The India digital twin market is expected to reach $12 billion by 2032, with a CAGR of 39.3%. The adoption of digital twins varies across sectors, yet manufacturing drives the way. A survey by Deloitte revealed that 15% of manufacturing executives plan to invest in digital twin technology within the next year. The automotive, aviation, and industrial equipment industries are specifically, strong adopters that are driven by the requirement for high precision & reliability.

Manufacturers in today’s rapidly evolving automotive industry are looking for innovative ways with an aim to enhance productivity, decrease costs as well as improve product quality. A transformative technology in this space is the digital twin. Automotive manufacturers can simulate various scenarios, predict outcomes as well as make data driven decisions by creating a digital counterpart of a physical asset. In this article let us look at the top three use cases of digital twins in automotive manufacturing that include product design and prototyping, quality control and predictive maintenance, supply chain management, and others.

Product Design and Prototyping

“Electric vehicles are soaring in popularity, and this is reflected in the demand for prototypes,” says Daniel Abel, Director at Futura Design. One of the most critical phases in automotive manufacturing is product design and conventionally, designing any new vehicle or even any automotive component comprises building physical prototypes that are expensive as well as time-consuming. However, owing to the advent of digital twins, manufacturers can today create virtual prototypes as well as run simulations in order to test numerous design scenarios. The global product prototyping market size is anticipated to reach USD 63. 91 Billion by 2030 registering a CAGR of 11.6 per cent until 2030. Digital twins help manufacturers in replicating the real-world performance of vehicles or even automotive parts in a virtual environment. This allows designers in evaluating factors which include aerodynamics, structural integrity & crash safety.

The use of digital twins was pioneered by Siemens specifically at their Amberg Electronics Plant in Germany. This manufacturing plant manufacturers PLCs and leverages digital twin technology for creating a virtual replica of the complete manufacturing process. This digital replica comprises all elements right from machine operations to production workflow. Through stimulating and optimizing these processes, the company has made a huge progress, with a 30 per cent increase in the ability of adjusting manufacturing volumes which is a 20 percent boost in productivity as well as a 40 percent enhancement in space efficiency.

“India’s exports have surged in recent years as the nation positions itself to be the next global industrial manufacturing powerhouse. Automotive, industrial machinery, electronics, textiles, chemicals and pharmaceuticals are among the sectors expected to help drive India’s exports to $1 trillion by 2028,” says Madison Huang is director of product and technical marketing for NVIDIA Omniverse.

Manufacturing Process Optimization

“Digital Technology uses real-time data from the physical systems, enabling ongoing improvements and predicting maintenance needs. Manufacturers can simulate entire powertrain systems, leading to better energy management, optimised manufacturing processes, and improved quality control,” says Naoya Nishimura, CEO, Musashi - India and Africa.

In the automotive industry, manufacturing is one of the highly complex as well as intricate process which comprises the integration of several machines, human workers as well as systems. Therefore, inefficiencies in any part of the manufacturing process can result in huge delays, quality issues or even higher operational costs. By rendering real-time, digital representation of the complete manufacturing line, permitting manufacturers to simulate, monitor as well as optimize all aspects of their operations.

Automotive manufacturers can track the performance of every machine, worker as well as phase in the manufacturing process by creating digital twins of their manufacturing lines. This helps in identifying bottlenecks, inefficiencies or underperforming equipment as well. For instance, if any specific assembly station is taking longer than assumed, digital twins will not only help in pinpointing the reason stating whether it is a machine malfunction or shortage of materials or any labor issue but it will also provide insights on how to address that issue.

GE leverages manufacturing digital twins for monitoring and maintaining its fleet of jet engines and every engine has one digital counterpart which helps in tracking its performance & predicts maintenance requirements on the basis of real-time data collected from sensors. Now, this proactive approach has decreased reactive maintenance by 40 percent & increased engine uptime thus it helps in ensuring smoother operations as well as less downtime.

“The automotive sector holds more than 15% of the market share of digital twin adoption, with significant demand in the electric vehicle (EV) segment,” says Ram Deshpande, EY India Technology Consulting Partner.

Quality Control and Predictive Maintenance

“As vehicle technology evolves, predictive maintenance systems must be constantly updated to ensure they remain accurate and reliable,” says Sven Patuschka, Chief Technology Officer, TMPV and TPEM. 

One of the primary concerns in automotive manufacturing is maintaining high product quality. This is because defects in automotive parts or even finished vehicles will not only lead to customer dissatisfaction but also incur huge costs owing to recalls or repairs. Digital twins play a major role in enhancing quality control by helping manufacturers to monitor the conditions continuously as well as the performance of all vehicles or component manufactured. The global market for digital twins in automotive manufacturing and quality control is anticipated to reach $34.6 billion by 2032.

Digital twins help manufacturers to monitor as well as simulate a wide range of operational parameters. These include pressure, temperature, vibration as well as wear-and-tear in real-time. These replicas offer insights into the health of every vehicle as well as its components by implementing sensors for collecting data from different phases of the production process. Lastly, if any discrepancies or even anomalies are found including deviation from a normal operating condition, the digital twin will alert engineers to potential quality issues prior to escalating into major issues.

For instance, Tesla leverages digital twin technology for streamlining manufacturing processes as well as enhancing vehicle performance. All Tesla cars possess digital twin which collects data via its lifecycle right from manufacturing to daily use and this particular data facilitates Tesla to enhance vehicle designs, improve customer satisfaction as well as predict maintenance requirements. The company uses digital twin for manufacturing in order to optimize the manufacturing lines, decreasing waste and optimizing efficiency which in turn has helped the company to maintain quality standards.

“India is the world’s fifth-largest economy with a GDP of $3.89 trillion. According to S&P, we’re on track to become number three by 2030. The automotive industry is one of India’s largest sectors and the growth of the CV segment has been instrumental in achieving this,” says Satyakam Arya, Managing Director & CEO, Daimler India Commercial Vehicles.

Digital twins is revolutionizing automotive manufacturing by offering manufacturers with a powerful tool for optimizing design, manufacturing processes, quality control and others. The utilization of digital twins will become more widespread by driving efficiencies, decreasing costs as well as improving product quality across value chain since the automotive industry continues to embrace digitalization.