Curso de Introduction to AI in Smart Factories and Industrial Automation

Esta capacitación en vivo dirigida por un instructor en Panama (en línea o en el sitio) está dirigida a ingenieros y técnicos de nivel principiante a intermedio que deseen dominar los fundamentos de los PLC AB y aplicarlos a escenarios de fabricación del mundo real.

Al final de esta formación, los participantes serán capaces de:

• Comprenda el papel y las aplicaciones de los PLC AB en la industria manufacturera.
• Programe PLC AB utilizando RSLogix 5000/Studio 5000.
• Solucione problemas comunes y realice el mantenimiento de los sistemas PLC.
• Diseñar e implementar un sistema controlado por PLC para un proceso de fabricación.
• Demostrar competencia en programación de PLC a través de un proyecto práctico.

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.

Este curso introduce al estudiante a los conceptos básicos de los controladores lógicos programables (PLC). Después de la discusión del concepto fundamental de los PLC, las instrucciones básicas del diagrama de escalera se aprenden y practican en Industrial Automation tareas. Público - Especialistas en electricidad - Ingenieros mecánicos - Programadores con interés en Industrial Automation

Este entrenamiento en vivo dirigido por un instructor en Panama (en línea o en el lugar) está dirigido a ingenieros de automatización y diseñadores de sistemas de control de nivel intermedio que desean implementar soluciones de control de movimiento utilizando PLCs de Omron.

Al final de esta capacitación, los participantes podrán:

• Entender los conceptos fundamentales de control de movimiento y sus aplicaciones.
• Configurar el hardware y software de movimiento en Sysmac Studio.
• Programar y optimizar el control de movimiento de un solo eje y de varios ejes.
• Implementar estrategias de movimiento coordinado, incluyendo interpolación y sincronización.

Esta capacitación en vivo dirigida por un instructor en Panama (en línea o presencial) está dirigida a programadores de nivel intermedio que desean mejorar sus habilidades en programación de PLC, configuración de HMI, control de movimiento y sistemas de seguridad de Omron.

Al final de esta formación, los participantes serán capaces de:

• Configure y programe PLC de Omron con Sysmac Studio.
• Comprender y aplicar los conceptos de IEC en lógica de escalera y programación de texto estructurado.
• Desarrollar programas de control de movimiento para movimientos coordinados y de un solo eje.
• Cree interfaces HMI utilizando la serie NA e intégrelas con los controladores Sysmac.
• Implemente y simule estándares y programas de seguridad utilizando el hardware de seguridad de la serie NX.

Esta formación en vivo dirigida por un instructor en Panama (en línea o presencial) está destinada a ingenieros de automatización principiantes y entusiastas que desean aprender los fundamentos de la programación ladder para PLC y aplicarlos en proyectos industriales y personales.

Al finalizar esta formación, los participantes podrán:

• Comprender los conceptos básicos y las aplicaciones de los PLC en sistemas de automatización.
• Escribir programas ladder simples y avanzados utilizando funciones lógicas y gestión de memoria.
• Integrar PLC con redes para aplicaciones de sistema más amplias.
• Aplicar habilidades aprendidas para crear y probar escenarios de automatización reales.

Un robot inteligente es un sistema Artificial Intelligence (AI) que puede aprender de su entorno y de su experiencia y aprovechar sus capacidades en función de ese conocimiento. Smart Robots puede colaborar con los humanos, trabajando junto a ellos y aprendiendo de su comportamiento. Además, tienen la capacidad no solo para el trabajo manual, sino también para tareas cognitivas. Además de los robots físicos, Smart Robots también pueden estar puramente basados en software, residiendo en una computadora como una aplicación de software sin partes móviles ni interacción física con el mundo.

En esta capacitación en vivo dirigida por un instructor, los participantes aprenderán las diferentes tecnologías, marcos y técnicas para programar diferentes tipos de mecánica Smart Robots, y luego aplicarán este conocimiento para completar sus propios proyectos de Smart Robot.

El curso se divide en 4 secciones, cada una de las cuales consta de tres días de conferencias, debates y desarrollo práctico de robots en un entorno de laboratorio en vivo. Cada sección concluirá con un proyecto práctico para permitir que los participantes practiquen y demuestren sus conocimientos adquiridos.

El hardware objetivo de este curso se simulará en 3D a través de software de simulación. El marco de código abierto ROS (Robot Operating System), C++ y Python se utilizará para programar los robots.

Al final de esta formación, los participantes serán capaces de:

• Comprender los conceptos clave utilizados en las tecnologías robóticas
• Comprender y gestionar la interacción entre el software y el hardware en un sistema robótico
• Comprender e implementar los componentes de software que sustentan Smart Robots
• Construya y opere un robot inteligente mecánico simulado que pueda ver, sentir, procesar, agarrar, navegar e interactuar con humanos a través de la voz
• Amplíe la capacidad de un robot inteligente para realizar tareas complejas a través de Deep Learning
• Pruebe y solucione problemas de un robot inteligente en escenarios realistas

Audiencia

• Desarrolladores
• Ingenieros

Formato del curso

• En parte conferencia, en parte discusión, ejercicios y práctica práctica intensa

Nota

• Para personalizar cualquier parte de este curso (lenguaje de programación, modelo de robot, etc.) por favor póngase en contacto con nosotros para concertarlo.

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.