ContiTech invests in Israeli industrial sensing startup 

Hanover, Germany – Continental AG is expanding its predictive maintenance and remote monitoring expertise for automotive, industrial and manufacturing applications, through a minatory stake acquisition in an Israeli startup.
 
The German group said it had invested an undisclosed amount in Tel Aviv-based Feelit, which provides “cutting-edge predictive maintenance solutions for various industrial equipment and machinery.”

The start-up has developed a structural sensing technology that is up to 50 times more sensitive than current standard market applications, Conti said in a 12 July statement. 

Feelit uses printed, nanomaterial-based, fully integrated sensors and cloud analytics to provide live, remote feedback on structural and performance changes in equipment. 

The sensors can be integrated, for example, into battery cooling systems for electric vehicles to optimise battery life and range. 

Furthermore, the group can see additional potential for remote monitoring and predictive maintenance applications for its industrial hoses for the food and beverage industry and for hydraulic and energy solutions.

“The investment further paves our way toward digitalisation and brings with it multiple strategic benefits,” said Philip Nelles, head of Conti’s industrial arm ContiTech. 

According to Nelles, the sensors can be integrated into both new and existing product lines to support the group’s transformation toward “smart and sustainable solutions beyond rubber.” 

Founded in 2017, Feelit has developed a “highly sensitive, flexible, printed nanomaterial sensor” that can be attached to static and rotating machinery parts, including flat and rounded surfaces. 

The sensor measures strain in ultra-high resolution, as well as other parameters such as temperature, vibration and pressure. 
 
Based on an industrial IoT platform for real-time remote sensing of structural changes in mechanical assets, the system serves as an “electronic skin” that sends an alert if it detects critical structural and operational anomalies in advance.