July 30 Webinar: Prevent Equipment Failures in Manufacturing with AI-Powered Anomaly Detection

In manufacturing environments such as factories and plants, various challenges exist regarding data utilization and AI/DX initiatives, including reliance on veteran staff's experience and intuition for inspections, missed anomalies, delayed initial responses, underutilization of sensor data and equipment logs, and increasing maintenance workloads.

This webinar will feature Mr. Takahito Honda, Director and CTO of Melon Inc., a company holding numerous patents in AI-related technologies, who will explain "anomaly detection AI" using sensor data such as temperature, pressure, vibration, and current.

The session will cover practical approaches to prevent equipment and machinery failures, including the fundamentals of anomaly detection AI, how to get started without failure data, capturing abnormal patterns through time-series analysis, and real-world development cases and demonstrations from manufacturing sites.

This webinar is packed with practical insights on leveraging sensor data for predictive maintenance, aimed at manufacturing professionals seeking to prevent unexpected line stoppages, quality defects, and rising inspection and repair costs.

We welcome your participation.

What You Will Learn in This Webinar:

- Key challenges in equipment maintenance in manufacturing and the fundamentals of anomaly detection AI using sensor data

- Approaches to detect early signs of anomalies from normal and time-series data, even in the absence of failure data

- Practical strategies for reducing downtime, stabilizing quality, and lowering maintenance costs, illustrated through real manufacturing case studies and demos

- Other applications of sensor data beyond maintenance, along with implementation examples, and more

View Webinar Details

Recommended For:

- Professionals aiming to prevent unexpected stoppages and equipment failures in manufacturing

- Those looking to utilize sensor data and equipment logs for predictive maintenance

- Individuals with limited failure data who have hesitated to adopt anomaly detection AI

- Those facing challenges with inspection dependency on individuals, missed anomalies, or delayed initial responses

- Manufacturing professionals targeting reduced downtime, stabilized quality, and lower inspection and repair costs

- Personnel responsible for maintenance or DX initiatives in factories and manufacturing sites

- Developers aiming to build and implement failure prediction features into their own products or systems

Webinar Overview:

Date and Time:

July 30, 2026 (Thursday) 13:00–14:00 JST

Registration Deadline:

July 29, 2026 (Wednesday) 13:00 JST

Format:

Online (via Zoom)

Note: The webinar viewing URL will be sent by email to registered participants in advance.

Fee:

Free (prior registration required)

Organizer:

BizTech Inc. (operating AI Market)

Important Notes:

- Participation may be declined for competitors, individuals, or any parties deemed inappropriate by the organizers. In such cases, the viewing URL will not be provided, even if registered. - Prior registration is mandatory to attend. - Presentation content is subject to change on the day of the event. - Redistribution or secondary use of the event content is strictly prohibited.

Register for the Webinar (Free)

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BizTech Inc. Company Overview:

- Company Name: BizTech Inc. - Headquarters: 4F Fujiwara Building, 1-32-4 Higashi-Ikebukuro, Toshima-ku, Tokyo - CEO: Yoshihiro Morishita - Founded: July 4, 2019 - Website: https://biz-t.co.jp

Note: Company names, product names, service names, and logos mentioned are trademarks or registered trademarks of their respective owners.