The cloud enables next generation digital twin
High-performance computing is enabling a new class of digital twin
The term ‘digital twin’ was coined sometime around 2002 and defines a concept which traces its origins to NASA, who pioneered the idea as a method to monitor and operate complex systems in remote, hazardous conditions.
Digital twins were originally used to mirror information and were leveraged primarily by research and development teams for modeling and analysis. In their next iteration, manufacturers began using digital twins for product design and simulation, creating virtual three-dimensional (3D) models that could be used to optimize the product lifecycle. In the last few years, a broad range of companies have begun incorporating digital twin technologies into their IoT solutions, allowing them to generate real-time feedback between physical objects and their digital counterparts. This latest wave of innovation has led to the rise of product-as-a-service business models via solutions such as remote monitoring and predictive maintenance.
Many companies have already derived immense value from digital twins. When implemented utilizing high-performance computing technologies (HPC) such as cloud-based workstations, cloud rendering, simulation and analysis, and deep learning/artificial intelligence (AI), digital twins are able to significantly accelerate the product development and manufacturing processes. Yet, these traditional digital twins are limited in that they cannot work on physical and virtual models simultaneously. The latest developments in HPC, IoT, AI and mixed reality tools such as HoloLens are addressing this barrier and ushering in a new class of digital twin: Process Digital Twin. This new class of digital twin requires the powerful, agile computing capabilities provided by HPC to facilitate global mobility and collaboration. Process Digital Twins enable manufacturers to generate digital representations of their end-to-end business processes, and offer new ways of collaborating simultaneously in the virtual and physical world.
The path to a new class of digital twin
Two critical gaps have created a strong need for Process Digital Twins in manufacturing today. First, while traditional manufacturers are operating in both physical and virtual models of their environments, they can’t be in each of these spaces simultaneously, creating a fundamental lack of end-to-end visibility. Second, though manufacturers are utilizing industrial robots capable of basic reasoning, these complex machines still require the ability to collaborate machine-to-machine (M2M) to make many decisions on their own, enhancing efficiency and freeing up human capital. Extending beyond the M2M challenge is the fact that machine-to-machine-to-people (M2M2P) collaboration remains elusive. Manufacturers need a means of collaborating across their physical and virtual ecosystems in real-time, modeling changes to complex systems that involve software, hardware, and digital representations of multiple machines.
The solution to closing these gaps lies in the next wave of digital transformation. Process Digital Twin leverages HPC, IoT, AI, and mixed reality technologies to optimize not only equipment, but the entire manufacturing process. Using Process Digital Twins, manufacturers can take advantage of advanced and immersive visualizations, including holographic representations that bring processes or entire production lines into the real world. HPC solutions further enhance Process Digital Twins, enabling engineers to interact with these in-process models in virtual and physical space simultaneously, and simulate potential changes before they are executed or train new equipment. This technology goes well beyond simply projecting objects into physical space, and instead provides an entirely new functionality that eliminates technology constraints to facilitate real-time collaboration across the value chain.
The benefits of Process Digital Twin for your business
Taking advantage of the new class of digital twin can provide powerful benefits across your manufacturing business.
With the connection of the entire production environment, manufacturing engineers can re-engineer processes for any plant, from anywhere. Simultaneously, the equipment’s design engineers can leverage HPC technologies to interact with machines in-operation. This means manufacturers can have end-to-end engineering integration across their entire supply chain, on a global scale.
The Process Digital Twin also enables intelligent, machine-level decision-making at a factory level, driving employee and plant productivity. When implemented throughout the production line with HPC, Process Digital Twins can leverage advanced analytics and cognitive capabilities, utilizing cloud workstations accessible from anywhere, on any device. With Process Digital Twin and HPC rendering and simulation tools, engineers can visualize potential workflow optimizations across the value chain and more accurately assess operational impact. When training these complex networks of equipment and systems, Process Digital Twins can integrate with HPC deep learning and AI frameworks to provide scalable solutions that support rapid training workloads and minimize production downtime.
Get started now
Microsoft offers the most complete set of capabilities and experience required to execute your digital twin strategies, providing the most comprehensive portfolio of products and services, an open and accessible platform, industry-leading security, and scalable cloud solutions. If you are looking to take advantage of the benefits Process Digital Twins provide, Microsoft offers powerful end-to-end solutions, such as Microsoft Azure Big Compute portfolio, Microsoft HoloLens, Microsoft Azure IoT, and Azure Cortana Intelligence, that enable you to quickly deploy Process Digital Twin and start realizing the powerful results digital twin can deliver.
Are you ready to unlock the full value of Big Compute and Process Digital Twin for your business? Learn more about our Microsoft Azure Big Compute and Digital Twin solution portfolio today.
