Technical background

Athens predictive failure diagnosis

can help you prevent unforeseen equipment problems

Athena

Fault prediction service

Developed failure prediction algorithm after collecting necessary data according to the manufacturing site situation, and provides failure prediction service that guarantees high reliability by using high performance RNN deep learning algorithm for machine learning and time series data analysis through pattern analysis

 

Health Diagnostic Service

In addition to the ultrasonic data, it can be customized according to the customer’s request such as temperature, humidity, vibration, current, and sensor

Apollon

Ultrasound data acquisitionIn

addition to collecting data on temperature, humidity, vibration, and current of companies related to existing facilities, it can also measure “ultrasound” acoustic signals that cannot be measured by the human ear.

 

Contactless products

By collecting ultrasonic sound signals, the sensor does not have to be in direct contact with the equipment, so there is no risk of damaging the sensor from external shocks

Features

Ultrasonic Analysis

Diagnose failure cause through inaudible frequency band analysis

Deep learning

In-house developed deep learning algorithm provides

high accuracy equipment failure prediction service

Customized

Offer on-demand failure prediction service upon customer request

Process

Benefit

cut down the money

· Increased efficiency of manpower operation

· Repair cost reduction

· Increased consumable replacement cycles

Increased productivity

· Increase overall facility efficiency

· Improvement of equipment life

Quality improvement

·Quality improvement

Case Study

Injection machine

cutter

It is used in various manufacturing sites such as

plastic injection molding machines and plastic manufacturing cutters