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

AI-driven predictive maintenance leverages machine learning and data analytics to anticipate equipment failures and optimize maintenance schedules. It shifts the paradigm from reactive maintenance to proactive strategies, resulting in improved uptime, reduced costs, and extended asset life.

This instructor-led live training (available online or onsite) is designed for intermediate-level professionals looking to implement AI-based predictive maintenance solutions within industrial settings.

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

• Distinguish predictive maintenance from reactive and preventive maintenance strategies.
• Gather and structure machine data for AI analysis.
• Utilize machine learning models to identify anomalies and forecast failures.
• Execute end-to-end workflows that transform sensor data into actionable insights.

Course Format

• Interactive lectures and discussions.
• Practical exercises and case study analyses.
• Live demonstrations and hands-on data workflow practices.

Customization Options

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

AI for Process Optimization involves leveraging 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 who want to apply AI techniques to streamline operations, minimize downtime, and drive continuous improvement initiatives.

Upon completing this training, participants will be able to:

• Grasp AI concepts pertinent to manufacturing optimization.
• Gather and prepare production data for analysis.
• Utilize machine learning models to pinpoint bottlenecks and predict equipment failures.
• Visualize and interpret outcomes to facilitate data-driven decision-making.

Course Format

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

Course Customization Options

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

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

This instructor-led live training, available either online or onsite, is designed for quality professionals at 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 able to:

• Grasp the application of AI in industrial quality control.
• Collect and label image or sensor data from production lines.
• Utilize machine learning and computer vision for defect detection.
• Develop basic AI models for anomaly detection and yield forecasting.

Format of the Course

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

Course Customization Options

• To request customized training for this course, please contact us to make arrangements.

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

This instructor-led live training, available online or onsite, is designed for intermediate-level supply chain professionals looking to leverage AI-driven tools to enhance logistics performance, improve demand forecast 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.

AI in Smart Factories involves applying artificial intelligence to automate, monitor, and optimise 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 a strategic and practical introduction to leveraging AI in smart factory environments.

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

• Understand the core principles of AI and machine learning.
• Identify key AI use cases in manufacturing and automation.
• Explore how AI supports predictive maintenance, quality control, and process optimisation.
• Evaluate the steps involved in launching AI-driven initiatives.

Format of the Course

• Interactive lecture and discussion.
• Real-world case studies and group exercises.
• Strategic frameworks and implementation guidance.

Course Customization Options

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

Implementing AI Use Cases utilizes a hands-on, project-focused 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) is designed for intermediate-level cross-functional teams seeking to collaboratively implement AI initiatives aligned with their operational objectives and build experience with industrial data pipelines.

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

• Identifying and defining practical AI scenarios within operations, quality, or maintenance functions.
• Collaborating across various roles to develop machine learning solutions.
• Managing, cleaning, and analyzing diverse industrial datasets.
• Demonstrating a functional prototype of an AI-enabled solution derived from a chosen scenario.

Course Format

• Interactive lectures and discussions.
• Group-based exercises and project work.
• Practical implementation within a live-lab environment.

Customization Options

• To arrange customized training for this course, please contact us to discuss your requirements.

Azure Bot Service integrates the Microsoft Bot Framework with Azure Functions, offering a robust platform for rapidly creating intelligent bots.

Through this instructor-led live training, participants will learn how to efficiently develop smart bots using Microsoft Azure.

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

Grasp the fundamental concepts underlying intelligent bots.

Develop intelligent bots using cloud-based applications.

Acquire practical expertise in the Microsoft Bot Framework, Bot Builder SDK, and Azure Bot Service.

Implement established bot design patterns in practical scenarios.

Create and deploy their first intelligent bot using Microsoft Azure.

Target Audience

This course is tailored for developers, hobbyists, engineers, and IT professionals with an interest in bot development.

Course Format

The training blends lectures and discussions with exercises, placing a strong emphasis on hands-on practice.

A bot, or chatbot, acts as a digital assistant designed to automate user interactions across various messaging platforms, enabling tasks to be completed more swiftly without requiring human intervention.

In this instructor-led live training, participants will gain hands-on experience in bot development by building sample chatbots using established development tools and frameworks.

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

• Comprehend the diverse uses and applications of bots
• Grasp the end-to-end process of bot development
• Explore the array of tools and platforms available for constructing bots
• Develop a sample chatbot for Facebook Messenger
• Construct a sample chatbot leveraging the Microsoft Bot Framework

Audience

• Developers keen on creating their own bot solutions

Format of the course

• A blend of lectures, discussions, exercises, and intensive hands-on practice

Digital Twins serve as virtual mirrors of physical systems, augmented by real-time data feeds and AI-powered analytics.

This instructor-led training, available online or onsite, is designed for intermediate-level professionals seeking to construct, deploy, and refine digital twin models leveraging real-time information and AI-driven insights.

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

• Grasp the architecture and key components of digital twins.
• Utilize simulation tools to represent complex systems and environments.
• Incorporate real-time data streams into virtual models.
• Deploy AI methodologies for predictive analysis and anomaly identification.

Course Format

• Engaging lectures and interactive discussions.
• Extensive practical exercises and hands-on practice.
• Live-lab implementation sessions.

Customization Options

• For tailored training arrangements, please get in touch with us.

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

This instructor-led live training (available online or onsite) is designed for advanced-level embedded and IoT professionals who aim 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.
• 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 practice.
• Hands-on implementation within a live-lab environment.

Course Customization Options

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

AI-driven industrial computer vision is revolutionizing the way manufacturers and quality assurance teams identify surface defects, verify part conformity, and automate visual inspection workflows.

This instructor-led live training, available both online and onsite, is designed for intermediate to advanced quality assurance teams, automation engineers, and developers who want 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:

• Grasp the architecture and key 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 within production environments.

Course Format

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

Course Customization Options

• To arrange customized training for this course, please get in touch with us.

A Smart Robot is an Artificial Intelligence (AI) system capable of learning from its surroundings and experiences, thereby enhancing its capabilities based on acquired knowledge. These robots can collaborate with humans, working alongside them and learning from their behavior. Beyond physical tasks, they are equipped to handle cognitive duties. In addition to physical robots, Smart Robots can exist purely as software applications on a computer, devoid of moving parts or physical interaction with the physical world.

Through this instructor-led live training, participants will explore the various technologies, frameworks, and techniques used to program different types of mechanical Smart Robots, applying this knowledge to complete their own Smart Robot projects.

The course is structured into 4 sections, each comprising three days of lectures, discussions, and hands-on robot development in a live lab environment. Each section concludes with a practical hands-on project, allowing participants to practice and demonstrate their acquired knowledge.

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

Upon completing this training, participants will be able to:

• Grasp the key concepts underpinning robotic technologies
• Understand and manage the interaction between software and hardware in a robotic system
• Understand and implement the software components that form the foundation of Smart Robots
• Build and operate a simulated mechanical Smart Robot capable of seeing, sensing, processing, grasping, navigating, and interacting with humans via voice
• Enhance a Smart Robot's ability to perform complex tasks through Deep Learning
• Test and troubleshoot a Smart Robot in realistic scenarios

Audience

• Developers
• Engineers

Format of the course

• A mix of lectures, discussions, exercises, and extensive hands-on practice

Note

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