Digital twin has provided great competitive advantages for industries that seek in digital transformation and Industry 4.0, a way to use new digital technologies in order to generate greater integration, flexibility and control over the operation
The technology consists of a continuous flow of data between real and digital assets, where an authentic digital twin is able to generate actions on assets through the digital or real sphere, unlike the concept of digital model and digital shadow.
Read on: Understand what an authentic digital twin is
The high level of digital integration of an authentic digital twin has attracted attention from major industries. In research conducted by Globenewswire, it is estimated that the market will reach a value of $4 billion by 2027, thus demonstrating the high applicability of the technology with good prospects for financial return.
The opportunities generated
Digital twins can be implemented at any stage of the asset lifecycle (PLM). There are models for the design and construction phases, most common in the construction and project development industry. Another kind of application is for the operation and maintenance phase, with more attractive purposes for process industries.
The digital twins have as a great advantage the opportunity of total control in an industrial plant. From the implementation of this technology, industries can integrate and centralize their processes, generating greater assertiveness in the execution of activities and less time spent.
Another attractive benefit of the technology is the possibility of implementing artificial intelligence algorithms that along with the digital twin will provide insights into possible scenarios, budgets, and can also generate important information about possible failures within the operation.
Besides the benefits mentioned above, one of the great advantages of the digital twin is the data contextualization provided by the technology. Perhaps this is the most important benefit generated by the technology, since digital processes and operations have huge amounts of data that need to be processed in order to be used as a generator of knowledge by decision makers.
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