The fourth industrial revolution (Industry 4.0) is accelerating the demand for data. The data-driven production techniques and the rising adoption of big data. One of the most popular data-driven manufacturing concepts is the digital twin. It allows organizations and manufacturers to mimic items to construct them faster, more cost-effectively, and of higher quality.
📍In the automotive industry, what are digital twins?
A digital twin is a virtual reproduction of a full car in the automotive business. It includes the software, mechanics, electrics, and physical behavior. All real-time performance, sensor, inspection data, service history, configuration changes, components replacement, and warranty data are stored in the digital twin.
📍What are the applications of digital twins in the automotive industry?
The following are some examples of digital twin applications in the automotive industry:
🚗 Product Testing
A product’s digital twin aids in assessing its quality and performance by virtually testing with various compounds. The raw materials to improve the design and maximize the product’s performance. A digital twin of a new tire, for example, can be virtually modeled. It is tested for various weather conditions before being optimized based on the outcome.
Increasing manufacturing capacity before investing in new manufacturing machines to boost output. Organizations can use digital twins to model the impact and benefits of the new machine on production capacity. The virtual model must consider the characteristics of the company’s product, the materials used, historical data on production time and necessary machinery, and so on before providing information on how the new machine might boost product production.
🚗 Employee Training
Companies can create a digital replica of a factory’s infrastructure and train workers remotely without physically installing the equipment. For example, a manufacturing company in Europe can train its employees in Mexico on a digital twin of the factory even before the complete infrastructure is install in Mexico, making the hiring process easier and allowing new hires to understand their training needs.
🚗 Predictive maintenance
Machine and manufacturing equipment digital twins can utilize to detect maintenance requirements and improve the health of production lines and facilities. To detect fault recurrences and causes, digital twins must employ real-time data derived from IoT devices and sensors in the production process.
Customers can give feedback on products before they are introduce to the market, which is one of the future consequences of digital twin technology. A corporation can allow a possible buyer to check out the product, examine the new features, and compare it to prior designs using a car’s digital twin. Manufacturers can change the features of cars in 3-D images and get feedback from customers before producing them.
🚗 Various operations
A digital twin of an organization (DTO), a digital clone of the corporation itself, is another application of digital twin technology. DTO assists businesses in better understanding and optimizing their processes. Because DTO relies on process data contained in documents and IT systems, it necessitates process mining to collect and analyze event log data to build a DTO.
📍 What are the advantages of digital twins in the automotive industry?
The automobile sector as a whole benefit from digital twins because:
🚗 Bringing data together
The digital twin overcomes the problem of combining data from many sources (e.g., Historical data of previous models, performance data, driver behaviors). The maker can visually assess and analyze the data to gain any insight.
🚗 Verifications are made easier
Companies waste time verifying new features or designs since they have to wait for manufacturing to see if their ideas are feasible. A digital twin can use to validate design success and efficiency quickly and reliably. It can gather all the information needed to execute simulations that produce reliable results.
🚗 Avoid failures
Because digital twin technology may use data to predict when machine downtimes will occur based on historical data, it can assist organizations in taking efforts to minimize such failures, allowing for continued production with minimum financial loss.
🚗 Customer demand forecasting
Once the car is on the market, manufacturers collect customer experience data to see which features are the most popular. Manufacturers may use digital twins to predict customer demand better and improve customer experience by leveraging customer experience data.
📍 What are the digital twins’ challenges in the automated industry?
🚗 Adoption of new technology
At each stage of the vehicle’s product life cycle, a vast amount of data is generate in the automobile sector. Big data facilitates the development of faster, more cost-effective, and higher-quality goods. However, car manufacturers have vary levels of successful data usage, with only about 12% of accessible data being analyzed. Consider an international automobile firm that manufactures autos at every stage worldwide. The maturity of data adoption across all areas involved in the product life cycle should be equal to building a vehicle’s digital twin.