Digital twin
Develop digital twins to simulate and emulate industrial systems
Integrate data analytics models in control systems
Service focused on developing machine learning models within the industrial environment, combining the expertise of OT and IT. Open Source tools are used, most notably Python and R languages. Within data analytics, the possibility of developing supervised and unsupervised machine learning algorithms to improve production processes, ready for integration in industrial automation systems, is particularly worthy of note. Predictive maintenance and industrial quality control are just some of the industrial applications possible thanks to these algorithms.
Moreover, this service consists of installing and configuring Edge Computing devices to collect and process data in the end user’s environment in real time. Data analytics models to estimate the most important predictive variables from the end user’s point of view can also be developed.
Develop digital twins to simulate and emulate industrial systems
Develop machine and process simulation projects
Control code debugging by emulating the automation system, signals, devices and processes
Develop virtual and augmented reality projects in order to streamline maintenance
Integrate sensorics and IoT connectivity in control systems