TIA AssetHealth consists of applications where meaning is drived from data by using algorithms focused on monitoring and forecasting, real-time data analysis on cluster or streaming data and anomaly detection algorithms are used. It allows for condition monitoring and anomaly detection as well as estimation of the remaining useful life of the asset.
It includes computational or analytical models necessary to describe, understand and predict the operational states and behavior of assets. These models include physics-based models, 3D engineering or simulation models, statistics-based data models, optimization models, machine learning, and artificial intelligence models. With the condition monitoring platform developed for predictive maintenance, operational and automation data obtained from different machines and sensors are analyzed, increasing the total equipment performance (OEE) and monitoring it with metrics.
There are components, graphics, game engine interfaces that include 3D digital models of the component parts of the asset, sensor points and dashboards of sensor data. Being a flexible system, TIA AssetHealth can be customized according to the specific needs and requirements of the users.
TIA SENSOR services enable the users to select the optimum set of sensors. The service implements the optimum sensor set for the machines.
TIA STREAM enables the users to transfer data from data sources to the related destinations, TIA PLATFORM modules and/or different destinations.
TIA MONITORING is a module that enables predictive maintenance using the condition monitoring method used in machine maintenance.
TIA DASHBOARD is a data visualization module developed with the involvement of real users.
