Just like in the Star Trek holodeck, digital twins are virtual replicas of the physical world. They enable industries to predict and optimize processes using live data. In manufacturing, digital twins create a real-time digital profile of production lines, assets, and processes. Manufacturers can use digital twins to analyze performance, predict failures, and refine workflows before making physical changes. 

But digital twins aren’t a new phenomenon—neither in movies nor in real life. However, the boom in digitalization in recent years means they have become far more accessible. In fact, the global digital twin market is projected to grow from $10.1 billion in 2023 to $110.1 billion by 2028, with a compound annual growth rate of 61.3%. Today, manufacturers are increasingly leaning on digital twins in many stages of the product life cycle.  

Transforming product development with digital twins

The ability to develop and launch new products is often the key to a company’s survival. McKinsey estimates that in the coming years, about $30 trillion in corporate revenue will depend on products not yet on the market. However, this is becoming more challenging, with customers expecting constant evolution in quality, novelty, and sustainability. This has led more companies to seek out ways to cut costs and speed up design cycles. 

In fact, research by McKinsey indicates that using digital twins can cut total product development times by 20–50% and reduce costs from physical prototyping along the way. A prime example of this is automotive giant Renault.

Much like how Star Trek’s engineers could fine-tune the Enterprise in a simulated environment, Renault builds a complete 3D digital twin of its vehicle—allowing designers to optimize aerodynamics, ergonomics, and system compatibility before producing a single physical part. Once optimized, the digital twin can inform the first prototype, significantly reducing design time.

Digital solutions for production processes

Beyond development, digital twins offer tangible benefits to the production process, too. By simulating different scenarios and continuously integrating real-time production data, they enable operators to make informed decisions about how production can be improved.  

Take the LG Electronics factory in Changwon, Korea. The factory used a digital twin to integrate real-time production data continuously into its assembly line visual simulation system. As a result, it improved operational productivity by 17%, product quality by 70%, and cut energy consumption by 30%.

Similarly, BMW has implemented a groundbreaking digital twin strategy through its BMW iFACTORY project. The company has fully captured its production sites using 3D scanning technology, creating digital twins that can be explored virtually in real time, no matter the location or time zone. This virtual approach allows users to walk through production lines with machines and employees while also integrating new vehicles into existing systems. By simulating production environments digitally, BMW can quickly identify areas for improvement in its manufacturing chain, saving time and resources.

With continuous data collection, operators gain real-time insights into system health. This allows them to pinpoint any potential issues that may lead to failure and take corrective action.

Integrating virtual commissioning into operations and maintenance

A significant application of digital twins in operations is virtual commissioning. This process allows manufacturers to test and optimize automation systems in a virtual environment before physical installation. By simulating real-world conditions, virtual commissioning helps ensure that all components, such as PLCs, robots, and HMIs, work seamlessly together. It minimizes downtime, reduces risks, and ensures systems are fully operational once physically implemented. This proactive approach not only accelerates system startup but also enhances ongoing maintenance by identifying potential issues early.

At COPA-DATA Silver Partner IDM-Systems Zrt., this concept has been taken a step further and developed into a comprehensive system based on two key components: the digital asset twin and the operational twin.

Digital asset twin: a periodically (on-demand) run, functionally validated 3D model that includes virtual peripherals such as HMI, PLC, and robot programs needed for operation. This model enables real PLC, robot, and HMI programs to be executed, making it ideal for virtual commissioning (i.e., testing and optimizing PLC programs) as well as training purposes.

Operational twin: a continuously running, data-based logical twin that remains synchronized with the real system. It maintains a real-time data connection to the physical environment and incorporates modules such as Predictor, Energy Optimizer, and Correlation Explorer to extract valuable insights from operational data.

These models integrate seamlessly through a framework and interfaces, ensuring real-time data exchange with SCADA and MES systems. The Zenon-based SCADA system further enhances efficiency, operator training, and overall performance.

Smarter factories, smaller footprints

While productivity and efficiency are obvious benefits, digital twins play a key role in enhancing sustainability in manufacturing by providing real-time insights into energy consumption, waste generation, and material use. By analyzing these data, manufacturers can identify areas to reduce energy and resource consumption, ultimately lowering their environmental impact. 

In Star Trek, the crew of the Enterprise didn’t make decisions based on guesswork. They used simulations, real-time data, and predictive technology to guide them. Today, digital twins are bringing that same level of foresight to industry. By harnessing real-time data and digital tools like COPA-DATA’s zenon, businesses can optimize development at every stage of the product life cycle. 

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