Categories: Automobiles

Predictive maintenance: BMW adopts technological diagnostic systems

Predictive maintenance consists of an early warning system in the production phase. Technology can predict failures before they occur. An interesting and technological system that the BMW Group has decided to adopt throughout its production network.

Predictive maintenance: when prevention is better than cure

BMW Group has decided to implement state-of-the-art sensors for the maintenance of its production plants, sensors based on artificial intelligence (AI). In this way, by analyzing the data in real time, it will be possible to carry out the process of predictive maintenance. A system whereby a problem is predicted well before it occurs. The management of the systems is therefore optimized, with positive impacts also on efficiency and sustainability.

The sensors will take care of monitoring equipment and parameters. In this way, the AI ​​is able to predict the occurrence of failures and problems. A true industrial application of the concept prevention is better than cure. Once the potential failure has been detected, the system will also suggest a possible solution such as replacing a particular component.

Checking the health of machinery via the cloud

Predictive maintenance uses a state-of-the-art cloud platform to get early alerts on potential production outages. The data comes directly from the production plants, and allows constant monitoring of the entire production network. Individual software modules within the platform can be flexibly activated and deactivated, as needed, to immediately adapt to constantly updated specifications. Furthermore, thanks to the high degree of standardization between the individual components, the system is globally accessible, highly scalable and allows you to easily implement new application scenarios and quickly activate existing solutions.

Predictive maintenance makes repairs more accurate and cost and resource efficient. In addition, the prolongation of operating times considerably extends the life cycle of instruments and implants.

Published by
John Vassallo

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