The Electronics activity of LACROIX announces a new partnership with Cartesiam, a B2B software developer specialising in “Edge” onboard artificial intelligence. LACROIX is thus improving its design and manufacturing services for connected electronic objects intended for the predictive maintenance market.
The IoT is a turning point for the industrial sphere because in the future, almost all products will have built-in sensors. With the industrial IoT, personal data is gradually moving aside to make way for strategic industrial data.
Our partnership with Cartesiam strengthens the position of LACROIX in this future-facing market.
With this in mind, the Electronics activity of LACROIX tested Cartesiam’s NanoEdgeTM AI Studio solution in-house by fitting intelligent vibration sensors to its reflow ovens with the objective of optimising maintenance.
Following the successful implementation of this in-house solution, the Electronics activity of LACROIX has chosen to work with Cartesiam on predictive maintenance in industrial environments in order to enhance its skills and products.
Thanks to this pooling of expertise, the Electronics activity of LACROIX can offer its customers a variety of onboard artificial intelligence sensor solutions based on our technology.
LACROIX and Cartesiam are therefore joining forces to overcome the hurdles of breaking into the field of industrial artificial intelligence together: creation, collection and management of data, IT security, necessary presence of data scientists, etc.
Artificial intelligence is a key factor in the development of the industrial IoT, namely because it tackles the three main challenges facing manufacturers today:
Data analysis takes place where the data itself is produced and the sensor is therefore able to select the relevant data to send to the cloud. This step results in a significant reduction in the processing costs of energy-intensive servers. This reduction in the need for storage considerably reduces the product’s environmental footprint.
Edge AI technology allows instantaneous responsiveness because the data collected is processed on site and in real time. In the field of machine monitoring, timing is crucial.