Innovation and collaborative, synchronized program management for new programs
Aerospace & Defense
Innovation and collaborative, synchronized program management for new programs
Explore IndustryAutomotive & Transportation
Integration of mechanical, software and electronic systems technologies for vehicle systems
Explore IndustryConsumer Products & Retail
Product innovation through effective management of integrated formulations, packaging and manufacturing processes
Explore IndustryElectronics & Semiconductors
New product development leverages data to improve quality and profitability and reduce time-to-market and costs
Explore IndustryEnergy & Utilities
Supply chain collaboration in design, construction, maintenance and retirement of mission-critical assets
Explore IndustryHeavy Equipment
Construction, mining, and agricultural heavy equipment manufacturers striving for superior performance
Explore IndustryIndustrial Machinery
Integration of manufacturing process planning with design and engineering for today’s machine complexity
Explore IndustryInsurance & Financial
Visibility, compliance and accountability for insurance and financial industries
Explore IndustryMarine
Shipbuilding innovation to sustainably reduce the cost of developing future fleets
Explore IndustryMedia & Telecommunications
Siemens PLM Software, a leader in media and telecommunications software, delivers digital solutions for cutting-edge technology supporting complex products in a rapidly changing market.
Explore IndustryMedical Devices & Pharmaceuticals
“Personalized product innovation” through digitalization to meet market demands and reduce costs
Explore IndustrySmall & Medium Business
Remove barriers and grow while maintaining your bottom line. We’re democratizing the most robust digital twins for your small and medium businesses.
Explore IndustrySeminar Series for Industrial Machinery: The Performance Engineering Process
Seminar Series for Industrial Machinery: The Performance Engineering Process
Learn more about the new technologies to complement test and Multiphysics simulation!
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.
An xDT is a smart, connected virtual representation of a physical asset, including its behaviors, that senses what is happening to it, applies a simulation or algorithm, and then optimizes and updates itself. It processes sensor information (at the edge or in the cloud) to recognize its environment and then adjusts to those conditions. We will show the value of the xDT via a practical demonstration case, and by a customer presentation on an industrial project.
The next step is to close the loop between the digital twin and the real assets, by gathering data from the real systems to continuously update and improve the fidelity of the digital twin. We do this by leveraging the industrial internet of things, artificial intelligence, and machine learning to automatically fine-tune the digital twin.
Rapidly reduce the risk and increase the product safety, reliability, availability, maintainability using a model-based approach during concept definition for the initial design. Use qualitative functional simulation to support analysis that will identify and mitigate potential engineering risks based on technical, operational, and economic consequences.
Finally, we will present RAMS: Model-based Reliability, Availability, Maintainability, and Safety.
RAMS allows you to build a Digital Risk Twin of your system to identify the expected behavior and the impact of potential failures and risks associated with a design configuration in an objective, repeatable, and traceable process. Using qualitative simulation, you will be able to easily analyze and understand the potential impact of design decisions on product safety, reliability (technical risk), and operational availability before it becomes impractical to change the configuration of the product. This allows you to design for reliability and link functional failures for each maintainable item and identify the most cost-effective maintenance approach tailored to the asset usage.
Alex Vermeulen
Portfolio Development Simcenter TEST Solutions, Siemens Digital Industries Software
Leoluca Scurria
Product Manager, Siemens Digital Industries Software
Koen Peeters
R&D Engineer, LAB Motion
Wim Hendricx
Business Development Engineering, Siemens Digital Industries Software
Stefan Dutré
Senior Product Manager Model Based RAMS Solution, Siemens Digital Industries Software
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Learn more about the new technologies to complement test and Multiphysics simulation!
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.
An xDT is a smart, connected virtual representation of a physical asset, including its behaviors, that senses what is happening to it, applies a simulation or algorithm, and then optimizes and updates itself. It processes sensor information (at the edge or in the cloud) to recognize its environment and then adjusts to those conditions. We will show the value of the xDT via a practical demonstration case, and by a customer presentation on an industrial project.
The next step is to close the loop between the digital twin and the real assets, by gathering data from the real systems to continuously update and improve the fidelity of the digital twin. We do this by leveraging the industrial internet of things, artificial intelligence, and machine learning to automatically fine-tune the digital twin.
Rapidly reduce the risk and increase the product safety, reliability, availability, maintainability using a model-based approach during concept definition for the initial design. Use qualitative functional simulation to support analysis that will identify and mitigate potential engineering risks based on technical, operational, and economic consequences.
Finally, we will present RAMS: Model-based Reliability, Availability, Maintainability, and Safety.
RAMS allows you to build a Digital Risk Twin of your system to identify the expected behavior and the impact of potential failures and risks associated with a design configuration in an objective, repeatable, and traceable process. Using qualitative simulation, you will be able to easily analyze and understand the potential impact of design decisions on product safety, reliability (technical risk), and operational availability before it becomes impractical to change the configuration of the product. This allows you to design for reliability and link functional failures for each maintainable item and identify the most cost-effective maintenance approach tailored to the asset usage.
Alex Vermeulen
Portfolio Development Simcenter TEST Solutions, Siemens Digital Industries Software
Leoluca Scurria
Product Manager, Siemens Digital Industries Software
Koen Peeters
R&D Engineer, LAB Motion
Wim Hendricx
Business Development Engineering, Siemens Digital Industries Software
Stefan Dutré
Senior Product Manager Model Based RAMS Solution, Siemens Digital Industries Software