di esercitarsi e dimostrare le conoscenze acquisite.

L'hardware target per questo corso sarà simulato in 3D attraverso software di simulazione. Per la programmazione dei robot verrà utilizzato il framework open-source ROS (Robot Operating System), C++ e Python.

Al termine di questo corso di formazione, i partecipanti saranno in grado di:

• Comprendere i concetti chiave utilizzati nelle tecnologie robotiche
• Comprendere e gestire l'interazione tra software e hardware in un sistema robotico
• Comprendere e implementare i componenti software che sono alla base Smart Robots
• Costruisci e gestisci un robot intelligente meccanico simulato in grado di vedere, percepire, elaborare, afferrare, navigare e interagire con gli esseri umani attraverso la voce
• Estendere la capacità di uno Smart Robot di eseguire attività complesse attraverso Deep Learning
• Testa e risolvi i problemi di uno Smart Robot in scenari realistici

Pubblico

• Gli sviluppatori
• Ingegneri

Formato del corso

• In parte lezione, in parte discussione, esercizi e pratica pratica pesante

Nota

• Per personalizzare qualsiasi parte di questo corso (linguaggio di programmazione, modello di robot, ecc.) contattateci per organizzare.

Smart Robotics is the integration of artificial intelligence into robotic systems for improved perception, decision-making, and autonomous control.

This instructor-led, live training (online or onsite) is aimed at advanced-level 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.