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“The daily maintenance coverage rate increased to more than 99%. This means that we catch defects early and can replace the deformed chains before they break—avoiding costly outages that impact production.”
At-a-Glance
- Customer: China Coal Huajin Group
- Industry: Energy and Utilities
- Product Family: Servers,Desktops & AIOs
- Region: China
- Processor: Intel,MediaTek
- Topic: Artificial Intelligence,Big Data and Analytics
Extracting the power of AI
Scraper chain conveyors transport coal to the surface. Over time, the chains deform and break. To reduce the risk of outages and minimize the time that staff need to spend underground, CCHG aimed to automate maintenance inspections. CCHG engaged the Lenovo Research Institute to develop a computer vision application that uses AI on camera streams to identify signs of wear and damage on scraper chain conveyors.
By automating the inspection process, CCHG can accurately identify chain defects without having to send maintenance teams underground. They can take early action to prevent chain breakages and keep production
on track.
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