CAPITAL ASSETS REPLACEMENT PREDICTION
CARP
Government Institutions, Hospitals, Oil&Gas, Public Transportation Systems, and International Airports understand the need to use Artificial Intelligence in Capital Assets Replacement Prediction. The non-stop operation of all critical devices like escalators, lifts, shuttles, tramways, trains, magnetic resonance imaging, air conditioning, robots, automatic doors, and gangways generate maintenance costs that increase over time.
There is a crossover point where one might consider replacing the asset instead of fixing it. Being able to predict precisely when the replacement will be optimum to ensure service continuity and the minimum cost is a complicated matter.
HOW TO USE ARTIFICIAL INTELLIGENCE TO GREATLY
REDUCE OPERATIONAL COSTS?
CAPITAL ASSETS REPLACEMENT PREDICTION
is using data science, machine learning, and big data analytics in processes related to the maintenance and replacement of capital assets. CARP develops a prioritized asset upgrade and replacement plan, spanning long-term horizons and predicting optimum cross-over points in time.
ARTIFICIAL INTELLIGENCE ENGINE
Using time series models leveraging the huge amount of data collected through telemetry and maintenance surveys, as well as an approach based on state-of-the-art machine learning and Artificial Intelligence techniques, ADGS is able to provide Public Institutions with a solution to optimize the use of capital and operating expenses, lowering operational costs in a predictable way.
• Helps to increase the availability of mechanical and electrical assets
• Predicts corrective maintenance operations year by year
• Helps to build an accurate operations budget for the coming years
• Schedule the best time to replace equipments
SENIOR MANAGER IT - HIA DIGITAL SYSTEMS & PROJECTS HAMAD INTERNATIONAL AIRPORT QATAR
David Luong
"ADGS’S NOVEL APPLICATION OF STATISTICAL METHODS TO PREDICT WHEN EQUIPMENT CAN BE REPLACED WILL ASSIST THE HAMAD AIRPORT TO OPTIMISE ITS ASSET MANAGEMENT PRACTICES."
CARP
• Operates by collecting data like telemetry and maintenance logs, oil analysis, infrared or X-ray non-intrusive data collection, etc...
• Predicts unexpected operation maintenance and possible downtime
• Then predicts when asset replacement will be optimum to maintain operational cost as low as possible
• Lowers operational costs for Airports, Public Transportation, Construction, Mining, Oil and Gas, Military, Industry and Hospitals