Introduction to AI in Smart Factories and Industrial Automation Training Course

The Allen Bradley platform is a prominent industrial automation environment widely used for configuring, controlling, and integrating PLCs, HMIs, and networked devices.

This instructor-led live training, available online or onsite, is designed for intermediate-level automation professionals looking to interconnect and integrate Allen Bradley automation devices via Ethernet for 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.
• Implement practical network topologies for automation systems.
• Troubleshoot device connectivity and data exchange issues.

Course Format

• Guided instruction with demonstrations using Allen Bradley tools.
• Hands-on integration exercises involving Ethernet-connected devices.
• Practical configuration and testing in a live-lab environment.

Course Customisation Options

• Customised training versions can be arranged based on specific device models or network architectures.

This instructor-led, live training in New Zealand (online or on-site) is designed for beginner to intermediate-level 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 within the manufacturing sector.
• Program AB PLCs using RSLogix 5000/Studio 5000.
• Troubleshoot common issues and carry out 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-powered predictive maintenance leverages machine learning and data analytics to forecast equipment failures and optimise maintenance schedules. It transforms reactive maintenance models into proactive strategies, enabling improved uptime, cost reduction, and extended asset longevity.

This instructor-led, live training (available online or on-site) is designed for intermediate-level professionals seeking to implement AI-driven predictive maintenance solutions within 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.

Course Format

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

Course Customisation Options

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

AI for Process Optimisation involves applying machine learning and data analytics to enhance efficiency, quality, and throughput in manufacturing operations.

This instructor-led, live training (available online or on-site) is designed for 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 optimisation.
• Collect and prepare production data for analysis.
• Apply machine learning models to identify bottlenecks and predict failures.
• Visualise and interpret results to support data-driven decisions.

Format of the Course

• Interactive lectures and discussions.
• Plenty of exercises and practical activities.
• Hands-on implementation in a live-lab environment.

Course Customisation Options

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

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

This instructor-led, live training (available online or on-site) is designed for beginner to intermediate-level quality professionals who wish to apply 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 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.

Course Format

• Interactive lectures and group discussions.
• Extensive exercises and hands-on practice.
• Practical implementation in a live-lab environment.

Course Customisation Options

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

AI in Supply Chain and Manufacturing Logistics refers to the application of predictive analytics, machine learning, and automation to optimise inventory management, route planning, and demand forecasting.

This instructor-led, live training (available online or on-site) is designed for intermediate-level supply chain professionals who wish to leverage AI-driven tools to enhance logistics performance, forecast demand with greater 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.
• Analyse routes and optimise transport using AI-based techniques.
• Automate decision-making in warehouses and fulfilment processes.

Course Format

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

Course Customisation Options

• To request a customised training session 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 analyse 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 Customisation Options

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

CANoe is a comprehensive software tool developed by Vector, widely used for the development, testing, and analysis of in-vehicle networks and ECUs, particularly those relying on the CAN (Controller Area Network) protocol.

This instructor-led, live training session (available online or on-site) is designed for beginner to intermediate-level automotive engineers and testers who aim to utilise CANoe for simulating, testing, and analysing CAN-based communication systems.

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

• Install and configure CANoe along with its associated components
• Grasp the fundamentals of the CAN protocol and understand message framing
• Develop simulations for ECUs and CAN networks using CAPL scripting
• Effectively monitor, analyse, and debug CAN traffic

Digital Twins are virtual replicas of physical systems, enhanced by real-time data and AI-driven intelligence.

This instructor-led, live training (available online or on-site) is designed for intermediate-level professionals who wish to build, deploy, and optimise 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 behaviour and anomaly detection.

Course Format

• Interactive lectures and discussions.
• Plenty of exercises and practical sessions.
• Hands-on implementation in a live lab environment.

Course Customisation Options

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

Edge AI involves deploying 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 (available online or on-site) is designed for advanced-level embedded and IoT professionals seeking to deploy AI-powered logic and control systems within 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 optimise AI models for deployment on embedded devices.
• Use 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 hands-on practice.
• Practical implementation in a live-lab environment.

Course Customisation Options

• To request a customised training session 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 optimise AI-powered inspection systems for production environments.

Format of the Course

• Interactive lecture and discussion.
• Plenty of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customisation Options

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

This instructor-led, live training in New Zealand (online or onsite) is aimed at intermediate-level automation engineers and control system designers who wish 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 optimise single-axis and multi-axis motion control.
• Implement coordinated motion strategies, including interpolation and synchronisation.

This instructor-led, live training in New Zealand (online or on-site) 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 programme Omron PLCs using Sysmac Studio.
• Understand and apply IEC concepts in ladder logic and structured text programming.
• Develop motion control programmes 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 programmes using NX series safety hardware.

This course introduces students to the fundamentals of Programmable Logic Controllers (PLCs). Following an exploration of core PLC concepts, learners will acquire and apply basic Ladder Diagram (LAD) instructions through hands-on industrial automation exercises. Target Audience: Electrical Specialists, Mechanical Engineers, and Programmers with an interest in industrial automation.

Smart Robotics involves integrating artificial intelligence into robotic systems to enhance perception, decision-making, and autonomous control.

This instructor-led, live training (available online or on-site) is designed for advanced-level robotics engineers, systems integrators, and automation leads who aim to implement AI-driven perception, planning, and control within 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.

Course Format

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

Course Customisation Options

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