Semiotic Labs, a company based in Leiden, Netherlands, and Germany’s SMS group signed an agreement under which the two companies will cooperate in the field of predictive maintenance. The AI-based technology developed by Semiotic Labs uses electrical signals and the data fingerprint of AC motors and other rotating equipment to monitor and analyze the condition of critical plant assets and enable reliable and early prediction of developing faults. SAM4 operates based on sensors installed directly in the control cabinet – not on the asset itself. This solution is particularly useful for the monitoring of equipment in the metallurgical industry.

SAM4 has already been implemented successfully on numerous hot-strip mills and other applications in steel plants throughout Europe. The results achieved by SAM4 under such highly demanding in-service conditions and tests at SMS group’s workshops led to the decision to make this technology part of the SMS product portfolio.

According to SMS group, SAM4 will be integrated as an app into the MySMS platform. The companies also plan to integrate SAM4 into GeniusCM, SMS group’s condition monitoring system.