Smart Robotics in Manufacturing: AI for Perception, Planning, and Control Training Course

AI-powered predictive maintenance leverages machine learning and data analytics to predict equipment failures and optimize maintenance schedules. It shifts reactive maintenance practices to proactive strategies, enhancing uptime, reducing costs, and extending asset life.

This instructor-led, live training (available online or onsite) is designed for intermediate-level professionals who aim to implement AI-driven predictive maintenance solutions in industrial settings.

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

• Grasp how predictive maintenance differs from reactive and preventive maintenance approaches.
• Gather and organize machine data for AI analysis.
• Utilize machine learning models to identify anomalies and forecast failures.
• Execute comprehensive workflows from sensor data collection to actionable insights.

Format of the Course

• Interactive lectures and discussions.
• Practical exercises and case studies.
• Live demonstrations and real-world data workflows.

Course Customization Options

• For a customized training tailored to your specific needs, please contact us to arrange.

AI for Process Optimization involves using machine learning and data analytics to enhance efficiency, quality, and throughput in manufacturing processes.

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

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

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

Format of the Course

• Interactive lecture and discussion sessions.
• Numerous exercises and practical activities.
• 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 involves the application of computer vision and machine learning techniques to detect defects, anomalies, and deviations in production processes.

This instructor-led, live training (available online or on-site) is designed for quality professionals at beginner to intermediate levels who want to use AI tools to automate inspections and enhance product quality in manufacturing settings.

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

• Understand how AI is utilized in industrial quality control.
• Gather and label image or sensor data from production lines.
• Employ machine learning and computer vision to identify defects.
• Develop basic AI models for anomaly detection and yield forecasting.

Format of the Course

• Interactive lectures and discussions.
• Numerous exercises and practical sessions.
• 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 involves the use of predictive analytics, machine learning, and automation to optimize inventory management, routing, and demand forecasting.

This instructor-led, live training (available both online and on-site) is designed for intermediate-level supply chain professionals who aim to leverage AI-driven tools to improve logistics performance, achieve accurate demand forecasting, and automate warehouse and transport operations.

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

• Understand how AI is utilized across various logistics and supply chain activities.
• Apply machine learning models for demand forecasting and inventory control.
• Analyze and optimize transport routes using AI-based techniques.
• Automate decision-making processes in warehouses and fulfillment centers.

Format of the Course

• Interactive lectures and discussions.
• Extensive exercises and practical activities.
• 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 Smart Factories involves the application of artificial intelligence to automate, monitor, and optimize industrial operations in real-time.

This instructor-led, live training (available online or onsite) is designed for beginner-level decision-makers and technical leads who want to gain a strategic and practical understanding of how AI can be utilized in smart factory environments.

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

• Grasp the fundamental principles of AI and machine learning.
• Recognize key AI applications in manufacturing and automation.
• Examine how AI enhances predictive maintenance, quality control, and process optimization.
• Assess the steps required to initiate AI-driven projects.

Format of the Course

• Interactive lectures and discussions.
• Real-world case studies and group activities.
• Strategic frameworks and implementation guidance.

Course Customization Options

• For a customized training session tailored to your specific needs, please contact us to arrange.

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

This training, led by an instructor (either online or on-site), is designed for intermediate-level cross-functional teams who want to collaboratively implement AI use cases that align with their operational goals and gain hands-on experience working with industrial data pipelines.

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

• Identify and define practical AI use cases from operations, quality, or maintenance areas.
• Collaborate effectively across different roles to develop machine learning solutions.
• Manage, clean, and analyze a variety of industrial datasets.
• Present a functional prototype of an AI-enabled solution based on a chosen use case.

Format of the Course

• Interactive lectures and discussions.
• Group 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.

The Azure Bot Service integrates the capabilities of the Microsoft Bot Framework and Azure functions to facilitate the rapid development of intelligent bots.

In this instructor-led, live training, participants will learn how to efficiently create an intelligent bot using Microsoft Azure.

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

• Understand the basics of intelligent bots
• Learn how to develop intelligent bots using cloud applications
• Gain insight into using the Microsoft Bot Framework, the Bot Builder SDK, and the Azure Bot Service
• Comprehend how to design bots using bot patterns
• Create their first intelligent bot using Microsoft Azure

Audience

• Developers
• Hobbyists
• Engineers
• IT Professionals

Format of the course

• Part lecture, part discussion, exercises, and extensive hands-on practice

A chatbot or bot is a type of computer assistant designed to automate user interactions on various messaging platforms, enabling tasks to be completed faster without the need for human-to-human communication.

In this instructor-led, live training, participants will gain insights into developing bots as they work through the creation of sample chatbots using bot development tools and frameworks.

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

• Comprehend the diverse uses and applications of bots
• Grasp the entire process involved in developing bots
• Explore the various tools and platforms used for building bots
• Create a sample chatbot for Facebook Messenger
• Develop a sample chatbot using Microsoft Bot Framework

Audience

• Developers interested in creating their own bot

Format of the course

• Part lecture, part discussion, exercises, and extensive hands-on practice

Digital Twins are virtual representations of physical systems that are enhanced with real-time data and AI-driven intelligence.

This instructor-led, live training (available online or on-site) is designed for intermediate-level professionals who want 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.
• Extensive exercises and practice sessions.
• 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 the deployment of artificial intelligence models directly onto devices and machines at the network's edge, enabling real-time decision-making with minimal latency.

This instructor-led, live training (available online or onsite) is designed for advanced embedded and IoT professionals who want to deploy AI-powered logic and control systems in manufacturing environments where speed, reliability, and offline operation are crucial.

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

• Grasp the architecture and benefits 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.

Format of the Course

• Interactive lecture and discussion sessions.
• Extensive exercises and practice activities.
• Hands-on implementation in a live-lab environment.

Course Customization Options

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

Industrial computer vision with AI is revolutionizing the way manufacturers and QA teams identify surface defects, ensure part compliance, and automate visual inspection processes.

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

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

• Comprehend the architecture and components of industrial vision systems.
• Develop 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.
• Numerous exercises and practice sessions.
• Hands-on implementation in a live-lab environment.

Course Customization Options

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

A Smart Robot is an Artificial Intelligence (AI) system capable of learning from its environment and experiences, enhancing its capabilities based on the knowledge it acquires. These robots can collaborate with humans, working alongside them and learning from their behavior. They are not only proficient in manual tasks but also excel in cognitive functions. In addition to physical robots, Smart Robots can be purely software-based, operating as applications within a computer without any physical interaction with the world.

In this instructor-led, live training, participants will explore various technologies, frameworks, and techniques for programming different types of mechanical Smart Robots. They will then apply this knowledge to complete their own Smart Robot projects.

The course is divided into four sections, each consisting of three days of lectures, discussions, and hands-on robot development in a live lab environment. Each section concludes with a practical, hands-on project to allow participants to practice and demonstrate their acquired skills.

The target hardware for this course will be simulated in 3D through simulation software. The ROS (Robot Operating System) open-source framework, along with C++ and Python, will be used for programming the robots.

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

• Understand the key concepts used in robotic technologies
• Manage the interaction between software and hardware in a robotic system effectively
• Implement the software components that underpin Smart Robots
• Build and operate a simulated mechanical Smart Robot capable of seeing, sensing, processing, grasping, navigating, and interacting with humans through voice commands
• Enhance a Smart Robot's ability to perform complex tasks using Deep Learning techniques
• Test and troubleshoot a Smart Robot in realistic scenarios

Audience

• Developers
• Engineers

Format of the course

• Part lecture, part discussion, exercises, and extensive hands-on practice

Note

• To customize any aspect of this course (such as programming language or robot model), please contact us to arrange.