China Unicom greatly increases fault handling efficiency and reduces costs with intelligent fault management tool.
China Unicom uses AI knowledge graphs in move towards more autonomous networks
Who: China Unicom
What: Increasing the efficiency of fault handling across its mobile networks
How: China Unicom collaborated with Nokia and Baidu to develop and deploy an intelligent fault management tool based on AI knowledge graph technology to better identify and resolve network faults.
Traditionally, network operation and maintenance has been a largely manual process. Not only is this time-consuming, but the results can be patchy, in part because employees bring different levels of experience, knowledge and expertise to the task of identifying and solving problems.
China Unicom, for example, found that 40% of its network fault management analysis was manual, and consumed 158,400 person-working-days per year at an annual cost equivalent to 18 million euros.
To top it all, the operator wasn’t even reaching the desired levels of efficiency. It took an experienced engineer between 30 minutes and 1 hour to deal with a 5G network fault, from identification, and root cause analysis, through to decision-making. This meant one person handled on average up to 12 problems a day.
China Unicom needed to go faster. It an extensive 5G network and at the end of October this year reported 251.943 million 5G package subscribers, as well as 474.387 million internet-of-things terminal connections, and 7,441 customers served by virtual 5G industry private networks.
It wasn’t only a question of resolving issues more quickly. China Unicom also wanted to greatly speed up the dissemination and use of knowledge. It points out that in the case of intelligent fault management, for example, it can take at least two months to acquire insight from the summaries provided by experts. Automation was the answer.
Automating network operations
In 2021 China Unicom set out to develop and deploy a network O&M knowledge center based on AI knowledge graph technology, which it could use to manage faults across multiple mobile domains, while addressing different scenarios, including network planning, construction, maintenance, optimization and operations. All while supporting rapid automation of its network operations.
“Based on knowledge graph technology, the solution can automatically collect, integrate and conclude multi-domain network operation and maintenance knowledge, realize the transformation from artificial experience to knowledge intelligence, and finally form a knowledge closed-loop to serve various scenarios of the Autonomous Networks,” according to China Unicom.
China Unicom has recorded numerous benefits from deploying the new system:
Whereas it can take at least two months to manually summarize experts’ mobile network cross-domain fault handling insight, with a knowledge graph technology the time needed falls to between two and four weeks. In addition, there is a more comprehensive gathering of content, resulting in a 38% increase in knowledge.
Prior to deploying the knowledge graph, on average 40% of the network fault analysis was manual, which cost around 18 million euros per year and demanded approximately 158,400 person-working-days. Now only 15% of network fault analysis is manual, saving 11.3 million euros annually.
With the knowledge graph most problems can be identified and analyzed automatically, reducing the average process time from 45 minutes previously to 15 minutes today.
The operator’s Root Cause Analysis accuracy rate used to be around 70%; since deploying the AI knowledge graph this figure has increased to 89%.
Today 100% of the inference processes can be explained, compared to 75% in the past, which helps front-line engineers understand recommended actions.
TM Forum standards provide a framework for automation
China Unicom worked with Baidu and Nokia to design and implement the knowledge graph solution using TM Forum’s Autonomous Networks Framework (IG1218 Autonomous Networks – Business requirements & architecture Version 2.0.0, IG1253 Intent in Autonomous Networks Version 1.0.0) and Open APIs (TMF921 Intent Management API).