Top Automation Processes Used in the Automotive Industry Today

Many industries have adopted automated technologies, such as AI or machine learning. While much of this technology is still in its early stages, it is already doing impressive work—automation in the automotive industry, for example, has led to a steep increase in productivity, even in complex tasks. Here, we’ll discuss four high-tech automation processes utilized by the automotive industry today.

Machine Vision

Machine Vision (MV), also known as “computer vision,” helps automakers to create safer, more robust vehicles that justify higher price points. In fact, the automotive industry was one of the first to adopt this high-end technology.

MV works by using numerous imaging processes to photograph the surfaces of the vehicle that needs to be inspected. These images are processed by analysis software, which typically utilizes the principle of Finite Element Analysis (a computerized technique used to simulate how a product would fare in a real-world scenario of vibrations, forces, extreme temperatures, fluid flow, and other conditions).

In addition to conventional imaging, other images that MV can capture include:

• X-ray imaging
• 3D imaging
• Infrared imaging
• Hyperspectral imaging
• Line scan imaging

This technology saves costs for automakers while allowing them to increase their price points and stay competitive.

Collaborative Robots

Also known as “cobots,” these robots may initially sound like machines that work with humans, but this is generally not the case. In fact, cobots frequently work independently. Per ISO 10218, there are four main types of cobots:

• Safety Monitored Stop
• Hand Guiding
• Speed and Separation Monitoring
• Power and Force Limiting

Designed around their necessary end function, cobots increase speed and productivity by taking on certain tasks normally done by human technicians. Many cobots are designed to multitask alongside technicians, automatically shutting down when the tasks are completed. Cobots can also pause when technicians enter their workspace, meaning that humans can easily take over any aspects of the task as the need arises.

Artificial Intelligence for Driverless Cars

At its core, Artificial Intelligence (AI) is a system that can achieve goals by reacting to its environment. This is particularly beneficial for driverless cars. In this scenario, AI uses smart sensors—including radar and sonar—to create and store an internal map of its surroundings. This allows it to interact with its environment, plotting out the best trajectory and communicating with the vehicle’s actuators.

AI for driverless cars utilizes a number of technologies, including:

• Predictive modeling
• Coded driving protocols
• Obstacle avoidance algorithms
• Smart object discrimination

Use of these technologies enables the AI to differentiate between various objects on the road, navigate around obstacles, predict behavior, and follow traffic laws at all times.

Cognitive Computing in IoT Connected Cars

While AI functions independently in driverless cars, Cognitive Computing (CC) makes use of both AI and signal processing. CC utilizes a variety of technologies, such as:

• Dialog and narrative generation
• Human-computer interaction
• Human language processing
• Reasoning
• Machine learning

Benefits of Cognitive Computing

Driverless cars utilizing AI need to drive alongside vehicles without AI, and are unable to communicate with other cars on the road. The main benefit of CC in IoT connected cars is it can use the Internet to connect to other CC vehicles on the road, making traffic significantly safer and more predictable.

Although this technology is still new, it could prove to be much more advanced than current driverless car systems. Certain automotive companies, including IBM and BMW, are already working on inventing autonomous cars using CC in IoT vehicles. If all cars eventually adopt this technology—allowing them to communicate with each other and recognize human driving patterns—car accidents may be able to be entirely eliminated.

How Magnetic Components Factor In

Magnetic components power much of the technological advances we have outlined above. There are four types of magnetics to be aware of:

• Low frequency: These magnetics range from 50 to 500 Hz. Devices using these magnets include 115V AC equipment such as HVACs and electricity meters.
• High frequency: Ranging from 16kHz to MHz, these magnetics are often used to charge cell phones.
• Non-isolated: This type of magnetic component decreases electric noise.
• Isolated: Isolated magnetics prevent electric shocks.

Aiding Industry Growth

The automotive industry is expected to grow drastically in the upcoming years. Research into materials helps the auto industry grow and continue to find brand-new solutions and uses for various vehicle components, including transformers. Magnetic components also aid in the development of electric cars, as their motor control systems make use of magnetics that draw energy from batteries. As battery quality continues to develop, magnetic parts will also continue to improve.

Automotive Magnetic Components at MPS Industries

The ongoing development of automation in the automotive industry is leading to increases in productivity and, eventually, decreases in accidents and fatalities. At MPS Industries, we offer magnetic components designed specifically to assist the automotive industry in its growth, including:

MPS transformers and inductors are included in the design of the following product applications:

• DC/AC Inverters
• Fuel Pumps
• Backup Sensors
• DC-DC Boost Converter
• Electric and Hybrid Vehicles
• Power Converter Modules
• Particulate Matter Sensors
• Trailer Brake Power Modules

MPS engineers custom-build these magnetics using our automotive clients’ unique electrical specifications. Contact us to learn more about how we can help meet your goals.