TDK Corporation (TSE: 6762) announced today that subsidiary TDK SensEI is unveiling its latest product line, edgeRX™, set to launch 3/17/2025. edgeRX™ represents a significant leap forward in industrial maintenance, bringing cutting-edge innovation to the forefront of machine health monitoring.

edgeRX™ is an advanced machine health monitoring platform that leverages the power of AI on edge sensor devices. By integrating advanced AI algorithms, edge computing, and powerful sensor devices, edgeRX™ provides real-time machine health monitoring, predictive maintenance insights, and actionable alerts directly on machines.

edgeRX™ is a comprehensive, out-of-the-box solution which eliminates the need for extensive setup or specialized integration, allowing reliability engineers, maintenance technicians, and plant managers to quickly deploy and benefit from advanced machine monitoring capabilities. By proactively identifying potential issues before they escalate. edgeRX™ maximizes uptime, reduces maintenance costs, and enhances overall operational efficiency, making it an indispensable tool in modern manufacturing environments.

Supported by TDK’s extensive history in sensors and components, TDK is well-positioned to build and enhance the edgeRX™ platform, ensuring best-in-class performance and reliability. With decades of innovation and expertise, TDK Corporation has been a global leader in electronic components, sensors, batteries, and materials technology. TDK’s rich legacy of pioneering advancements in these fields provides a strong foundation for the development of cutting-edge solutions like edgeRX™.

Key features of edgeRX™ include:

• Complete Platform: Advanced sensors, gateway, dashboard, and AI are all included

• Easy Data Collection: A highly adaptable system that collects data automatically

• Smart Detection: Multi-class automated operation label detection

• Accurate Monitoring: Advanced methods that classify and detect any issues in an operation

• Customizable Alerts: Adjustable sensitivity parameters such as anomaly detection frequency

• Quick Response: Fast and efficient methods to take immediate action when needed

• Continuous Monitoring: Real-time tracking identifies, predicts, and prevents degradation/failure

• Smooth Integration: Seamless data collection, model development, and deployment

The current state of machine health monitoring is rapidly advancing beyond legacy CbM (Condition Based Monitoring) toward PdM (Predictive Maintenance). PdM leverages advanced technologies such as AI, IoT, and sensor fusion to monitor the health of equipment in real-time, providing predictive insights that lead to reduced downtime and higher production output. According to recent reports, the market size for PdM is growing rapidly and is projected to reach USD +13 billion in 2025 with a CAGR (Compound Annual Growth Rate) of +35% over the next 5 years. This growth is fueled by advancements in technology, adoption of AI, and Industry 4.0 acceleration.

“When we decided to launch TDK SensEI mid-2024, edgeRX™ is exactly the type of innovative product that we envisioned the team bringing to market. We believe edgeRX™ marks a pivotal moment in the manufacturing industry as edgeRX™ is the perfect product to solve everyday maintenance related issues with easy to implement AI” stated Noboru Saito, President, and CEO of TDK Corporation.

“Maintaining optimal machine health is crucial in industrial manufacturing operations to keep maintenance costs low and production output high. AI is a crucial ingredient to achieve optimal machine health, however manufacturers have historically struggled to implement AI,” said Sandeep Pandya, CEO, TDK SensEI, a TDK group company. “The edgeRX™ platform offers an out-of-the-box experience to solve the AI challenge and accelerate manufactures ability to achieve optimal machine health. Which is why we’re so excited to announce edgeRX™ to the industrial world.”

 

Glossary

Edge Computing
A technology that processes data close to where it is generated (at the “edge” of the network), reducing latency and bandwidth usage compared to cloud computing

PdM (Predictive Maintenance)
A maintenance strategy that uses data analysis and predictive algorithms to anticipate equipment failures before they occur, allowing for timely maintenance and minimizing downtime

CbM (Condition-Based Monitoring)
A monitoring technique that continuously assesses the condition of equipment using real-time data, enabling maintenance decisions based on the actual health of the machinery rather than on predetermined schedules

 

Main Applications

• Industrial IoT for manufacturing

• Condition- based monitoring, predictive maintenance, prescriptive maintenance

• Enterprise Machine Learning and Advanced Analytics platform

 

Main Features and Benefits

Real-Time Monitoring
Provides continuous oversight of machine health, allowing for immediate detection of potential issues and minimizing downtime

Predictive Maintenance Insights
Uses advanced AI algorithms to predict maintenance needs before failures occur, reducing unexpected breakdowns and maintenance costs

Actionable Alerts
Sends real-time notifications and alerts to reliability engineers and plant managers, enabling swift and informed decision-making

Comprehensive Out-of-the-Box Solution
Eliminates the need for extensive setup or specialized integration, allowing for quick and hassle-free deployment of the monitoring system.

Seamless Integration
Integrates smoothly with existing systems, ensuring a streamlined process from data collection to model development and deployment, enhancing overall operational efficiency