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Industrial AI
INCREASE ASSET AVAILABILITY AND DRIVE PERFORMANCE
FiiVESENSE AI

Humanise your machines and drive more value

Data driven predictive maintenance program for predicting future outcomes and maximising efficiency.

Fiivesense AI is a digital twin of your asset that will help to reduce your maintenance activity and improve asset performance.

This innovative and cost effective solution is developed using 3D game engine and powered by Artificial Intelligence. The system has two customisable layers, an interactive outer layer and artificially intelligent inner layer.

The outer layer consists of Laser scan Point Cloud data, 3D models, 2D drawings or photographs.

Inner layer is an artificial neural network that comprises of Big Data from IoT, condition monitoring sensors and also from manual data collection.

Different application specific Machine Learning and Deep Learning AI algorithms are applied to these datasets for performance insight and to prevent equipment failure.

Reduce your cost by evolving your asset maintenance strategy from time based approach to a proactive predictive maintenance (pdm) system.

Fiivesense monitors, learns and optimises people, process and assets across your ecosystem.

deck management

FiiVESENSE AI

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results and outcomes

get real insight using FiiVESENSE AI machine learning technology for maximising asset performance

Improve uptime

Reduce equipment trips and unplanned shutdowns by applying Machine Learning models to your complex data for predictive alerts and increased visibility.

See it before it happens !

Reduce personnel cost & time

Achieve deeper and real time operational know how and identify component failure. Mobilise the right resource and spares. Decrease OPEX and reduces excesses spare part inventory.

Enhance asset performance

Using our accurate 3D Digital Twin to seamlessly interact with your physical asset to visualise, monitor and control the asset remotely.

success story:Manufacturing

Multiple data sets in moulding process was analysed in FiiVESENSE AI using Deep Learning. Results clearly identified optimum mould time and key variables causing the defects. This reduced remedial work by 72%

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