A digital twin is a virtual representation of a physical object, process, or machine that enables companies to understand and optimize how that machine operates. A digital twin is a computer model of a real-world system that captures all the variables in that system -- including how materials interact with other materials, machines, or people in the factory -- along with algorithms that help predict how the system might behave under various conditions.
Dr. Norbert Gaus is one of the world's leading experts on digital twins and is EVP for Research and Development for Digitalization and Automation at Siemens Corporate Technology.
In this video, Dr. Norbert Gaus discusses the challenges of bringing digital twin automation to life. He offers sage advice to business leaders considering digital twin technology for their own companies.
In this conversation you will learn about topics that include:
-- What is a digital twin?
-- How a digital twin improves manufacturing
-- Machine learning models used to create a digital twin
-- Ensuring the digital twin accurately represents the physical object
-- Digital twins across the product lifecycle
-- Customer applications for the digital twin
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Dr. Norbert Gaus of Siemens Corporate Technology defines the concept of a digital twin as a "digital representation of a physical product in all its aspects." Digital twin technology can speed time to market, reduce costs, and allow a company to create a much broader portfolio of products.
Dr. Gaus explains how Siemens uses AI-based simulations to take the place of creating multiple physical prototypes to achieve new designs. He describes how Siemens combines a digitized version of the physical product with artificial intelligence throughout the product life cycle. That product lifecycle includes design, components, manufacturing, operations, and service and maintenance.