EN
TIA Platform is composed of four main modules, each of which includes multiple interoperable applications: TIA IoT, TIA DATA, TIA APPS, TIA UX. Establishing a network of things, TIA IoT enables a platform to acquire multisensory data from assets. TIA DATA transfers, stores and preprocesses data collected by means of TIA IoT. TIA APPS contains different applications that can be used for different purposes including smart condition monitoring, anomaly detection, predictive maintenance, energy minimization and parameter optimization for diverse objective functions. TIA UX provides supreme visualization & control in digital twins.
In addition to providing real-time condition monitoring for assets, processes and vehicles, TIA Platform offers tools to enable forward-looking strategic and operational decision-making processes complemented with Artificial intelligence algorithms and models.
Apps
TIA Platform provides end-to-end customized solutions with its product portfolio.
TIA AssetHealth has been developed to predict and prevent failure situations, and to provide optimum management of the maintenance process.
TIA MachineHealth introduces a comprehensive solution for real-time monitoring and analysis of various types of manufacturing equipment.
TIA CNCHealth has been developed to detect and predict significant changesand anomalies in the behavior of CNC machines and tool wear.
TIA QualityHealth has been developed to prevent defective products and performs quality assurance operations through computer vision and automation applications.
TIA ProcessHealth has been developed to allow the use of intelligent algorithms to optimize the production process.
TIA VehicleHealth has been developed to monitor the performance of mobile vehicles in real-time.
Please find here the abstract and URL of the paper presented at FiCloud 2019 7th International Conference on Future Internet of Things and Cloud (FiCloud).
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Hello friends, in my previous articles, I told you about the issues I found important about Figma. Now I want to talk about a few plug-ins that will make your job easier when using Figma. The community section in Figma is nice and actively used. People help each other by actively sharing what they do here.
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In general, LSTM is a recurrent neural network (RNN) architecture that operates on time-ordered incoming data. Before we start analyzing LSTM networks, it is useful to understand the recurrent neural network (RNN) and how LSTM differs from the classical RNN. In a feed-forward neural network, information travels only in the forward direction, whereas in an RNN, information rotates through a loop.
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