In the Post-epidemic Era, Demand in the Automotive Industry will Pick up, and the Robot Market is Expected to Grow Rapidly

The global auto market under the influence of the pandemic

As of April 27, 2020, the number of confirmed cases worldwide has exceeded 2.81 million. The United States and Europe are the hardest-hit areas, and European and American companies have to suspend production. According to statistics, about 38 multinational auto companies had shut down or planned to shut down factories, and the total number of factories has reached more than 150.

The epidemic hits the automotive supply chain the hardest. With the continuous escalation of the global pandemic, the resumption of work of Chinese parts and components companies has been delayed, and logistics and transportation have been blocked. The supply chains of some multinational companies are facing the risk of supply disruption. The strict control measures adopted by various countries, such as transportation and population movement, affect the industrial production of each country and face certain challenges to the increasingly integrated global industrial chain.

Robots are used on a large scale in the automotive industry

At present, global automakers have used industrial robots in large numbers, and the utilization rate of robots in auto assembly and parts production is increasing. In addition, the improvement of robot raw materials and technology is reducing the cost of products, and manufacturers are more willing to invest in robots to reduce labor costs.

Robots were mainly used for cutting, welding, painting, and assembly in the original automotive industry. Some easy-to-deploy, lightweight, and space-saving robots gradually penetrated the production line. For example, due to their high speed and flexibility, parallel robots can be applied to the production of some small parts and are favored by the automotive industry. According to analysis, parallel robots in the automotive industry will maintain an annual growth rate of 4%.

In addition, SCARA robots have also found a place in the automotive industry. It is estimated that by 2024, the demand for SCARA robots in the automotive industry will exceed 30,000 units. SCARA robots are increasingly used in high-speed assembly, and their low energy consumption and fast processing capabilities are advantages in the automotive field.

At present, the four major robot families are the main suppliers in the automotive industry, with Fanuc, ABB, KUKA, and Yaskawa occupying most of the global automotive robot market. In addition, Kawasaki Heavy Industries, Omron, and Stäubli have also become important players in the automotive industry.

In general, there is still a lot of room for developing robots in the automotive industry. With the popularity of new energy vehicles, major automakers will need to invest in electric vehicle factory production lines. At present, this trend has become very obvious. Some auto manufacturers are closing traditional factories and putting funds into the layout of new energy vehicles.

High-quality training data is helping artificial intelligence break new barriers

The three essential elements for artificial intelligence to operate are computing power, algorithms, and data. Together, they form the whole of artificial intelligence.

High-quality training data will maximize the efficiency of artificial intelligence, while low-quality AI data will be not only impossible to improve efficiency, but also will hinder the evolution of artificial intelligence to a certain extent.

Previously, the media reported that a user had a car accident while riding in a smart driving vehicle. After the investigation, it was discovered that the smart driving system failed to distinguish the difference between the white vehicle and the cloud and did not identify obstacles. The vehicle failed to brake in time, which in turn triggered tragic consequences.

In this case, the lack of accurate data on the distinction between white vehicles and the cloud is the direct factor leading to the tragedy.

Therefore, the measures to provide high-quality AI data for different scenarios and different needs have gradually become the consensus of artificial intelligence solutions.

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End

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source：https://www.robot-china.com/news/202004/27/61771.html