Hankook Tire develops AI and IoT based Condition Monitoring System+
- Establishing predictive condition monitoring system through real time anomaly detection
- Leading digital innovation by developing original technology in collaboration with KAIST
Seoul, Korea, April 20, 2020 – Leading global tire maker Hankook Tire developed a facility abnormality prediction system CMS+ (Hankook Condition Monitoring System Plus) based on artificial intelligence (AI) and internet of things (IoT), accelerating its development of smart factories.
Facility abnormalities can cause entire production lines to shut down as well as incur extra expenses and long hours spent on bringing it back to normal. Some symptoms of these abnormalities include change in the outputs, abnormal temperature rise, noise and vibration. Therefore, identifying minor symptoms in real time and performing maintenance in advance play the key role in preventing major facility failures.
In general, facility abnormality prediction system uses vibration sensor attached to key components of equipment. It requires experts to analyze the information collected by the sensor and determine if there is any symptom. However, Hankook, in order to improve accuracy in anomaly detection and cut down response time compared to the existing system, adopted AI and IoT technology to develop a new facility abnormality prediction system called CMS+.
The CMS+ uses 3-step AI algorithm which proceeds through ‘Next-generation wireless-based IoT module’, ‘Gateway’, and ‘Server’. This enables data analysis with precise prediction three to four times greater than the existing system.
During the first step that utilizes the IoT module, CMS+ collects and analyzes data every second whereas the conventional method collected sensor data only at regular intervals. It was impossible to store vast amount of sensor data transmitted in real time due to limitation in server capacity; however, the AI algorithm equipped in next-generation wireless-based IoT module and gateway made it possible to automatically sort out and selectively store the data suspected of abnormalities. This original AI algorithm was developed in cooperation with KAIST.
At the Gateway and Server level, CMS+ conducts an in-depth analysis of the data collected based on deep learning technology. It analyzes different types of data all together including sensor data, temperature, and operational information to predict abnormal conditions of the facility in advance. It is also equipped with a real time alarm system based on wireless communication technology. In case of anomalies, the system immediately alarms the manager, which allows the manager to take appropriate action much faster.
Hankook adopted the newly-developed system to factories in Korea and is in process of applying to all factories around the globe. The company is working on improving the system further by trying to integrate augmented reality (AR) to make it easy to identify data flow that is difficult to distinguish in the field. In the meantime, Hankook is expanding adaptation of AI step by step through joint research and development with KAIST to focus on establishing the smart factory.
In an effort to secure innovative R&D and digital technology capabilities and to realize digital transformation, Hankook signed an agreement with KAIST, a renowned science and technology university in Korea, in April 2019 for industry-academic joint research on future technologies. As a result, Hankook has made tangible achievement such as developing the ‘Virtual Compound Design (VCD) system’, a predictive model for tire compound properties using AI, as well as the ‘Automatic Inspection Process’ based on AI and digital sensor. As such, Hankook is taking a leading role in implementing smart factories that fuel digital innovation in tire industry.