Artificial intelligence in the automotive industry is yet another important fruit of the digital transformation in business. This segment is increasingly reformulated and full of new perspectives.
Electric cars, autonomous biofuels and a series of novelties are invading the dealership market and people’s lives. But how does artificial intelligence especially impact this market?
That’s what we’ll see from now on. Get ready to learn a little more about this innovation and how it fits into this universe of the automotive industry. Follow up!
What Is Artificial Intelligence?
AI (Artificial Intelligence) refers to a set of technologies and innovations encompassing algorithms, neural networks and other functionalities to optimize and improve a business, simulating human actions.
Artificial intelligence finds its applications across the entire automotive value chain. AI is currently being implemented in automotive manufacturing, including:
- supply chain;
AI is being implemented, for example, in driver assistance and risk assessment systems, transforming the transport industry. Aftermarket services such as predictive maintenance and insurance are also changing with AI use.
How Important Is It To The Automotive industry?
The use of artificial intelligence in the automotive industry still encounters certain barriers. First, most manufacturing methods already have some level of automation.
The maturation of artificial intelligence technologies is the other impediment, as this industry has a very high level of demand for the performance and safety of the final product.
However, the growing technology imposes a general reformulation in models, in which the software level gradually replaces the hardware level. That is, increasingly, applications and automation systems are added to vehicles and require using technologies based on artificial intelligence. In addition, this innovation should impact:
- improvement of manufacturing processes;
- a multitude of applications;
- increase in vehicle autonomy;
- modification of maintenance services, among other features.
How Is AI being Applied In The Automotive Industry?
There are several innovations based on artificial intelligence in the automotive industry, especially manufacturing, where we have important tools and influence in other sectors, as we will see below.
Through Lean Management technology, it is possible to optimize productivity. This innovation prints a management model focused on delivering more value and optimizing processes. In the automotive industry, it is possible to apply important indices, such as TRS (Synthetic Rate of Return) or EGE (Global Equipment Efficacy).
Identification Of Defects And Failures
The identification of flaws and defects is much more accurate with artificial intelligence. Through cameras, it is possible to film strategic points and analyze by algorithms the functioning or failure of some components.
A problem or risk is flagged in advance so that the maintenance service can take targeted actions and correct defects.
Robots are simultaneously working with humans and learning automotive manufacturing skills. With the help of AI, several industry segments are being impacted, such as:
- parts manufacturing;
Today, AI helps humans develop cars using standard structures. In the future, these AI-powered robots could operate the entire plant.
Big car makers are working to create their self-driving cars and driving capabilities. They are focusing manufacturing on tech companies and relatively young startups that grew out of the idea of self-driving vehicles. In this scenario, more and more vehicles become less physical and dependent, becoming logical and automated.
Analysis capability is another management and processing need today. At this point, artificial intelligence contributes to mass analytics for asset management, recommending plans and optimizing actions.
Management is yet another point of attention for artificial intelligence. Through this tool, it is possible to manage IT and cybersecurity environments. Data represents the newest direction of decision-making, and innovations are fundamental to support this process.
Decision-making is much more based on data than intuition these days. For this, it is necessary to have digital mechanisms to monitor general conditions of manufacture, operation and sales. The objective is to improve these analyzes and identify strategic and preventive actions.