Cad Models, Simulations, And Digital Twins – The Evolution And Value Addition

By Author: Satya K Vivek
Total Articles: 77
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Engineering professionals at the best companies have worked with models for designing, testing, and improving the quality of products. Modelling tools have made it easier for the industry to innovate initially with hand-drawn blueprints and later by using computer-driven systems.

Digital Twins have lately taken over the engineering world by storm, but to understand why they are so powerful, we must first look back to the days when we used CAD models and simulations to achieve the same goals. Only then can we realize how these intelligent, data-driven virtual replicas have changed the scope of model making.

From CAD Models to Smarter Design
Computer-Aided Design (CAD) first came into being during the 1960s and then earned mainstream popularity in the 1980s, thus transforming the scope of engineering forever. It is being replaced with the practice of manual drafting using particular and repeatable 2D and 3D digital drawings.

By using 3D CAD models, engineers can easily visualise the products they create from every angle, evaluate their assembly fits, and come up with new digital prototypes. Such an ...
... evolution minimized design cycles by about 30% to 50% compared to the previous manual methods. They also accelerated the time-to-market quotient and reduced costly human errors throughout industries like automotive, aerospace, and construction.

However, CAD models ultimately remained static in their functionality. Although they defined the appearance of products, they could not determine their behaviour in the real world.

The Leap into Simulation
Even as early as the 1990s, digital simulations were used by engineers to create models that were closer to reality. By using mathematical models and physics engines, these professionals could virtually test performance before even developing a single physical prototype.
Simulations allowed carrying out stress analysis, thermal modelling, fluid dynamics, and motion studies. For instance, aerospace companies reduced the need for wind-tunnel testing significantly by adopting Computational Fluid Dynamics (CFD) and saved millions in research and development costs.

According to NAFEMS reports, simulation adopters have reduced overall development costs by about 20% and achieved around 15% faster time-to-market. However, simulations were still very predictive and not related to live data, and their accuracy rested almost wholly on input parameters and assumptions.

The Current Rise of Digital Twins
The digital twins are structures that are dynamic, data-driven models of the real products, processes, or systems. Digital Twins were first propagated by NASA. It dates to the early 2000s when they were used to monitor spacecraft systems. Unlike the old-style CAD models or simulations, a digital twin incessantly updates itself using IoT sensors, AI, and analytics, reflecting its physical counterpart in real time. The global market for digital twins was worth around $12.9 billion in 2022 and is expected to go beyond $110 billion by 2028.

Value across the Product Lifecycle
Digital twins offer numerous benefits apart from design efficiency:

Smarter Design Decisions: Continuous feedback allows easy design refinement and performance optimization.
Efficient Manufacturing: Virtual production line twins lessen interruption and boost efficiency by up to 25%.
Predictive Maintenance: Live data permits engineers to envisage fiascos, thus saving millions in unforeseen downtime.
Enhancing Sustainability: Digital Twins enable the creation of greener, regulation-compliant products.
The world of engineering has evolved over time, from CAD’s precision to simulation’s predictive power, and now to digital twins’ real-time intelligence. Digital twins offer a major competitive advantage to business leaders when they want to save costs and design innovative products.

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