CANoe for CAN Compact Trainingのトレーニングコース

The Allen Bradley platform is a widely adopted industrial automation ecosystem used to configure, control, and integrate PLCs, HMIs, and networked devices.

This instructor-led, live training (online or onsite) is aimed at intermediate-level automation professionals who wish to interconnect and integrate Allen Bradley automation devices using Ethernet for seamless communication across PLCs, HMIs, servers, and routers.

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

• Configure Ethernet-based communication within the Allen Bradley ecosystem.
• Integrate PLCs, HMIs, servers, and routers using common communication protocols.
• Implement real-world network topologies for automation systems.
• Troubleshoot device connectivity and data exchange issues.

Format of the Course

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

Course Customization Options

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

This instructor-led, live training in 日本 (online or onsite) is aimed at beginner-level 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 in the manufacturing industry.
• Program AB PLCs using RSLogix 5000/Studio 5000.
• Troubleshoot common issues and perform 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 in Smart Factories is the application of artificial intelligence to automate, monitor, and optimize industrial operations in real time.

This instructor-led, live training (online or onsite) is aimed at beginner-level decision-makers and technical leads who wish to gain a strategic and practical introduction to how AI can be leveraged 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 optimization.
• 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.

This instructor-led, live training in 日本 (online or onsite) is aimed at intermediate-level to advanced-level engineers and technicians who wish to learn how to program, operate, and optimize Fanuc and Epson robotic systems for industrial applications.

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

• Understand the architecture and functionalities of Fanuc and Epson robots.
• Program robot movements, logic, and sensor integrations.
• Implement safety protocols and troubleshooting techniques.
• Optimize robotic workflows for improved efficiency.

Industrial Robotics Automation: ROS-PLC Integration & Digital Twins is a hands-on course focused on bridging industrial automation with modern robotics frameworks. Participants will learn to integrate ROS-based robotic systems with PLCs for synchronized operations and explore digital twin environments to simulate, monitor, and optimize production processes. The course emphasizes interoperability, real-time control, and predictive analysis using digital replicas of physical systems.

This instructor-led, live training (online or onsite) is aimed at intermediate-level professionals who wish to build practical skills in connecting ROS-controlled robots with PLC environments and implementing digital twins for automation and manufacturing optimization.

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

• Understand communication protocols between ROS and PLC systems.
• Implement real-time data exchange between robots and industrial controllers.
• Develop digital twins for monitoring, testing, and process simulation.
• Integrate sensors, actuators, and robotic manipulators within industrial workflows.
• Design and validate industrial automation systems using hybrid simulation environments.

Format of the Course

• Interactive lecture and architecture walkthroughs.
• Hands-on exercises integrating ROS and PLC systems.
• Simulation and digital twin project implementation.

Course Customization Options

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

このインストラクター主導のライブトレーニング（オンラインまたはオンサイト）は、中級レベルの自動化エンジニアと制御システムデザイナーを対象としており、オムロンPLCを使用して運動制御ソリューションを実装することを目指しています。

このトレーニング終了時には、参加者は以下のことができるようになります：

• 基本的な運動制御の概念とその応用を理解する。
• Sysmac Studioで運動ハードウェアとソフトウェアを構成する。
• 単軸および多軸の運動制御をプログラミングし、最適化する。
• 補間や同期を含む協調運動戦略を実装する。

This instructor-led, live training in 日本 (online or onsite) 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 program Omron PLCs using Sysmac Studio.
• Understand and apply IEC concepts in ladder logic and structured text programming.
• Develop motion control programs 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 programs using NX series safety hardware.

このコースでは、プログラム可能論理コントローラ（PLC）の基本を学習します。PLCの基本概念について説明した後、基本的なラダーダイアグラム命令を学び、産業自動化タスクで実践します。対象者 - 電気専門家 - 機械エンジニア - 産業自動化に興味があるプログラマ

このインストラクター主導のライブトレーニング（オンラインまたはオンサイト）は、初心者レベルの自動化エンジニアや愛好家向けで、PLCラダープログラミングの基本を学び、産業や個人プロジェクトに適用することを目指しています。

このトレーニング終了後、参加者は以下のことができるようになります：

• 自動化システムにおけるPLCの基本概念と応用について理解する。
• 論理関数とメモリ管理を使用して、単純なおよび高度なラダープログラムを書く。
• ネットワークとの統合により、より広範なシステムアプリケーションにPLCを適用する。
• 学んだスキルを活用し、実際の自動化シナリオを作成しテストする。

リモートターミナルユニット (RTU) は、データ収集、信号送信、および自動化・電力システムネットワーク内の制御命令の実行に使用される重要なフィールドデバイスです。

この講師主導のライブトレーニング（オンラインまたはオンサイト）は、中級レベルの専門家を対象としており、電力セル環境での自動化・制御操作に RTU を設定することを目指しています。

本トレーニング終了時には、参加者は以下ができるようになります：

• RTU ハードウェアのセットアップと入出力チャンネルの正規マッピング。
• SCADA および制御システムとの統合に必要な通信パラメータの設定。
• RTU プラットフォーム内の論理、アラーム、制御戦略の実装。
• RTU のパフォーマンスと通信問題の効果的なトラブルシューティング。

コース形式

• 実際の例を使用した講師主導のプレゼンテーション。
• 手動で行う設定活動と実践的な演習。
• RTU 通信と制御ワークフローのライブデモンストレーション。

コースカスタマイズオプション

• 特定の RTU ハードウェアモデルや制御環境に基づいたカスタマイズされたコースバージョンが利用可能です。

A Smart Robot is an Artificial Intelligence (AI) system that can learn from its environment and its experience and build on its capabilities based on that knowledge. Smart Robots can collaborate with humans, working along-side them and learning from their behavior. Furthermore, they have the capacity for not only manual labor, but cognitive tasks as well. In addition to physical robots, Smart Robots can also be purely software based, residing in a computer as a software application with no moving parts or physical interaction with the world.

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

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

The target hardware for this course will be simulated in 3D through simulation software. The ROS (Robot Operating System) open-source framework, 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
• Understand and manage the interaction between software and hardware in a robotic system
• Understand and implement the software components that underpin Smart Robots
• Build and operate a simulated mechanical Smart Robot that can see, sense, process, grasp, navigate, and interact with humans through voice
• Extend 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

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

Note

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