Frustration and annoyance ensue when customers purchase a product touted as being bleeding-edge but, once they put the product to use, realize the functionality and quality leave a great deal to be desired. The resulting consumer disappointment can cause significant damage to capital goods. To avoid this damage, manufacturers are increasingly using the analytics-supported, virtual prototype development of digital twins to get all their proverbial ducks in a row.
A “digital twin is a virtual model of a process, product or service. This pairing of the virtual and physical worlds allows analysis of data and monitoring of systems to head off problems before they even occur, prevent downtime, develop new opportunities and even plan for the future by using simulations.” i
The idea of a digital twin has been around since the early 2000s, but it’s only become cost-effective to implement in recent years, thanks to the Internet of Things (IoT). A recent Gartner survey reveals that digital twins are entering mainstream use.ii Gartner predicts that at most, “by 2022, over two-thirds of companies that have implemented IoT will have deployed at least one digital twin in production.”iii
Only 13 percent of Gartner’s respondents claim to use digital twins currently, while 62 percent are either in the process of establishing twin technology or plan to do so over the next 12 months.iv This swift growth in adoption is because digital twins are delivering business value and are now part of enterprise IoT and digital strategies.
Saving Time and Money with Digital Twin Technology
As Hermann Wedlich wrote in his blog Running Real-Time Digital Twins on FlexPod with NetApp and INNEO, there are many advantages to employing analytics in data-based development processes.
Wedlich highlights that much time and money can be saved in the development process when multiple simulation technologies work together to reduce the required number of physical prototypes. Virtual simulation technologies accurately test all aspects of a product already in its virtual or digital form. By using applied AI, companies can check the most reliable and cost-optimized variants before developing physical prototypes.
FlexPod Cloud-Connected Converged Infrastructure is Ideal for Digital Twins
To create effective simulations in real-time requires highly flexible, scalable IT architectures that are connected to cloud resources.
The ideal choice for running digital twins is a combination of FlexPod Cloud-Connected Converged Infrastructure, 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 Solutions is a NetApp partner that fully understands the application of FlexPod technologies and can use them to successfully implement digital twin projects for customers. Because of INNEO’s service and product portfolio, the company can draw on many years of experience. They also offer a separate test center for evaluation.
With expertise in the areas of product development and manufacturing, visualization, information technology, and process optimization, INNEO Solutions are digital twin experts. For more information, visit https://www.inneo.com.