What do you think are some of the more exciting advances in modeling for enterprises?īanerjee: Artificial intelligence and machine learning (AI/ML) have been around for more than 30 years, and the field has advanced from concepts of rule-based expert systems to machine learning using supervised learning and unsupervised learning to deep learning. VentureBeat: AI and machine learning models are getting much press these days, but I imagine there are equally essential breakthroughs in other types of models and the trade-offs between them. Specifically, through physics, simulation provides virtual sensors, enables “what-if” analysis, and improves prediction accuracy. With digital twins, simulation plays a key role during the product operation, unlocking key benefits for predictive and prescriptive maintenance. That complexity could include support for 5G or increased concerns about electromagnetic interference. The connectivity needed for products to support digital twins adds significant complexity. VentureBeat: In what fundamental ways do you see modeling and simulation complementing digital twins and vice versa?īanerjee: Simulation is used traditionally to design and validate products - reducing physical prototyping and cost, yielding faster time to market, and helping design optimal products. Today, we have demonstrated that the accuracy of the digital twins can be greatly enhanced by complementing the data analytics with physics-based simulation. In the past, customers have built digital twins using data analytics from data gathered from sensors using an IOT platform alone. They also scale with a number of monitored assets, equipment, and facilities. That could include services, predictive maintenance, yield, and, as well as budgets. Also, they typically impact a variety of business objectives. So, digital twins represent a distinct new application of these technology components in the context of product operations and are used in various phases - such as design, manufacturing, and operations - and across various industries - like aerospace, automotive, manufacturing, buildings and infrastructure, and energy. While digital twins as a concept are not new, the technology necessary to enable digital twins (such as IoT, data, and cloud computing) has only recently become available. Digital twins enable tracking of past behavior of the asset, provide deeper insights into the present, and, most importantly, they help predict and influence future behavior. Sensors mounted on the entity gather and relay data to a simulated model (the digital twin) to mirror the real-world experience of that product. VentureBeat: How would you define a digital twin, and why do you think people are starting to talk about them more as a segment?īanerjee: Think of a digital twin as a connected, virtual replica of an in-service physical entity, such as an asset, a plant, or a process.
#Ansys simulation software#
Now they can build the entire virtual prototype through software simulation and create an optimal design by exploring thousands of designs. In the past, engineers would build multiple prototypes in hardware, resulting in long times and cost. As a result, engineers no longer need to build and test several different configurations. Through digital modeling, engineers can vary the pressure and temperature of the valve to gauge its strength and discover failure points more quickly. A more specific example would be a valve in an aircraft engine that regulates pressure in a pipe, or a duct that needs to be modeled in many ways. The best way to understand the advantages of simulation is by looking at an example: One blue chip customer is leveraging simulation technology to kickstart digital transformation initiatives that will benefit customers by lowering development costs, cutting down the time it takes to bring products to market. Companies use simulation software to design their products in the digital domain - on the computer - without the need for expensive and time-consuming physical prototyping. Prith Banerjee: Simulation and modeling help companies around the world develop the products that consumers rely on every day - from mobile devices to cars to airplanes and frankly everything in between. VentureBeat: What do executive managers need to know about modeling and simulation today? They both allow us to peer deeper into things, but how do these underlying technologies serve in various contexts to speed up the ability to explore different designs, trade-offs, and business hypotheses? This interview has been edited for clarity and brevity.