This webinar goes into specific detail about how to address certification challenges, including: Structural loads and performance, Flutter, Landing and take-off, Structural occupant protection, High frequency electromagnetic simulation, Noise and vibration, and Electric drive.
Digital convergence is enabling industries to make the most of the data they collect to inform decisions at every stage of the product life cycle, connect information technology (IT) with operational technology (OT), and capitalize on new business models. Where does simulation engineering fit in the broader digital convergence discussion?
Welcome to the future of engineering. Let us show you how Siemens Simcenter executable digital twins (xDTs) do what we thought impossible. This short video shows smart virtual sensors, a type of xDT, created with the help of the Simcenter portfolio. These sensors let you create models that can update themselves as you use them (often in real-time) to predict previously not measurable quantities.
How Do Digital Twins and Monitoring Systems Work Together? In the data center industry, it’s a given that having the right data is essential for making sound decisions throughout design and operations. But agreeing on how best to get that data is a different story.
Creating a Digital Twin or virtual copy of the data center is the surest way to navigate the changes your data center faces. This blog will walk you through where and how a Digital Twin fits into the constantly changing landscape that is the data center industry.
The Digital Twin provides a collaborative framework and the necessary design tools to drive informed, real-time decisions regarding thermal risk and capacity utilization. 6SigmaDCX Release 15 streamlines data center design
and management with new big data features, faster model creation and automation across the board.
Deploying any change within your data center can seem daunting. But with a data center Digital Twin you can undertake virtual testing of those changes, using physics-based simulation, ensuring nothing goes into a live environment that hasn’t already been assessed for performance.
This paper provides an aerospace industry perspective on the Digital Twin and the significant benefits and rationale to accelerate embracing the fourth industrial revolution referred to as digital transformation.
A True Digital Twin replicates the proposed physical space, and includes all mechanical, robotic, sensor, vision, AI, and computer systems, while simultaneously incorporating real human action and interaction. Humans experience the system in virtual reality (VR), with concurrent motion capture driving their avatars in real time. The avatars interact with virtual objects and their physical “stand ins”, which are also motion-tracked. All aspects of the system, including hardware, software, AI training data/models, and human interaction, are developed, tested and optimized virtually using a proprietary software platform.
If you capture a product’s configuration correctly, you have context―which enables you to create traceability. In essence you have created the Digital Twin time machine. The context of the Digital Twin, supported by digital thread data, and analysis tools like simulation or analytics, allows you to move backwards and forwards for any product or system of products.
Companies must ensure a cost effective and reliable product is introduced to the market in a timely manner while also addressing the challenges relating to in-service product updates and on-going maintenance. The Digital Twin in the context of virtual engineering and digital transformation is becoming a critical player in such highly innovative and competitive environment.
Akselos is a new simulation technology that can evaluate structural behavior 1000x faster than traditional techniques. Akselos is capable of producing high-fidelity, physics-based models of large complex assets which may be connected to sensor data to regularly update the simulation model and provide the required assessments in a timely manner.
A digital twin is a dynamic digital model of a product, process, or person, which analyzes existing business system data combined with real-world data. However, the value expands past the single digital model of an asset and is increasingly an underpinning element of an organization's digital transformation initiatives.
The digital twin continues to proliferate and is a concept often associated with Siemens, and given our investment in software, additive manufacturing and the digital industries, this is good news indeed. But sometimes these terms can be too ethereal and my interest is piqued when I see this concept in action.
"Although analytical twins have existed for a while, this evolution of simulation-based models that lead to the creation of digital twins is really transforming manufacturing, as product designs become more customized, unique and intricate by nature."
“Collaborating with ANSYS to create an advanced IoT digital twins framework provides our customers with an unprecedented understanding of their deployed assets’ performance by leveraging physics and simulation-based analytics.” — Sam George, corporate vice president of Azure IoT, Microsoft
Let's discuss the importance of keeping your digital twins in sync with real products.
Models so accurate they’re a digital twin of the product you’re creating can help you throughout the design and development process. 1D models can help you determine the best architecture for your multi-physics system, 3D models can help you design into the details, and testing can help you improve modelling realism. Combining all the three technologies gives you the highest possible accuracy while making design decisions. But in today’s world the design job isn’t done when you ship. You have to be able to take feedback, track how products are used – with detailed data coming from the increasing numbers of sensors in modern devices – and then use that to support, maintain and improve the products you have out in the market, as well as incorporating all that information into your next generation. That means keeping your digital twins in sync with the real products, even once they’re in customers’ hands.
How can food and beverage companies use the digital twin and industrial IoT to dramatically improve production performance? This eBook shares the value of the digital twin and IIoT for companies that produce food and consumer packaged goods. Then, it shares some practical examples and advice to get started down the path to streamline R&D and new product development, optimize production plans, increase performance, gain production intelligence, improve quality, and compete as an integrated supply chain.
In a commissioned study of IoT decision makers conducted by Forrester Consulting on behalf of Siemens in May 2019, respondents of varied IoT maturity levels recognized that digital twins can continuously improve their product offerings and improve product quality.
Karen Willcox is a leading aerospace researcher and expert in simulation-based engineering who specializes in the aerospace industry. Her work on simplified simulation models has made it possible to accelerate the development and design of complex systems.
Innovation and new technology applications are being established as part of core business management tools and are starting to appear in the area of managing M&A. When M&A is announced, organisations are committing to buy an asset or asset groups – at which point a due diligence effort is usually conducted to establish the actual state of the asset.
Digital Twins have shown significant promise for the management of assets, and could also be transformational in the M&A process to qualify the quality of the assets.
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