Digital transformation of the automotive industry
Industry 4.0 refers to modern factories with interconnected digital systems communicating with each other and with humans - also called ‘smart factories’. Many of these technologies are already in use and manufacturers are seeing visible improvements. Recently, 94% of the surveyed organizations said Industry 4.0 technologies helped keep their operations running during the pandemic. Moreover, 58% said these were critical to their crisis response.
The automotive industry has the opportunity to utilise the latest technologies in manufacturing plants as well as in their products to revolutionise the industry. The digital transformation of the automotive industry has already been kicked off by major OEMs like BMW, Ford and Porsche with adoptions of computer vision, AGVs and IIoT in their operations.
Smart manufacturing and smart vehicles
Industry 4.0 includes multiple technologies that contribute to the design, manufacturing, testing, maintenance and demand forecasting in the automotive industry. The comprehensive improvement due to higher efficiency, better product designs and safety can be huge once an OEM achieves smart manufacturing.
Moreover, technologies like IoT, AI and ML are central to the development of smart vehicles, which have quickly created a space for themselves. The development of self-driving cars is another front of smart vehicle development where conventional OEMs face new competition from Tesla, Apple, Waymo and others, due to technologies like LiDAR, computer vision and IoT.
Let’s have a look at some of the major improvements being made by Industry 4.0 technologies to get an idea of their impact on the industry.
Additive manufacturing
Additive manufacturing techniques have rapidly become common in various high-precision industries. These techniques have the ability to 3D print a complex prototype with unmatched accuracy, which can accelerate the designing and testing phase for OEMs. Rapid prototyping technologies foster R&D and provide designers with the freedom to innovate.
Digital twins
Digital twins are data-powered models which simulate products - including all their systems and sensors. The automotive industry can create vehicle digital twins to test mechanics, software, electronics and physical characteristics through simulations. Digital twins can also aid in planning manufacturing capacity expansions, predictive maintenance, training and sales.
IIoT, AI and ML
Industrial Internet of Things (IoT) creates the infrastructure required for interconnected systems to communicate with each other using embedded sensors. The information can be utilised by the plant to optimise production based on real-time conditions.
IIoT is used in automated robots, predictive maintenance, inventory management, material handling and many other parts of the production system. A large amount of data available from the system improves operations visibility and helps align maintenance and production.
Artificial intelligence (AI) and machine learning have a special place in today’s manufacturing and autonomous vehicle development. Predictive maintenance and automated robots use AI and ML in combination with IIoT to make manufacturing more efficient. Smart vehicles use IoT for infotainment systems to warn the user when a part in the car needs repair. Self-driving vehicles also use AI and ML in their Advanced Driver Assistance Systems (ADAS).
The improved automotive industry
Industry 4.0 technologies can create a smart automotive factory where all systems are connected and optimised for high efficiency. They improve the flexibility of manufacturing which is a key requirement to remain competitive in the industry.
Predictive maintenance and optimum resource utilisation reduce downtime and costs. Also, there is Supply Chain 4.0, a concept for optimized supply chains using data and connectivity for uninterrupted, accurate and efficient production. Another important advantage of Industry 4.0 is the greater workplace safety due to automation and sensors.
Industry 4.0 can be revolutionary for the automotive industry due to its broad applications. The potential to optimize manufacturing and create a unique customer experience gives OEMs enough reasons to upgrade their production systems. While many big brands have started adopting these technologies, the industry’s competitiveness requires companies to consider the return on investment, demand and customer willingness to pay for the smart features.
