The manufacturing industry is thriving at a rapid pace but it is necessary for manufacturers to cope with increasing demand. Here, digital twins can be useful for simulating the production process. This concept is designed to facilitate manufacturers to create virtual representations of a real-world product, production process, equipment, or a whole system.
Such representations or simulations can help manufacturing industries track and manage machine operations in real-time. Digital twins can be augmented with machine learning algorithms, and manufacturing companies can identify problems in advance with the help of predictive analytics.
When it comes to maintaining equipment, digital twins make it possible to monitor the equipment’s health and identify potential anomalies in real-time. With the help of machine learning and artificial intelligence, a customized digital twins solution can accurately predict the time of maintenance. Manufacturing companies can take proactive measures to avoid sudden downtime or prevent the breakdown of equipment.
Visual representation of equipment and plants is cumbersome. The remote location of manufacturing units makes the process of creating virtual models even more difficult. Also, manufacturers need to address the challenge of getting and analyzing real-time performance data for equipment and infrastructure.
IoT-based digital twins can make visual models of equipment and plants based on real-time performance data. Such data is accurately analyzed by advanced analytics and ML-powered algorithms. With this, digital twins can simulate all possible ‘what-if’ scenarios to define the best operational condition.
Thanks to digital twins, manufacturers can use raw materials with more precision and reduce wastage. As a result, they can get high productivity while meeting quality standards easily. Eventually, simulation by digital twins can make the manufacturers process more efficient.