Car companies have been leaders in the Industrial Revolution since Henry Ford invented the assembly line. Today, it is common to see robots working next to autoworkers on the factory floor.
The industry’s latest advancements come from machine learning that improves the manufacturing process and the vehicles. New cars are both digital and mechanical. The data they collect and receive helps companies and consumers in six exciting ways.
1. Improve factories
Auto machine learning can make factories more efficient. Robots and equipment used to build the cars have sensors that send alerts about defective parts. This can help the manufacturer make a repair before it shuts down the assembly line or causes damage. A study by Capgemini found that by 2023, smart technology could add up to USD 160 billion each year to the global auto industry with gains in productivity.
Quality control in a factory is also improving due to machine learning. Workers who are tasked with the job have the potential to make errors. Systems that run with artificial intelligence (AI) can also miss issues if they weren’t programmed correctly. However, machine learning can improve the process by gathering feedback and updating the system.
Audi uses cameras that can detect cracks in sheet metal that are not visible to the human eye. GM uses sensors to monitor factory conditions. If the paint area is too hot or cold, the paint will not set, and the equipment could fail.
2. Predict inventory demand
Cars are expensive to build, and inventory has a significant impact on profits. If a car has higher demand than expected, auto manufacturers can miss sales. On the flip side, if a car has lower demand than anticipated, it may have to be sold at a loss.
Machine learning can monitor and analyze market conditions to forecast demand. For example, Volkswagen uses economic, political, and even weather data to predict car sales in 120 countries.
3. Generate customer sales
Machine learning can help car companies sell more vehicles. It can collect data about a customer like demographics, past transactions, and online activities, and create personalized promotions.
Cars.com uses machine learning to help customize the car search process. It matches buyers with cars based on a quiz that measures the shopper’s lifestyle preferences.
4. Prevent problems
AI in the automotive industry can directly help the car owner. For example, car maintenance used to be preventative — something you did on a schedule. Drivers got their oil changed about every 3,000 miles, and their tires rotated every 8,000 miles.
With machine learning, maintenance becomes “predictive.” Instead of basing service on mileage or waiting until a car breaks down, sensors can detect damage and predict problems before they happen and notify drivers via the dashboard or their phones. Drivers can then schedule service at a convenient time for them.
With predictive maintenance, itis possible that recalls, or roadside service could become things of the past.
5. Communicate With Customers
Machine learning improves communication with customers.
If a car needs service, an automated chatbot can set up and confirm appointments and send reminders. Chatbots can also conduct surveys after service is done to help auto manufacturers and dealerships personalize service. They can even answer customer questions.
A McKinsey study found that a well-designed chatbot could resolve about 80% of customer interactions, reducing call centers’ costs.
6. Avoid Collisions
Perhaps the most exciting thing about machine learning is improving driver safety.
Sensors monitor the car’s activity as well as vehicles that are traveling nearby. The car can warn the driver of a dangerous situation or even take action.
Infiniti offers Predictive Forward Collision Warning and Forward Emergency Braking features. The technology analyzes the speed and distance between the driver’s car and the two cars in front of it. If the two vehicles in front of the car slow down or brake suddenly, the system alerts the driver. It can even take over and slow or stop the car if the driver does not have time to respond.
Vincent Tang, regional vice president for Asia at Epicor, wrote this article.
The views and opinions expressed in this article are those of the author and do not necessarily reflect those of CDOTrends. Image credit: iStockphoto/metamorworks