Imagine the following scenario: You purchase a product that has been advertised as super-innovative, but once you start using it, you notice that the quality and functionality do not live up to expectations. Does this sound familiar? A situation like this can be annoying and frustrating in the consumer business, but it can cause great damage to capital goods. To avoid this damage, manufacturers use analytics-supported, virtual prototype development of digital twins.
Advantages of Analytics in Many Data-Based Development Processes
Usually, multiple simulation technologies work together to reduce the required number of physical prototypes. This approach saves time and money in the development process. These virtual simulation technologies test all aspects of a product already in its virtual or digital form. By using applied artificial intelligence (AI), you can test the most reliable and cost-optimized variants before developing the real physical prototypes. In this way, you can create many simulations, for example, of strength, vibration, and temperature characteristics.
Another striking example can be found in the telecommunications sector: Electromagnetic radiation and ideal placement of antennas are calculated for the desired radiation range and battery capacity. The calculation takes place almost in real time. Therefore, the long waiting times that were previously associated with important simulations are now a thing of the past. Planning during expansion is thus more reliable, especially for blind spots and hot spots in mobile network coverage.
Because most product and service costs are determined at a very early stage, the early use of simulations helps to reduce later expenses and greatly reduces development time.
FlexPod: The Ideal Platform for Digital Twins
High-end simulations in real time require highly flexible, scalable IT architectures that are connected to cloud resources. The best simulation software today can use parallel work cycles of GPUs to achieve results faster. The ideal choice is a combination of FlexPod®, the converged reference architecture from NetApp and Cisco; the corresponding NVIDIA analytic GPUs in Cisco UCS Servers; and the ultrafast, cloud-connected flash systems from NetApp. Because you can use FlexPod as a multiplatform system, you can meaningfully supplement various applications such as AI and machine learning, containers, SAP, databases, and hybrid scenarios with NetApp® Cloud Volumes Service or cloud data services.
INNEO: A NetApp Partner for the Demanding Implementation of Digital Twin Projects
INNEO Solutions GmbH, one of NetApp’s partners, fully understands the application of these technologies and can use FlexPod to successfully implement them for customers. Because of INNEO’s service and product portfolio, the company can draw on many years of experience. A separate test center is also available for evaluation.