ABB, Corys Join Forces To Advance Digital Twin Technology

Dec. 4, 2020
ABB and Corys sign MoU for digital collaboration.

ABB and Corys, a French simulation company, sign a memorandum of understanding (MoU) for digital collaboration. The two companies enter a strategic agreement to advance digital twin modeling and simulation technology across energy and process industries. The agreement reflects a strategic collaboration between ABB and Corys, with both companies committed to delivering advanced digital twin technology to help drive down capital and operational costs and reduce risks for customers.

Leveraging ABB Ability 800xA Simulator, ABB delivers complete digital replicas of a plant’s control system. Combined with Corys’ dynamic high-fidelity Indiss Plus process modeling simulator, customers may benefit from a complete digital twin offering that supports training and allows operators to validate and test control strategies and production processes, as well as manage changes during the lifecycle of operations, according to the companies. The collective digital product is expected to reduce capital expenditure in greenfield projects by improving quality of the control applications, reducing number of late changes, training the operators and by reducing the number of commissioning and start up hours. 

“In today’s economy, our oil, gas and chemical customers are exploring all ways to maximize return on investment in operations,” says Colin Ward, chemicals and refining svp for ABB Energy Industries. “Digital twin modeling and simulation creates more confidence in executing projects – reducing cost, schedule and risk – and helps operators identify and understand improvement opportunities across an asset’s complete lifecycle.”  

Also applicable for use in brownfield sites, operators can utilize the ABB Corys digital twin package to build intelligent models and run scenarios to increase performance of plant operations. This includes improving plant efficiency and availability, as well as reviewing and managing equipment and assets across the plant, enabling maintenance teams to build an effective condition-based maintenance program. 

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