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Join us to learn how to overcome challenges through the Performance Engineering Process
Machine builders around the world are looking at how digital transformation can help them innovate in response to better performance, the adoption of new technology, and global competition. This is driving demand for more intelligent, flexible, configurable, and automated industrial machinery equipment. Industrial machinery companies need to develop new design practices to keep pace with the growing complexity of the machines. Industrial machinery companies will need to develop new design practices to keep pace with the growing complexity of these machines, and to ensure these variations are safe, cost-effective, and perform as designed. Each variation needs to be validated before it’s delivered to a customer.
In this seminar series, our experts will take you through all the steps of the performance engineering process. Customer examples will be presented by our experts, and customers will present as well how they managed to implement IPE (Intelligent Performance Engineering) and what benefit that brought to them.
Next to this, we will present in detail how the engineering digital twin can be connected to factory automation, allowing to perform virtual commissioning and closed-loop validation. Finally, we will introduce to you the application of new technologies like eXecutable Digital twin, as well as applying AI on machine data, and how this relates to the digital twin.
Last but not least, we will also give a practical example of how to combine machine data, digital twin, and AI to optimize the operation of a fully integrated production plant.
In this session, we will explain what Intelligent Performance Engineering (IPE) all is about. In a nutshell, it is a connected digital thread that helps automate the processes of sharing information between design teams, analysts, production test teams, and service engineers. This allows teams to evaluate the capabilities and limitations of product variations in the most efficient way. An intelligent performance engineering solution focuses on improvements in simulation and test, design, and connectivity for machine builders.
Closing the loop between the different domains is essential for IPE: connecting requirements with the digital twin for performance engineering, connecting the digital twin with the physical twins (machines) in operation (IoT) for performance optimization, to even embed the digital twin as a real-time executable to make the machines smarter.
Motor, pump, and compressor manufacturers face more competition than ever. New suppliers are coming into the market from low-cost countries, putting pressure on prices and your overall bottom line. To stay competitive, you need to innovate and differentiate your products from the commodities and develop new capabilities that your customers value. Achieving innovation in a fast-moving market for complex products is a challenge you need to overcome.
Simulation is a key to unlocking innovation and doing it faster than your competition can. Simulation lets you quickly test new design ideas before ever cutting a physical prototype. This means you can rapidly evaluate many new design variants to find the right design for your application. Physical testing still plays a role to meet regulations, but it is also used to validate and fine-tune your simulation models.
In this Industrial Machinery series of presentations, this subsegment will consider the Production Machine. It will start with an executive presentation that describes the trends for high-end production machines, the implications for machine manufacturers, and presents the Siemens PLM Software’s answer to these challenges. In considering these challenges it will expand on the need for rapid innovation of complex systems and technologies.
This webinar introduces key concepts and delivers examples demonstrating benefits and how Siemens Digital Industries Software can boost productivity through efficient and automated workflows in model building and executing projects in tighter time frames. The session will include our Siemens Automation division using these tools for the production machine.
HVAC systems played a critical role in reducing the spread of airborne transmitted diseases in closed spaces. Achieving an improved understanding of the factors affecting an HVAC system such as in aircraft, Automotive transportation, or buildings is vital to designing cost-effective and energy-efficient systems capable of providing improved comfort and supply of clean air. Combining 1D and 3D techniques allows the simulation to be deployed throughout the product development phase, minimizing cost while maximizing performance and reliability. In the automotive, coupling a 1D Electric vehicle thermal management system model with a 3D Passenger Cabin model using a seamless Co-Simulation approach allows high fidelity thermal system prediction for the vehicle and components against a real Drive Cycle. In contrast, the traditional silo design approach takes considerably longer in the design phase and generates a low-fidelity representation of the actual system.
Using AGV or AMR is a solution for repeated logistics tasks allowing your employees to focus on added value tasks. This webinar introduces key concepts and delivers examples demonstrating benefits and how Siemens Digital Industries Software can boost productivity through efficient and automated workflows in model building and executing projects in tighter time frames.
In this session we take the digital twin to the factory floor. How do we connect the Digital Twin to automation? How can you commission a machine without impacting or stopping the production line? We will see how virtual commissioning is done by connecting the digital twin with automation code, to simulate transient behavior of multi-domain systems including hydraulics, pneumatics, electronics, thermal & mechanics of a machine and coupled with the automation code (SIL) and real PLC (HIL).
Sacmi will come to present their project on how virtual commissioning was successfully applied.
Next to this, we will also close the loop between the real machines and the digital twin. Model-Based System Testing allows to combine real machine data with information from the digital twin. This provides many advantages, like for virtual sensing. Finally, we will show how a complete production plant can be optimized by using a Factory Digital Twin Model with a low code developed application framework. Throughout the session we will share real project examples, inspiring you how Siemens technology can also benefit for you.
Within this session, we introduce new technologies that when used in combination with data acquired via both real measurements or Multiphysics simulation bring further efficiency and accuracy to predictive capabilities. The new technologies that will be demonstrated with real use cases will introduce the use of AI, xDT both for predictive maintenance and real-time operations.