One of the most rapidly evolving concepts of Industry 4.0 is digital twin technology. A digital twin is a virtual replica of a physical object run in a simulation environment to test its performance and efficacy.
Fremont, CA: The key factors driving growth in the digital twin market are growth in IoT and cloud and the desire to reduce costs and time for product development. Engineers can now test and communicate with sensors embedded within a company's operating products, providing real-time insights into the system's functionality and ensuring timely maintenance.
While digital twin technology is already being used in various industries, it is essential for product manufacturers. Let's look at some of the key advantages of using a digital twin model, what to think about before implementing one, and a real-world example of how GlobalLogic deployed digital twins for a leading warehouse automation company.
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Key Advantages of Using Digital Twin Technology
Companies can use a digital twin to test and validate a product before it exists in the real world. A digital twin allows engineers to identify any process failures before the product goes into production by creating a replica of the planned production process. Engineers can disrupt the system to synthesize unexpected scenarios, examine the system's reaction, and identify mitigation strategies.
Because IoT sensors in a digital twin system generate big data in real-time, businesses can proactively analyze their data to identify any system problems. This capability enables companies to schedule predictive maintenance more precisely, improving production line efficiency and lowering maintenance costs.
Obtaining a real-time, in-depth view of an extensive physical system is frequently difficult, if not impossible. On the other hand, a digital twin can be accessed from anywhere, allowing users to monitor and control system performance remotely.
Process automation and 24-hour access to system information enable technicians to focus more on inter-team collaboration, increasing productivity and operational efficiency.
Financial data, such as the cost of materials and labor, can be integrated into a virtual representation of a physical object. Because of the availability of a large amount of real-time data and advanced analytics, businesses can make better and faster decisions about whether or not to make changes to a manufacturing value chain.
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