OVERVIEW
The changes in the markets of the global economy, the increase in the complexity of manufacturing systems, the need to speed up customer demands, with customised products available immediately, has led to a generational change, which can be tackled by introducing new technologies, which will transform companies and factories in general with its plants into a new way of producing. The expression Industry 4.0 expresses a vision of the future according to which, thanks to digital technologies, industrial and manufacturing enterprises will increase in competitiveness and efficiency through the interconnection and cooperation of existing resources inside and outside the Factory.
BUSINESS CASE.
Companies in the manufacturing market need to equip themselves not only with enabling technologies to capture production data and alarms, but with true off-the-shelf assets that integrate into product improvement and factory efficiency processes.
The current market landscape, while rich in technology pattaform proposals, does not address the ‘need to rely on a single partner to provide the technologies and expertise to implement the IoT project and also the strategic advice and ability to govern a project within the required timeframe and constraints.
SOLUTION AND BUSINESS VALUE
Connected Factory is Bitia’s proposal for Industry 4.0, which concentrates years of experience in the world of new digital and IoT technologies, with solutions that are immediately usable and quickly demonstrable, connecting existing plants and providing, in addition to technologies, “assets” with high added value for the company’s business : calculation of plant efficiency (OEE), downtime analysis, management of requests for intervention, are just some examples of the functionalities made available by our solution.
Bitia is able to provide its expertise along the whole “End-to-End” chain of an IoT project : from PLC or sensor data mapping, through the IoT platform and the cloud, we implement the applications for real time data analysis and visualization, combined with the data lake for “deep” and predictive analysis.