AI-based Equipment Maintenance Management System

I&T Solution AI-based Equipment Maintenance Management System
(REF : S-0169)
Solution Feature
  • A self-developed AI system that is designed for solving E&M operation and maintenance (O&M) problems by leveraging AI, Big Data, and Machine Learning technology. It can be applied in medical equipment maintenance. It consists of three main components – Visualization Module, Prediction and Machine Learning Engine, and AI Optimization Engine.
  • Those AI engines can be interoperated in order 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 in order to enhance the sustainability and maintainability of the equipment management service.
  • (1) Spare parts demand forecasting – By analysing spare part criticality, demand characteristics, parts consumption pattern from the historical record and the actual usage, it can predict the demand for each part to reduce the inventories while maintaining the required service level.
  • (2) Optimization/ Trouble shooting – Maintenance knowhow can be learned and optimized by the machine learning engine through the maintenance log. And the system will use the knowhow to give recommendation on the maintenance action.
  • (3) Predictive maintenance – The machine learning and optimization engine can be used to identify fault patterns of equipment in order to predict the failure of equipment and optimize the maintenance schedule based on predicted parts life-cycle, spare parts availability and technician availability.
Trial Application and Expected Outcome
  • A trial of the system can be conducted with a number of selected medical equipment.
  • (1) Develop a tool for parts consumption patterns analysis, and what-if analysis
  • (2) Deploy an AI model for spare parts demand forecasting with the user interface system displaying on a desktop computer for the operator to monitor and control
  • (3) Deploy an AI model for continuous maintenance prediction with recommended actions for medical equipment with the user interface system displaying on a desktop computer for the operator to monitor and control
  • (4) Deploy an AI model for an optimized maintenance schedule for medical equipment with the user interface system displaying on a desktop computer for the operator to monitor and control
Info on I&T Solution Provider
Solution Provider:Optix Solutions Limited
Address:Unit B, Level 18, YHC Tower, Sheung Yuet Road, Kowloon Bay, Hong Kong
Contact Person:Spencer Fung
Position:CEO and Founder
Tel: 2351 7780
Email: sfung@optix.com.hk
Webpage: sfung@optix.com.hk

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