4 most widely used automation technologies in the automotive industry

Currently, there are four automation technologies in the automotive industry that are most widely used and with which companies in this sector are digitising their production processes.

Automation technologies in the automotive industry have integrated options such as collaborative robots, robotic arms, the Internet of Things (IoT) and Artificial Intelligence (AI) into the manufacturing process. These robots are producing car parts such as chassis, powertrains and other components, with the exception of some simpler parts that can be made by human workers.

New automation technologies in the automotive industry combine advanced robotics with automation technologies and learning modules, performing tasks with high precision and increasing industrial productivity.

In the automotive industry, machine vision provides a significant number of tools that will assist the factory, both in the inspection of components and in the correct assembly of parts during the automotive production line assembly process.

So, to learn more about the four most widely used automation technologies in the automotive industry, let's take a closer look at each one:

1. Machine vision (MV)

The need to manufacture safer, more reliable, and more robust cars to justify price points is pushing car manufacturers to adopt machine inspection. In this way, the Machine Vision (VM) system is one of the automation technologies in the automotive industry that meets this need by providing an automatic internal machine inspection method.

The focus of VM is to perform automatic inspection and analysis based on images for automatic inspection, process control, and robot guidance. This technology is also known as “computer vision” because it handles a large source of high-quality technologies, software and hardware products, integrated systems, and, of course, expertise. 

Of the most widely used automation technologies in the automotive industry, VM functions as the eye of the automotive production process through the use of imaging processes, including conventional imaging, hyperspectral imaging, infrared imaging, line scan imaging, 3D surface imaging, and X-ray imaging.

Smart cameras, or smart sensors with frame capture devices, are used with customised interfaces to record or capture images of the surface to be inspected. There are also digital cameras capable of connecting directly to a computer via various internet interfaces.

With the VM system, cameras capture images of the surface of the car component to be inspected. For example, the body or fins of an engine. These images are then analysed and processed by specialised analysis software, which mostly uses the principle of Finite Element Analysis in its work. A VM system helps car manufacturers save money, justify price points and emerge as strong competitors.

2. Collaborative robots

The second of the four most widely used automation technologies in the automotive industry are collaborative robots, commonly referred to as cobots. These are machines that work independently, without the need for human presence in their workspace.

A cobot uses machine learning to pause all its operations when a human worker enters its space. So why are they called “collaborative” even though their functions are the opposite? Cobots actually help human technicians handle a large part of the work when an order requires multiple functions to be performed at once. For example: The cobot will allow the worker to work on it, and then shut down when the latter's work is finished. Not all cobots are the same; some are designed to stop, while others are not. According to ISO 10218, there are four basic types of cobots in terms of functions:

• Supervised safety shutdown.
• Manual guide.
• Speed monitoring.
• Separation and power and force limiting robots.

3. Artificial Intelligence (AI) for driverless/autonomous cars

Artificial Intelligence (AI) is another of the most widely used automation technologies in the automotive industry. This technology works by creating and storing an internal map of the environment (street, town or region) using smart sensors such as radar, sonar and/or laser. It then processes this input, plots the most plausible trajectory, and sends instructions to the vehicle's actuators that control acceleration, braking, and steering. 

With programmed driving protocols, obstacle avoidance algorithms, predictive modelling, and intelligent object discrimination (i.e., knowing the difference between a bicycle and a motorbike), the car will follow traffic rules and avoid obstacles.

4. Cognitive computing in connected IoT vehicles

Cognitive computing (CC) is another of the most widely used automation technologies in the automotive industry. CC is a technology platform based on artificial intelligence and signal processing. 

These platforms encompass and utilise machine learning, reasoning, human language processing, speech and object recognition, human-computer interaction, dialogue and narrative generation, among other intelligent features. Meanwhile, cars connected to this automation technology are vehicles that use the Internet to connect and communicate with each other to create safe, easy and hands-free traffic.

To date, several automotive manufacturers are combining CC and IoT to invent autonomous cars that communicate with each other, while recognising and linking driving patterns with the emotional response of their human drivers in all possible scenarios (such as applying brakes at the right moment, with due caution, to avoid accidents).

Vehicles with this type of automation technology would prove to be much more advanced than driverless cars, should the technology be approved and successfully replicated.

Some successful exercises with the IoT platform have enabled car manufacturers to develop a cloud-based service to connect remote OBDII devices and vehicles, manage vehicle diagnostics and driving behaviour data, integrate data with business systems, and develop new applications for connected and innovative vehicles. 

The world of robotics is becoming increasingly involved in human life to ensure safer and more accurate processes. With the application of some of these intelligent platforms and the automation of production, taking into account goals such as a greater visibility of the automotive supply chain, We may well be approaching a new industrial revolution, which is not too far off.

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