Siemens recently announced an expansion of its Industrial Assistant, introducing advanced maintenance solutions powered by generative AI. This tool, called "Siemens Industrial Assistant," aims to help customers leverage generative AI across the entire value chain, from design and planning to engineering, operations, and service.
The assistant notably supports engineering teams in generating Programmable Logic Controller (PLC) code in their native language. This process is estimated to increase SCL code generation speed by 60%, while simultaneously reducing errors and lowering reliance on specialized expertise. This innovation not only shortens development time but also improves long-term quality and productivity.
Siemens' new generative AI solution will cover every stage of the maintenance lifecycle, empowering industries to move beyond traditional maintenance practices towards intelligent, data-driven maintenance. To achieve this, Siemens is launching two new products based on its Microsoft Azure-powered Senseye predictive maintenance solution.
The first is the "Starter Package," offering a cost-effective entry point to predictive maintenance, combining AI-driven repair guidance with basic predictive capabilities. This helps companies transition from reactive to condition-based maintenance, supporting limited sensor data connectivity and real-time condition monitoring. With AI-assisted troubleshooting, businesses can reduce downtime, improve maintenance efficiency, and lay the groundwork for comprehensive predictive maintenance.
The second is the "Scale Package," designed to help companies comprehensively transform their maintenance strategies. This package integrates Senseye predictive maintenance with full maintenance assistant capabilities, enabling customers to predict failures before they occur, maximizing uptime, and lowering costs through AI-driven insights. This enterprise-grade scalable solution features automated diagnostics, helping businesses optimize operations across multiple sites and driving long-term efficiency and resilience.
The new offerings provide comprehensive coverage of the maintenance lifecycle, from reactive repairs to predictive and preventative strategies, leveraging generative AI insights to improve decision-making and efficiency in industrial settings. As industries continuously seek ways to improve reliability and reduce costs, maintenance operations are shifting from reactive to proactive approaches. Traditional maintenance strategies often lead to costly downtime and other inefficiencies. By integrating AI-driven maintenance solutions, Siemens helps companies optimize asset performance and maximize operational uptime.
Margherita Adraani, CEO of Siemens Digital Industries Customer Services, stated: "The expansion of our Industrial Assistant marks a significant step in transforming maintenance operations. By expanding our predictive maintenance solutions, we help industries seamlessly transition to proactive maintenance strategies, driving efficiency and resilience in increasingly complex industrial environments." With this innovation, Siemens continues to advance its vision of a digitalized industry, providing intelligent and integrated maintenance solutions to ensure long-term operational success.
Key Highlights:
💡 Siemens introduces new generative AI maintenance solutions to help customers transition from reactive to intelligent maintenance.
🔧 New offerings include a "Starter Package" and a "Scale Package," providing basic and comprehensive predictive maintenance capabilities, respectively.
📊 Through AI-driven maintenance strategies, Siemens helps companies optimize asset performance, reduce downtime, and improve efficiency.
