The Siemens Industrial Copilot is a generative AI-based assistant enabling customers to leverage generative AI across the value chain – from design and planning to engineering, operations, and services. For example, the Industrial Copilot empowers engineering teams to generate code for programmable logic controllers using their native language, speeding-up SCL code generation by an estimated 60% as well as minimising errors and reducing the need for specialised knowledge. This in turn reduces development time and boosts quality and productivity over the long term.
Siemens is developing a full suite of copilots to industrial-grade standards for the discrete and process manufacturing industries. It has now introduced an advanced maintenance solution.
Generative AI throughout the maintenance cycle
The new generative AI-powered solution is designed to support every stage of the maintenance cycle, helping industries to move beyond traditional maintenance practices towards an intelligent, data-driven approach. To realise this, the Senseye Predictive Maintenance solution powered by Microsoft Azure is being extended with two new offerings.
The Entry Package provides an accessible and cost-effective introduction to predictive maintenance, combining AI-powered repair guidance with basic predictive capabilities. It helps businesses transition from reactive to condition-based maintenance, providing limited connectivity for sensor data collection and real-time condition monitoring. With AI-assisted troubleshooting and minimal infrastructure requirements, companies can reduce downtime, improve maintenance efficiency, and lay the foundation for full predictive maintenance.
The Scale Package is designed for enterprises looking to transform their maintenance strategy fully. It integrates Senseye Predictive Maintenance with the full Maintenance Copilot functionality. This enables users to predict failures before they happen, maximise uptime, and reduce costs with AI-driven insights. Offering enterprise-wide scalability, automated diagnostics, and sustainable business outcomes, this solution helps companies move beyond traditional maintenance, optimising operations across multiple sites and supporting long-term efficiency and resilience.
The new offering enables comprehensive coverage of the full maintenance cycle – from reactive repair to predictive and preventive strategies – by leveraging generative AI-driven insights that enhance decision-making and efficiency across industrial environments.
As industries increasingly seek ways to strengthen reliability and reduce costs, maintenance operations are evolving from reactive to proactive approaches. Traditional maintenance strategies can often lead to costly downtime and other inefficiencies. Siemens addresses this challenge by integrating AI-driven maintenance solutions that help companies optimise their asset performance and maximise operational uptime. The fusion of generative AI and predictive maintenance enables customers to harness real-time data and advanced analytics, guiding timely interventions and strategic planning. First pilot use cases have shown that the Industrial Copilot for maintenance helps save on average, 25% of reactive maintenance time.
“The expansion of Industrial Copilot marks a significant step in Siemens’ mission to transform maintenance operations,” said Margherita Adragna, CEO Customer Services at Siemens Digital Industries. “By extending our predictive maintenance solutions, we’re enabling industries to shift from reactive to proactive maintenance strategies and drive efficiency and resilience in an increasingly complex industrial landscape.”
With this innovation, Siemens continues to advance its vision for digitalised industry, providing customers with an intelligent and integrated approach to maintenance that supports long-term operational success.
For more information visit: www.siemens.com