PSE is now A Siemens Business within the Process Automation Business Unit of the Siemens Digital Industries division.
PSE’s model-based solutions span the entire process lifecycle via a unified and integrated set of tools that are widely acknowledged to be leaders in their respective fields. Our technology is 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.
What better fit than with Siemens, leaders in industrial digitalization? PSE technology strongly complements the Siemens process industries portfolio, and strengthens Siemens’ position as a leading provider of digitalization technologies to the chemicals, petrochemicals, pharmaceuticals and food sectors.
As Eckard Eberle, CEO of the Siemens Digital Industries Process Automation BU, says: “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.”
He adds “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.”
Costas Pantelides, Managing Director of PSE, says: “We are delighted to become part of the Siemens organisation. Our technology and know-how are highly complementary to Siemens’ products, and our combined portfolio will build on Siemens’ already strong position in digitalization to deliver unprecedented benefits to 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 optimization.