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A Digital Twin is a digital replica of any process, system, or physical asset that will enhance applications serving business objectives.

Engineers and data scientists save valuable time using process Digital Twins. Gone are the days of manual data pulls and complex manual analyses. A Digital Twin automates data pulling, cleaning, structuring, and transforming.

This puts the most important information directly into the hands of your skilled engineers. Your teams can focus on solving problems that move your company forward instead of manual data manipulation. 

Digital Twins are especially useful in manufacturing.

That’s because a Digital Twin in manufacturing can be built for assets, specific production lines, by end product, or for any other “real world” scenario within a production process.

The basic concept of the Digital Twin is not new, but due to the advancement and evolution of enabling technologies, we’re seeing renewed focus on the implementation of the Digital Twin and associated benefits that could be gained.

Using Digital Twins that represent the product and production systems, manufacturers can reduce the time and cost associated with assembling, installing, and validating factory production systems. Additionally, implementing digital twins for asset management typically provides quantifiable benefits for maintaining equipment in the field.

In manufacturing, the Digital Twin is a virtual representation of the as-designed, as-built, and as-maintained physical product; augmented by real-time process data and analytics based on accurate configurations of the physical product, production systems, or equipment.

This is, in essence, the  operational context of the digital twin needed to support performance optimization. While virtual models are conceptual in nature, the real-time and operational data is a digital representation of real physical events. CAD models represent the virtual fit, form, and function of the Digital Twin’s physical  counterpart. 

However, real-time operational and asset data are required to execute analytics applications that define the state and behavior of the performance-based Digital Twin and allow optimization and process improvement.

Want to learn more? Tonex offers Digital Twin in Manufacturing, a 2-day course where participants learn the principles of Digital Twins and how it relates to integration of Digital Engineering, modeling and simulations, AI/ML, 3D and integration for service and product-related data and systems.

Learn how Digital Twins can help in the manufacturing sector. Also learn how a Digital Twin creates the virtual model of physical entity in digital way, promotes the interaction and integration of physical world and information world, and builds a reliable bridge for industrial information integration.

For more information, questions, comments, contact us.

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