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DIGITAL TWIN: HOW INTELLIGENT DATA MODELS CAN HELP SHAPE THE FUTURE FOR ENTERPRISES

Ever since the emergence of the COVID-19 contagion, every enterprise and industry are widely adopting digital transformation strategies. Even manufacturing sectors and their operations are becoming increasingly digital or virtual. As this new trend unfolds, several organizations frequently strive to choose what they should invest in to drive and deliver substantial ROI both operationally and strategically. Indeed, their selection of technology entirely depends on the services they provide or how they develop those services. For them, digital technology may ensure considerable advantages—advantages that would never have been accomplished earlier without the advent of virtual, smart technologies. Of particular attraction of late seems to be the concept of a Digital Twin: often referred to as a precise real-time virtual representation of a physical thing in the real world.

Until lately, the digital twin and the extensive quantities of big data it analyzes often prevailed intangible to businesses because of constraints in traditional digital technology. However, with the increasing potential capabilities of cloud storage, edge computing, 5G networks, and many other technologies, the digital twin has seen exponential adoption. Comparatively lower processing expenses and advanced power capabilities have commenced a significant change that empowers the combination of (IT) and operations technology (OT) to enhance the digital twin.

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Why Is The Digital Twin Important For Enterprises?

The digital twin can enable businesses to develop a comprehensive digital footprint of their products, machinery, devices, etc- anything in the real world. They can streamline the entire product from design, development and deployment through the end of the complete product life cycle. These deep insights and analytics regarding the product will enable them to experience not only the product in a virtual simulation but can help them understand the pros and cons of the product in a real-world environment.

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With the implementation of a digital twin, organizations can significantly improve the time to market of a new product, improve business operations, reduce employee stress and defects. The digital twin is capable of preventing physical errors faster by identifying them promptly in a virtual environment. The grouping of advanced technologies such as Artificial Aptitude (AI) and Natural Dialectal Processing (NLP) with digital twins helps in predicting results to a considerably higher level of accuracy. This eventually helps the manufacturing sectors in designing and building more reliable products, and, ultimately, prevents calling back products.

With this innovation in creating smart architecture design, manufacturers will realize quality and advantages faster than with traditional product manufacturing. But before anything else, businesses must understand how the digital twin technology works in order to efficiently integrate it into the operational process.