Last week, the Matrix team revealed the formation of the Yangdong Artificial Intelligence Research Institute. The research institute is currently developing several “Smart City” and “Smart Logistics” projects. This article delves deeper into the Matrix’s enterprise-grade dig data cloudchain solution — unofficially dubbed the Matrix Enterprise Cloudchain.
The Birth of a Platform
The Matrix Enterprise Cloudchain aims to support the operations and maintenance of several industrial production applications by providing distributed computing resources based on the blockchain, data and an AI model ecosystem. It relies on two major architectures. The first is a platform that controls the system’s core functionality — essentially a fog computing layer that performs core functions for the platform and enables data storage, enterprise-grade data throughput capacity and enterprise-grade data processing capabilities. The second is a predictive health management (PHM) system to track the status of equipment. The system is supported by the National Natural Science Foundation of China, the CRRC and the China Railway Corporation, amongst others.
The Matrix Enterprise Cloudchain makes full use of Matrix’s AI expertise in supporting industrial data analysis and operations status monitoring applications. It has the ability to troubleshoot equipment and optimize operations and maintenance using deep learning strategies, machine learning strategies and GANs, amongst others. The Matrix Enterprise Cloudchain also integrates ERP systems, production line management and work order systems. It supports real-world business processes with visualizations and other reporting tools. It can also integrate with third-party system interfaces and allows companies to access existing systems in an effort to reduce costs by eliminating unnecessary and repetitive development.
Four Building Blocks
Products and applications built on the Matrix Enterprise Cloudchain rely primarily on four core technologies. The first is symbolic regression, which is used to identify failure states and fit them to models. The second is two-stage GANs that are applied to small data samples for the purpose pattern recognition. The third is deep neural networks for image recognition and object detection for the purposes of monitoring and detecting products, processes and personnel status. The fourth is models that integrate industrial domain knowledge to enable automatic reasoning in various industrial fields.
Presently, this technology is being applied and tested in Kenya’s Mombasa–Nairobi Standard Gauge Railway. Currently, with the help of smart meters and remote data centers, 48 locomotives exported to Kenya by the CRRC Corporation Limited are being monitored to optimize the management, maintenance and operations of the trains.
This technology is also being used in the Matrix Enterprise Cloud’s predictive health management (PHM) system. The PHM system is used to complete design improvement, optimize operations and optimize maintenance of industrial equipment. It can also estimate the remaining lifespan of equipment and components, automatically diagnose faults and issue repairs. The Yangdong Artificial Intelligence Research Institute expects that the PHM will greatly improve operations and maintenance efficiency, reduce maintenance costs and support the sustainable development of the railway industry, amongst other things.
China’s Belt and Road Initiative was proposed in 2013. One important component is a network of six land-based economic corridors that are to serve as the basis for inter-regional commerce and trade. High-speed rails are a key part of these corridors. It is estimated that by 2020, the annual value of the rail industry will reach 200 Billion RMB. The operations and maintenance testing market is expected to reach 50 Billion RMB in that time. This emerging market has spawned the rapid development of industrial big data platforms and equipment maintenance technologies. Matrix’s Yangdong Artificial Intelligence Research Institute hopes to optimize the existing operations system and jointly apply for research projects with local governmental bodies and other private research institutions.