Verónica Castro-AllendeThe concept of digital twin holds immense promise in various industries, particularly manufacturing, by enabling predictive modeling and optimization through real-time data replication. Major industry players such as Siemens, GE, IBM, and Microsoft Azure are actively investing in digital twin technology, offering professional-grade solutions to clients. These digital twins simulate the behavior and performance of physical assets, leveraging sensor data to predict future outcomes and potential failures.
While digital twins offer significant advantages like maintenance optimization and defect reduction, caution is advised by experts like Gartner due to potential complexities and associated costs. Nonetheless, companies like Chevron and Siemens are already implementing digital twin technology in their operations, aiming to streamline processes and reduce maintenance costs significantly.
As the technology continues to evolve, standardization and integration remain key challenges. However, the potential benefits in terms of efficiency and performance optimization make digital twins a compelling proposition for businesses looking to stay ahead in the era of Industry 4.0.
Efficiency and another advantages are more likely to be discovered the more a digital twin can replicate the natural object. Digital twins, for instance, could simulate how extremely instrumented devices have performed over time in manufacturing, which could aid in predicting future performance and potential failure.
Vendors for modern twins
The process of creating a modern twin is difficult, and there is currently no standardized platform for it. The outline of a modern twin platform has been put forth by Ian Skerrett, an expert in the field with extensive experience with open source, despite the fact that this is only the second step given the technology’s still-emerging nature.
Professional digital-twin offerings are coming from some of the biggest companies in the industry, in contrast to many emerging technologies that are driven by startups. For instance, Siemens, another business giant seriously involved in manufacturing, as well as GE, which internally developed digital twin technology as part of its jet engine manufacturing process, are now offering their expertise to customers. As part of its IoT push, IBM is marketing online twins to compete with these factory-floor suppliers, and Microsoft is launching its own digital-twin platform under the Azure umbrella.
Predictive twin vs. online twin
Deepak Puri, a contributor to Network World, just described an example of an Oracle online twin tool that gives users the choice between predicting twins and e-twins.
A description of the devices, a 3D rendering, and information on each sensor in the device are all possible with the modern twin. Sensor readings are regularly produced to simulate real-world options.
According to Puri, the predicted twin “models the upcoming state and behavior of the device. This is based on historical data from other devices, which can simulate emergency breakdowns and other circumstances.”
Microsoft is using the idea and applying it to processes in addition to natural products as part of its digital twin initiative. Microsoft suggests the concept of the online process twin in a white paper:
According to Microsoft, “The Process Digital Twin is the next stage of modern transformation, compounding the advantages of the product digital twin throughout the factory and supply chain.” The whitepaper highlights some cutting-edge manufacturing scenarios that process electronic twins would be able to support but that a product would not.
Advantages and disadvantages of online twins
Digital twins provide a real-time view of what’s happening with natural assets, which significantly reduces the need for maintenance. Chevron is implementing online mini technology for its refineries and oil fields in an effort to reduce maintenance costs by millions of dollars. Siemens also claims that using digital twins to model and prototype items that haven’t yet been produced can lessen product defects and speed up the process of going to market.
But keep in mind that Gartner cautions against using digital twins because they can excessively make things more complicated. “Digital twins” might be an unnecessary piece of technology for a specific business issue. Concerns about cost, security, privacy, and integration are also present.
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