The effort links digital twin, asset, service and factory data to connect design intent with real-world equipment performance.
Siemens and IFS have announced a partnership to help manufacturers connect engineering data with operational data across the product lifecycle using industrial AI.
The collaboration combines Siemens’ work in industrial AI, engineering, automation and manufacturing execution with IFS’ capabilities in industrial AI, enterprise asset management and field service. The partnership is intended to address gaps between factory design and day-to-day operations, including unplanned downtime, disconnected maintenance schedules, siloed production data and supply chain disruption.
Focus on manufacturing operations
Manufacturers are under pressure to increase output from existing assets, manage margins, extend equipment life and respond more quickly to changing conditions. Many still use separate systems for production, maintenance planning and supply chain management, which can limit coordination between engineering, operations and service.
Role of industrial AI
Industrial AI is a central part of the partnership. The goal is to connect design data with operational performance data so manufacturers can compare engineering plans with actual operating conditions and use that information in future design and production decisions.
Siemens’ digital twin technology provides engineering, simulation and manufacturing context, while IFS provides service history, asset performance and lifecycle data. Together, these inputs are intended to support a digital twin that links design intent with field performance across design, simulation, service records and factory execution.
Industrial AI systems for manufacturing must address requirements such as accuracy, reliability, regulatory compliance and adaptability because decisions can affect safety, compliance and physical assets.
For more information, visit siemens.com.
