AI and Machine Learning Practical Know-How for Industrial Equipment Applications Seminar Held

IR Engineers Education Institute will hold an online seminar explaining from the principles of neural networks and reinforcement learning to time-series data collection, data preparation for learning, and key points of IoT system construction, from an implementation perspective.

In equipment domains such as manufacturing sites and commercial buildings, the use of AI for system control and anomaly detection is expanding. However, in on-site implementation, there are often "realistic challenges" that are difficult to solve with theory alone, such as constraints specific to each piece of equipment, information security, bias in collected data, and ensuring the necessary amount and quality of data for learning. This seminar addresses these challenges and provides "practical" implementation know-how from both theoretical and implementation perspectives.

Seminar Overview ・Seminar Title: Practical Know-How for Applying AI and Machine Learning to Industrial Equipment

・Format: Online (Zoom LIVE streaming / Archive streaming)

・ Date and Time: 【LIVE Streaming】Tuesday, May 26, 2026, 10:00 - 16:00 【Archive Streaming】May 28, 2026 - June 11, 2026

・Capacity: 20 people

・Participation Fee: 49,500 yen/person (tax included)

・Instructor: Chuza Ninagawa (Representative Director, N Research Institute Co., Ltd.)

Course Details This seminar will provide a step-by-step learning experience, starting with an overview of industrial applications of machine learning, followed by modeling of controlled objects, prediction for equipment maintenance, reinforcement learning for equipment management, and tips for collecting learning data and designing systems. In particular, it focuses on "data collection" and "preparation of data for use as learning data," which are often bottlenecks in the field, and covers concepts of ideal collection distribution and methods for dealing with insufficient data (SMOTE method). Furthermore, it will provide an overview of the internal principles of Transformer, which is the foundation of generative AI attracting attention as a cutting-edge technology, and discuss industrial application examples (research cases) such as time-series trend prediction and event occurrence prediction.

Seminar Program 1. Overview of Industrial Applications of Machine Learning (Research Example Videos / On-site Application / Practical Samples) 2. Modeling of Controlled Objects (NN Basics / Step Response / Black-box Models for Multivariate Control) 3. Prediction for Equipment Maintenance (LSTM / Sudden Event Prediction / Accuracy Evaluation Metrics) 4. Reinforcement Learning for Equipment Management (Q-Learning / Transfer Learning / Optimal Economic Operation / Shortening Learning Period) 5. Actual Data Collection for Learning (Quantity and Quality / Ideal Distribution / SMOTE / Tools or Custom Development) 6. Practical Tips for System Design (Initial Strategy / Target Selection / Team Composition / Tool Limitations) 7. Cutting-Edge Industrial Applications of Generative AI Technology (Transformer Overview / Time-Series Prediction / Event Prediction) 8. Summary and Q&A

Target Audience ・Those who want to learn about concrete implementation methods and case studies of machine learning in industrial settings.

・Engineers and team leaders involved in development design and production management related to system control.

・Manufacturers of equipment and machinery, infrastructure and industrial system manufacturers, and companies in civil engineering, construction, and related fields.

・Those who have already started implementation but are struggling with on-site challenges (data, operation, design).

※Details of this seminar can be found here https://nihon-ir.jp/seminar/ai_industrial