(1) Real-time monitoring – plant data will be stored and visualized, so that the system status can be accurately evaluated.
- A self-developed AI platform that is designed for solving E&M operation and maintenance (O&M) problems by leveraging AI, Big Data, and Machine Learning technology. It consists of three main components – Visualization Module, Prediction and Machine Learning Engine, and AI Optimization Engine.
- Those AI engines can be interoperated to provide flexibility for tailor-made a best fit solution in different complex conditions. The O&M decision making process can be automated and optimized to enhance the sustainability and maintainability of the facility management service.
- The platform can be applied in chiller plant management,
(2) Optimization – technicians’ knowhow can be retained and optimized via machine learning and optimization engine. And it will use the knowhow to generate optimized operation sequence for chiller plant management with different objectives, such as energy efficient, load-balancing, and so on.
(3) Predictive maintenance – The machine learning engine can be used to identify fault patterns of equipment in the chiller plant in order to predict failure of equipment for predictive maintenance purpose.