Preventative maintenance is a must in any facility to ensure shortened downtime and to reduce im- pacts to production timelines. While there is a vast amount of preventative maintenance technologieson the market, one company decided they needed morethan a simple system to detect equipment failures.
New Equipment Digest spoke with Hankook Tire aboutits development of a condition monitoring system that incorporates AI and Io T technologies to improve its production efficiency at a rapid rate, as well as to accelerate theadvancement of smart factories.
NEW EQUIPMENT DIGEST (NED): What is the Hankook Condition Monitoring System Plus (CMS+) and whatdoes it do?
HANKOOK TIRE (HT): CMS+ is a facility abnormalityprediction system based on artificial intelligence (AI) andthe Internet of Things (Io T) developed by Hankook. It willhelp us double-check abnormalities efficiently, allowing usto accelerate the development of smart factories.
The system collects various data in real-time on vibration,noise, temperature, etc. to predict any abnormalities. CMS+studies the normal range data and finds those that are outside of that “normal range,” by using Hankook’s massivedata collection that has accumulated over time. The AI system also studies fault data, which uses a collection of datawe have from malfunctions, to determine abnormalitieswhen similar cases show up. Different sensors in proximi-ties collect data, which are then incorporated together foranalysis. The CMS+ system consistently studies all data tocreate this algorithm.
In detail: The CMS+ uses a 3-step AI algorithm whichproceeds through the next-generation wireless-based Io Tmodule, gateway, and server. This enables data analysis withprecise predictions three to four times greater than the existing system. During the first step that uses the Io T module,CMS+ collects and analyzes data every second, whereas theconventional method collected sensor data only at regularintervals. It was impossible to store the vast amounts of sensor data transmitted in real-time due to limitations in server capacity; however, the AI algorithm in next-generationwireless-based Io T module and gateway made it possible toautomatically sort out and selectively store the data suspected of abnormalities.
NED: Does the introduction of AI and IoT remove themanual analysis of data by experts?
HT: No. While the system cuts down on having to sortthrough all the data, this step is not removed. The systemwill serve as an additional step for us to double-check, andthe data will be collected for big data analysis, making dataselection faster.
Hankook’s experts created the system and will still ultimately be the ones making the final call on any abnormalities. The system is serving to assist Hankook’s experts withtheir works. With over 4,000 sensors installed, the systemanalyzes the data to see if there are any immediate abnormalities, and then Hankook experts make the final call.Once our experts finish the data analysis, the AI systemstudies the algorithm set, which will allow the system tomake a similar analysis like that of our experts in the future.
NED: How is this technology different from similar prediction maintenance systems already on the market? Whydid Hankook decide to develop its own?
HT: One may say that our system is similar to those alreadyout in the market. However, most of those systems do nothave the data that ours has accumulated over time, thusnot having the expert management applied in the systemyet. Hankook was not looking for a mere sensor data system—we needed a system that collects and analyzes qualitydata. We also needed it to have Hankook’s unique expertise,which was why we decided to develop the system ourselves.Yes, such technologies can be developed by IT or Algorithmcompanies, but it will not be perfect. Data knowledge fromall aspects needs to be accumulated and fused together. InHankook Technology Group, we have experts in all areassuch as manufacturing, IT, equipment, mechanics, etc. Withhelp from the Korea Advanced Institute of Science andTechnology (KAIST), we were able to create a system thatbest suited Hankook.
NED: How exactly has it helped Hankook’s productivity of production lines? What is the biggest change thathas happened?
HT: CMS+, in short, predicts the possible abnormality, allowing us to fix the problem ahead of time, preventing possible utility malfunction. This saves time and energy as themaintenance needed can be executed with minimal loss intime. For example, we performed a test run with a utilitythat was up for maintenance and the system immediatelyfound an equipment error, which was also confirmed byour experts. CMS+ will allow for double-checking of thesystem which will add reassurance in the analysis processand decrease the rate of doubts in oneself, helping our experts make efficient decisions on their reviews.
For more, visit newequipment.com/21131590
By Laura Davis
Leading global tire maker, Hankook Tire, has developed a facility abnormality prediction system based onAI and Io T technologies to detect and predict production line abnormalities before they become a problem.
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Photo Credit: Hankook Tire