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Siemens to Acquire Process Systems Enterprise

10/03/2019 by Lighting Controls Association Leave a Comment

Process Systems Enterprise (PSE), a supplier of Advanced Process Modelling (APM) software and services, recently announced that it plans to be acquired by Siemens AG in a transaction scheduled to close in Q4 2019. The 160-person PSE operation will be integrated into the Process Automation Business Unit of Siemens Digital Industries. The current PSE management team will remain in place.

PSE’s advanced process models are used within digital R&D, design and operations in the process industries to help make fast, safe and more efficient decisions through rapid and effective exploration of the decision space. The technology is widely used in the chemicals, petrochemicals, pharmaceuticals and food industries to accelerate innovation, improve process design and operation, streamline R&D and manage technology risk.

PSE’s model-based solutions span the entire process lifecycle via a unified and integrated set of tools. These strongly complement the Siemens portfolio in the process industry sector, and will further strengthen Siemens’ position as a leading provider of digitalization technologies.

Eckard Eberle, CEO of the Siemens Process Automation Business Unit, said, “The combination of high-fidelity predictive models and process data plays an increasingly important role in the digitalization of design and operations in the process industry. It is important to take the process knowledge that is already available in product and process development and to map it in predictive models which can then be used to add value in the digitalization environment in every step of the lifecycle. With PSE, we will be even better equipped to meet the specific requirements of our process industry customers.”

Siemens and PSE collaborated closely for two years before entering a strategic partnership in June 2018, developing new model-based solutions for diverse high-value applications including detailed unit operation design, plant monitoring and performance forecasting, soft sensing, nonlinear model-predictive control and real-time optimizsation.

Both companies have agreed not to comment on the financial details of the transaction.

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