Siemens, IFS Align Technology To Improve Operational Performance

Determined to improve operational performance across manufacturing and industrial sectors, including energy, Siemens and IFS have formed a  partnership to integrate industrial AI, digital twin technology and asset lifecycle management.

The collaboration combines Siemens’ engineering, automation, manufacturing execution and digital twin technologies with IFS’ enterprise asset management and field service platforms to better connect engineering, production and operational data throughout the asset lifecycle.

The companies said the partnership is intended to help operators improve production efficiency, reduce unplanned downtime and optimise maintenance by linking engineering design with real-time operational performance.

A key objective is the development of a closed-loop digital twin that combines engineering, simulation and manufacturing data with operational and asset performance information. The companies said the integrated approach is designed to provide more accurate, context-aware AI applications for industrial environments, where reliability, safety and regulatory compliance are critical.

“Industrial AI only delivers value when it is grounded in both engineering intent and real-world performance,” said Tony Hemmelgarn, president and CEO of Siemens Digital Industries Software. “Together with IFS, we are bringing these domains together by connecting design, manufacturing and asset lifecycle data.”

The partnership also aims to improve production planning, maintenance scheduling and asset management by reducing information silos between engineering, operations and service organizations.

CEO of IFS, Mark Moffat, said combining the companies’ industrial AI capabilities will help manufacturers better align factory operations with engineering objectives while delivering measurable improvements in operational performance.

The companies plan to jointly develop integrated Industrial AI capabilities that enable operators to optimize production assets, accelerate decision-making and improve equipment performance throughout the product lifecycle.