Home5G5G manufacturing use case spotlight: Troubleshooting using a digital twin

5G manufacturing use case spotlight: Troubleshooting using a digital twin

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What is a digital twin?

According to the Digital Twin Consortium, digital twins are “virtual models of a process, product or service that allow for data analysis and system monitoring via simulations” to make data-based decisions around maintenance, sustainability, efficiency and performance.

A white paper by Altran highlighted that companies in almost every industry are looking to digital twin technologies to drive meaningful business outcomes across the entire product development life cycle, from ideation and production to manufacturing, support and maintenance. Digital twins integrate geometry, real-time telemetry, engineering analysis, sensors, connectivity, artificial intelligence, machine learning and software analytics in a unified spatial model to create a living digital simulation that can update and change as their physical counterparts change. Digital twins are used to help companies improve a variety of business processes, from validating the expected behavior of a product or system design before it is deployed, to boosting production efficiency of a factory or optimizing the performance or maintenance of products in the field.

How can digital twins improve smart manufacturing processes?

Specifically in manufacturing, digital twins could be created to focus on a single component within the manufacturing process or to focus on a single piece of equipment within a production line. Also, digital twins could be implemented at a manufacturing site to monitor and improve an entire production line or even monitor the entire manufacturing process from product design and development to production.

In a research note, GlobalData Principal Disruptive Tech Analyst Kiran Raj highlighted the relevancy of digital twin capabilities—using sensor data and software tools to build virtual models of current and future state physical assets or processes—to product iteration, asset monitoring, improving maintenance regiments, and reducing downtime in industrial environments. The researcher specifically called out the oil and gas, automotive, healthcare, and construction verticals as likely drivers of digital twin adoption.

Digital twins for troubleshooting in the manufacturing field

According to Simultech Multimedia, one of the ways digital twinning of production facilities is expected to help manufacturers is in the area of maintenance and repair and optimized asset performance. Digital twins allow hybrid visualization, a combination of visual information and both live and historical data. This kind of visualization lets manufacturers look into the hidden place deep within production machinery (including even very difficult-to-access equipment, such as subsurface oil reservoirs or space vehicles) to check temperature abnormalities, structural integrity, and other conditions that lead to equipment failure and inefficiencies. That way, they can be dealt with in the real-world before they become a problem, providing huge savings in avoided downtime, Simultech said.

TechSci Research said that the digital twins are created to transform the way companies perform predictive maintenance of products, identifying and addressing malfunctions even before they happen. “Sensors embedded in the machines feed performance data into the digital twin in real time, which helps to tailor service and maintenance plans for effective asset management, enhanced worker safety, reduced risk of accidents, lower maintenance costs, and improved customer satisfaction,” the firm said in a blog post.


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