Huakong Zhijia
AI-powered predictive maintenance for industrial equipment.
| Date | Investors | Amount | Round |
|---|---|---|---|
* | N/A | - | |
| Total Funding | 000k | ||
Beijing Huakong Zhijia Technology Co., Ltd., founded in May 2018, is an industrial internet and artificial intelligence platform company that emerged from the commercialization of scientific and technological achievements from Tsinghua University. The company specializes in intelligent operations and maintenance for industrial equipment, leveraging proprietary technologies such as subtle feature extraction and low-resource AI. Its core solutions include predictive health maintenance based on machine fingerprints and big data analysis, alongside intelligent optimization of operational parameters.
The founding team has deep roots in Tsinghua University. Co-founder and CEO Liu Deguang is a Tsinghua alumnus, while co-founder and Chief Scientist Liu Jia is a professor in the Department of Electronic Engineering at Tsinghua, with three decades of research in intelligent signal and information processing. Other co-founders, Zhang Weiqiang and He Liang, are also associate professors in the same department. This academic and research-driven foundation provides the company with a significant technological edge.
Huakong Zhijia's business model is centered on providing advanced monitoring and predictive maintenance solutions that help industrial enterprises enhance safety, save energy, reduce emissions, and increase efficiency. The company has developed a smart edge computing terminal that collects and processes multi-sensor data in real-time, including sound, vibration, and temperature. This data is then analyzed using deep learning and knowledge graph models to diagnose potential failures at a very early stage and optimize equipment performance. Its client base consists of major state-owned enterprises in the energy sector, such as the State Grid, State Power Investment Corporation, China Energy, and others in hydropower and wind power.
Keywords: industrial internet, predictive maintenance, artificial intelligence, machine learning, equipment health monitoring, smart manufacturing, AIoT, big data analytics, sound vibration analysis, energy efficiency, industrial IoT, asset performance management, Tsinghua University, intelligent operations, anomaly detection, machine diagnostics, edge computing, sensor fusion, knowledge graph, condition monitoring