Digital twin technology transforms manufacturing operations, finds GlobalData
Digital twin technology runs at the technological forefront of the Industry 4.0 adoption to assist manufacturers boost productivity while lowering operating costs, optimizing performance, and transforming the way predictive asset maintenance is undertaken. As manufacturing processes grow more digital, the digital twin technology helps companies to spot physical flaws quicker, anticipate outcomes more precisely, and develop better products, finds GlobalData, a leading data and analytics company.
Abhishek Paul Choudhury, Senior Disruptive Tech Analyst at GlobalData, comments: “The key factors driving the growth in the digital twins market are the advancements in machine learning (ML) and artificial intelligence (AI) capabilities, Internet of Things (IoT) and cloud expansion, as well as the objective to reduce product development costs and time. The emerging technology is helping manufacturers test and interact with sensors embedded in functioning products, offering real-time visibility into system performance and ensuring timely maintenance.”
GlobalData’s latest Innovation radar report, “Physical meets digital: how digital twins help future-proof sectors,” highlights how various companies are developing and adopting digital twins across major sectors.
BMW uses Nvidia Omniverse platform to design a complete digital twin of an entire factory to simulate 31 factories. The duo claims that all elements of the complete factory model, including the associates, the robots, the buildings, and assembly parts, can be simulated to support various AI-enabled use cases including virtual factory planning, autonomous robots, predictive maintenance, and big data analytics.
GlaxoSmithKline (GSK) joined hands with Siemens and ATOS to pilot a digital twin of the vaccine manufacturing process. GSK plans to use the information generated to fine-tune its manufacturing using a variety of models and ML approaches. The twin can also assist the organization in parsing and modeling production variances, which is a major challenge for manufacturers nowadays.
Industrial Goods & Machinery
Amazon Web Services (AWS) has rolled out a service “AWS IoT TwinMaker” to simplify the creation of digital twins of real-world systems including factories, industrial equipment, and production lines. The service provides the necessary tools to build digital twins using existing data from multiple sources, create virtual representations of any physical environment, and combine existing 3D models with real-world data.
Choudhury concludes: “The future of digital twins seems almost infinite as they are continually acquiring new skills and capabilities to produce the insights required to improve goods and processes.”