MISSISSAUGA, ON – Oct 24, 2020 – Schneider Electric, the leader in digital transformation of energy management and automation, and Semiotic Labs, a provider of an AI-driven predictive maintenance solution for AC motors and rotating equipment, have signed a partnership agreement. This agreement will broaden Schneider’s managed service offering to now support the monitoring of rotating equipment including induction motors, pumps, conveyors, and compressors.
This expanded digital service enables the implementation of an optimal condition-based maintenance strategy for critical motors, vital to the reduction of costly unplanned process downtime. The integration of Semiotic Labs’ predictive analytics into Schneider’s EcoStruxure Asset Advisor platform enables the prediction of upcoming failures up to six months in advance, thereby giving maintenance teams the time they need to resolve potential failures before they happen. The expanded service gives plant and operations managers a unified user experience and remote expert service team, through Schneider’s Connected Service Hub, for a single view of the health of a broad portfolio of critical, multi-site assets.
“We know that enabling resiliency by minimizing costly unplanned downtime and on-site interventions is paramount to driving higher operational efficiency,” says Stephane Maravel, Schneider’s SVP for Digital Services. “This new partnership with Semiotic Labs expands our digital service offering to now enable condition-based monitoring of rotating equipment, an asset class deemed highly critical by our customers.”
Semiotic Labs’ SAM4 system delivers market-leading accuracy, offering the highest levels of savings due to the innovative AI-based technology that uses electrical signals and the data fingerprint of AC motors and other rotating equipment to monitor and analyze the condition of critical plant assets, enabling reliable and early prediction of developing faults. In contrast to traditional, vibration-based solutions, SAM4 operates based on sensors installed directly inside the motor control cabinet – not on the asset itself. Because of this, the solution is a good complement to Schneider’s broad portfolio and installed base of motor management assets, and leverages Schneider’s expertise across the electrical domain.
Through this tight integration, EcoStruxure Asset Advisor powered by SAM4 analytics provides Schneider customers with robust asset reliability. SAM4’s advanced machine learning algorithms also provide performance and energy insights that drive improved asset management efficiency and effectiveness.
“This partnership is great news for Schneider Electric customers who are looking to increase uptime and decrease energy waste,” says Jasper Hoogeweegen, CEO of Semiotic Labs. “It puts customers in a position to prevent machine failures and significantly reduce energy usage.”
About Semiotic Labs
Semiotic Labs was established in 2015 with the aim of making maintenance 100% predictable. An expert team of data scientists, software developers and technical specialists develop AI-driven predictive maintenance solutions for AC motors and rotating equipment. Our clients and partners include industry leaders such as ArcelorMittal, Nouryon, Sappi, Vopak and Xylem.
About Schneider Electric
Schneider Electric is leading the Digital Transformation of Energy Management and Automation in Homes, Buildings, Data Centers, Infrastructure and Industries. With global presence in over 100 countries, Schneider is the undisputable leader in Power Management – Medium Voltage, Low Voltage and Secure Power, and in Automation Systems. We provide integrated efficiency solutions, combining energy, automation and software. In our global Ecosystem, we collaborate with the largest Partner, Integrator and Developer Community on our Open Platform to deliver real-time control and operational efficiency. We believe that great people and partners make Schneider a great company and that our commitment to Innovation, Diversity and Sustainability ensures that Life Is On everywhere, for everyone and at every moment.
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