AI-based Decision Support System for Operation and Maintenance in Facility and Asset Management
| I&T Wish | AI-based Decision Support System for Operation and Maintenance in Facility and Asset Management (REF: W-0143) |
|||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Matched I&T Solution | ||||||||||||||||
| Trial Project | ||||||||||||||||
| Summary and Challenges | This project is to develop an integrated system encompassing AI, Big data and optimisation technology to improve the operation and maintenance (O&M) processes in facility and asset management. The system should be capable of managing a chiller system for operation sequencing decisions. It should help reduce manual effort in O&M and provide real-time what-if analyses for different operation configurations. It should also achieve different objectives for facility optimisation, such as minimising energy consumption, load balancing for equipment, minimising down-time risk and so on. The system should come with a dashboard for visualising the outcome of different configurations for the facility. The extendibility and maintainability of the system are of much concern for future expansion, such as optimising the workforce for O&M, electrical system, and so on. In addition, the system should be able to interoperable with different AI models in order to provide flexibility to cope with different complex O&M situations. For example, the system shall detect and predict equipment fault, and self-adjust the decision strategy automatically. The system should trigger alert if an equipment fault is predicted. |
|||||||||||||||
| Expected Outcome | This project aims to :- 1. enhance the E&M operation and maintenance quality. 2. enhance the sustainability by quantifying and retaining technicians and engineers knowhow in facility and asset management.
3. rationalize the planned and unplanned maintenance tasks. 4. enhance the efficnency of a chiller system. 5. promote wider application of AI, Big Data and optimization technology for improving efficiency. |
|||||||||||||||
| Expected Trial Duration | 12 months (2/2019-2/2020) |
|||||||||||||||
| Contact Information |
|
|||||||||||||||
| Upload Date | 2018-12-24 | |||||||||||||||
| Closing Date | 2019-01-07 | |||||||||||||||
| Propose I&T Solution | Closed |