SPX FLOW is excited to collaborate with Siemens to highlight cutting-edge digital twin technology at the MxD (Manufacturing x Digital) center in Chicago. A premier hub for innovation in manufacturing, MxD is driving advances across industries such as food and beverage, chemicals, and batteries.
At MxD, SPX FLOW and Siemens are demonstrating the transformative potential of digital twin technology. This technology is further enhanced by industrial 5G connectivity and modular production using software-defined Module Type Package (MTP) concepts, showcased through an automated mixing tank with an associated digital twin.
This collaboration combines SPX FLOW’s fluid processing solutions (including mixers, pumps, and valves) and expertise with Siemens’ IoT connectivity solutions and Computational Fluid Dynamics (CFD) simulation capabilities to create a digital twin (a precise virtual replica of the physical systems) of an autonomous mixing tank concept. This enables users to design, test, and optimize fluid systems virtually, mitigate risks, improve efficiency, and accelerate innovation.
SPX FLOW helps enable Siemens to demonstrate the transformative potential of its virtual simulation technologies, whereby creating a digital twin of a flexible, autonomous production process, manufacturers can optimize production, validate throughput, and boost efficiency and flexibility when compared to traditional fixed production lines. This innovative approach also allows for continuous mixing of materials or ingredients while the Autonomous Mobile Robot (AMR) navigates the plant, ensuring optimal production capacity and quality.
Computational Fluid Dynamics (CFD) modeling and IoT conditional monitoring support SPX FLOW’s product development by: Accelerating Innovation: Reducing modeling time while improving precision; Improving Efficiency: Refining designs with enhanced flow analysis; and Integrating Seamlessly: Aligning digital twins with real-world applications.
Smart Products: Leveraging IoT conditional monitoring to optimize equipment performance and enable predictive maintenance.
