How to use Artificial Intelligence to greatly
reduce operational costs?

Government Institutions, Hospitals, Oil&Gas, Public Transportation Systems or International Airports understand the need to use Artificial Intelligence in Capital Assets Replacement Prediction. The non-stop operation of all the 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 exactly when the replacement will be optimum to ensure service continuity and minimum cost is a complicated matter.

Capital Assets Replacement Prediction

is using data science, machine learning, and big data analytics into processes related with 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 optimise the use of capital and operating expenses, lowering operational costs in a predictable way.

• Helps to increase availability of mecanical and electrical assets
• Predicts corrective maintenance operations year by year
• Helps to build an accurate operations budget for the coming years
• Schedules the best timing to replace equipments

ImageDavid 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."

Senior Manager IT - HIA Digital Systems & Projects Hamad International Airport Qatar


• 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