Predictive Maintenance Time Series Data Automatic Analysis Machine CX-M
Time Series Data Automatic Analysis Machine CX-M
Automating abnormal equipment detection, failure prediction, and AI model generation! By automating analysis and development tasks, we enable rapid data utilization.
In manufacturing sites, the utilization of equipment data is advancing for productivity improvement, quality enhancement, and equipment maintenance. However, these initiatives require not only knowledge and skills in manufacturing but also new knowledge and technologies such as IT and data science, resulting in more time and costs than anticipated. The time series data automatic analysis machine "CX-M" is designed to automate the analysis of time series data for abnormal detection and failure prediction, aimed at predictive maintenance and quality improvement for our customers (manufacturers). It automates the analysis tasks (data preprocessing, feature extraction, and creation of inference models (AI) through machine learning) and program development tasks that were traditionally performed by data analysis experts (data scientists), enabling users without data analysis knowledge to quickly perform advanced data analysis utilizing machine learning.
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basic information
**Advantages** 1. Automation of analysis tasks By automating data analysis tasks, initiatives can be advanced within the company's factory even without experts. 2. Operable within the factory Inference models (AI) created from analysis tasks can be immediately utilized in the equipment monitoring system without the need for program development. 3. Reduced initial costs A subscription-based contract system allows for the use of advanced features while keeping costs down. **Features** 1. Automatically generates highly accurate inference models by exploring optimal analysis methods. 2. Analysis functions tailored to the purpose of data analysis and equipment data. 3. Visualization of the characteristics and reasoning of inference models (AI). 4. Inference models (AI) are immediately available for use in monitoring systems. 5. Intuitive operation allows anyone to perform data analysis tasks.
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Applications/Examples of results
【Application Examples】 1. Issue: Abnormal detection of rotating bodies (bearings) ↓ Normal/abnormal classification from vibration and current data 2. Issue: Quality inspection of processed parts ↓ Judgment of good or bad from voltage and vibration data 3. Issue: Predictive maintenance of press machines ↓ Condition classification from current, vibration, and pressure data 4. Issue: Diagnosis of furnace operating conditions ↓ Judgment of operating conditions from temperature, gas data, etc.
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| Model number | overview |
|---|---|
| CX-M | This machine automates the time series data analysis and inference model (AI) generation for abnormal detection and failure prediction of equipment, aimed at customer predictive maintenance and quality improvement. |
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Company information
PB (Private Brand) Business Tokyo Electron Device’s PB business combines image processing, data science, and robotics to develop equipment and embedded solutions that automate and streamline operations in semiconductor and panel manufacturing, as well as factory and logistics environments. Through the inrevium brand, we offer a one-stop service from specification review and design to prototyping, evaluation, pilot production, and mass production. By leveraging our proprietary technologies and integrated in-house capabilities, we help customers improve development efficiency and productivity through automation and labor-saving solutions.
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