Siemens launches AI solutions for predictive maintenance

Siemens is enhancing its Industrial Copilot portfolio with a new generative AI-powered solution for predictive maintenance.

Siemens' Industrial Copilot is a generative AI-based assistant designed to streamline various industry operations, from design and planning to engineering, operations, and services. By employing this assistant, engineering teams can expedite the generation of code for programmable logic controllers by an estimated 60%, effectively reducing errors and the need for specialised knowledge. This not only cuts down on development time but also enhances quality and productivity in the long term.

The company is now extending its Industrial Copilot offering with advanced maintenance capabilities as part of a broader strategy to redefine industrial maintenance. The introduction of the Senseye Predictive Maintenance solution, powered by Microsoft Azure, marks this expansion. The new solution aims to support every stage of the maintenance cycle by shifting from traditional practices to an intelligent, data-driven approach.

Siemens has developed two new offerings under the Senseye Predictive Maintenance line: the Entry Package and Scale Package. The Entry Package is intended as an accessible and cost-effective introduction to predictive maintenance, combining AI-powered repair guidance with limited predictive capabilities. This initiative helps businesses transition from reactive to condition-based maintenance, facilitated by sensor data collection and real-time condition monitoring. With AI-assisted troubleshooting, companies can lower downtime and improve maintenance efficiency, establishing a foundation for full predictive maintenance.

The Scale Package, on the other hand, targets enterprises aiming to fully transform their maintenance strategy. It integrates Senseye Predictive Maintenance with the comprehensive Maintenance Copilot functionality, enabling enterprises to predict failures before they occur, enhance uptime, and cut costs through AI-driven insights. With a focus on enterprise-wide scalability, the Scale Package offers automated diagnostics and supports sustainable business outcomes by optimising operations across multiple sites.

The expanded maintenance solution facilitates coverage of the full maintenance cycle, leveraging generative AI-driven insights to aid decision-making and enhance efficiency across industrial environments. As industries increasingly seek reliability and cost reduction, the move from reactive to proactive maintenance methods is gaining traction. Traditional maintenance strategies often lead to costly downtime and inefficiencies, issues that Siemens aims to mitigate with its AI-driven maintenance solutions.

By integrating real-time data and advanced analytics, the combination of generative AI and predictive maintenance ensures timely interventions and strategic planning. Initial pilot use cases have demonstrated that the Industrial Copilot for maintenance can reduce reactive maintenance time by an average of 25%.

"This expansion of our Industrial Copilot marks a significant step in our mission to transform maintenance operations," stated Margherita Adragna, CEO Customer Services at Siemens Digital Industries. "By extending our predictive maintenance solutions, we're enabling industries to seamlessly shift from reactive to proactive maintenance strategies and drive efficiency and resilience in an increasingly complex industrial landscape."

Siemens continues to pursue its vision of a digitalised industry by offering customers intelligent and integrated maintenance solutions to ensure long-term operational success.