From forest fire prevention and border patrol to tax inspection and counterterrorism, the applications for aerial drones are multiplying daily. Now, there is a new use for them: transporting car parts.

Partnering with logistics services provider Grupo Sesé, Spanish carmaker SEAT SA has implemented a pilot project to use drones to deliver components from Grupo’s logistics center to its assembly line in Martorell, Spain, in just 15 minutes.

Initially, the drones will be used to periodically transport steering wheels and air bags to the plant. If the project goes well, the service could be expanded. “Drone transport is going to revolutionize logistics at SEAT, where it will reduce part delivery time by 80 percent,” says Christian Vollmer, Ph.D., SEAT’s vice president for production and logistics.

When a specific steering wheel is needed on the line, an order is sent to the logistics center, which is located nearby. There, the part is loaded into a carbon-fiber capsule that weighs 5.5 kilograms. Next, the capsule is firmly attached to the drone with an electromagnet. The steering wheel is now ready for airborne delivery from the launch pad.

Measuring 1.7 meters in diameter, the drone takes off and covers the 2 kilometer distance separating the logistics center and the assembly plant. The drone flies autonomously over the factory at a height of 95 meters and a speed of 40 kilometers per hour. It only takes 4 minutes from liftoff until the drone delivers the capsule at its destination. It takes just 15 minutes from when the order is sent to when the wheel is installed on the line.

“With this innovation, we are boosting Industry 4.0 and will be more efficient, agile and competitive, as well as much more sustainable,” says Vollmer. 

Delivery is emissions-free, since the drones run on batteries. In the past, a worker at the logistics center would have to run the part over in a gas-powered vehicle. 

The drones are also safe. The project is being carried out under the supervision of the Spanish Aviation Safety Agency.

Each drone has a large load capacity and is streamlined for maximum efficiency. “In addition to its six motors, we’ve equipped it with three GPS units, six batteries and three inertial measurement units, which are the inner workings of the drone,” says Toni Caballero, a drone pilot at the logistics center.

SEAT’s use of drones to deliver parts to the assembly line is just one example of how the automotive industry is pushing the envelope in applying new technologies to solve problems. The industry has always been an early adopter of the latest assembly technologies, such as robots, vision systems and computer-controlled fastening tools. Now, the industry is embracing Industry 4.0 and the Industrial Internet of Things. Here’s a look at how automotive assemblers are applying cutting-edge technologies in their manufacturing operations.

Augmented Reality Aids Assembly of EV Motors at Porsche

We’ve all done it: Installed fresh batteries in a device only to discover that it still doesn’t work. Often, the problem isn’t that the device is broken. It’s simply that one or more of the batteries were inadvertently installed with the wrong polarity. When a cathode is paired with an anode, no current will flow. 

This mistake is often made with AA batteries or button cells, but it can’t happen with a 9-volt block battery because there is only one way it can be connected. It’s designed to be error-proof.

A similar problem can arise when assemblers stack sheet metal laminations onto a shaft to make the rotor for an electric motor. For electromagnetic reasons, there are numerous variants with small geometric differences, which are not visible to the human eye. In this case, an error-proof design is not an option.

This was the challenge presented to manufacturing engineers at Porsche’s assembly plant in Zuffenhausen, Germany, where the company’s Taycan electric sports car is made. To solve the problem, engineers worked with Munich-based start-up Viscopic to develop an error-proofing system using augmented reality, machine vision and CAD models.

The system works like this: A high-resolution camera scans the parts to identify the subtle geometric differences between them. The vision system identifies the parts by comparing the images with the original CAD files for the parts. 

The system then forwards this information to a set of smart glasses worn by an assembler. Through augmented reality, the glasses instruct the assembler which parts to pick and how to assemble them. Assemblers can also use the glasses to access instruction and troubleshooting manuals that help them when performing their work without taking their eyes or hands off the product. 

The technology was created, tested and deployed in just 100 days.

“The digital solution that Viscopic developed is protecting against incorrect component installation,” says Tobias Schmack, technology developer for Porsche’s electric drive planning department. 

Porsche engineers are now working to expand the system to other assembly applications, such as process planning. Managers, developers and maintenance engineers no longer have to be in the same room to collaborate on a project or troubleshoot unexpected faults. The system can be used to plan a new line or plant or to virtually troubleshoot existing equipment for maintenance or repair.

Viscopic is one of several new companies to emerge from Startup Autobahn, a technology incubator in Sindelfingen, Germany. Porsche is one of several automotive companies that sponsor the incubator, including Daimler, Hyundai, Faurecia and ZF.

AI Supports QC at BMW

BMW’s assembly plant in Munich is increasingly using artificial intelligence (AI) and data analytics to improve quality and increase efficiency.

“It takes about 30 hours to manufacture a vehicle. During that time, each car generates massive amounts of data,” points out Robert Engelhorn, director of the Munich plant. “With the help of artificial intelligence and smart data analytics, we can use this data to manage and analyze our production intelligently. AI is helping us to streamline our manufacturing even further and ensure premium quality for every customer. It also saves our employees from having to do monotonous, repetitive tasks.”

One part of the plant that is already seeing benefits from AI is the press shop, which turns more than 30,000 sheet metal blanks a day into body parts for vehicles. Each blank is given a laser code at the start of production so the body part can be clearly identified throughout the manufacturing process. This code is picked up by BMW’s iQ Press system, which records material and process parameters, such as the thickness of the metal and oil layer, and the temperature and speed of the presses. These parameters are related to the quality of the parts produced.

Uploaded to the cloud in real time, the data is immediately available in its entirety for the production team to gain a clearer picture of the manufacturing process. This data is critical, since it eliminates the need for each body part to be checked in minute detail. It only picks out irregularities that require action.

AI also offers potential to identify recurring patterns in the data to support continuous improvement. As a result, the technology has helped increase hourly output from the press shop.

Another area where AI is being put to work is in the body shop. The shop’s numerous robots are equipped with more than 600 welding tongs. If these tongs ever need replacing unexpectedly, it costs significant time and money. Moreover, many of the robots are difficult to access, so dismantling and replacing their tongs can take hours.

Until recently, the condition of tongs has been monitored by eye, by a member of the production team. Now, maintenance specialists have equipped sensors to all the tongs to measure friction levels three times per shift and report any abnormalities. The data they produce is constantly evaluated by software, allowing potential machine failures to be predicted. 

“Because we have the sensors and collect their data in a cloud, we can now monitor round-the-clock whether any maintenance work is needed,” says Martin Hilt, the plant’s innovation and digitalization officer. “Now, we can plan any replacements better and potentially schedule them for a production break.”

AI is also being applied in the paint shop. Despite comprehensive cleansing systems, vehicle bodies can pick up dust particles as they make their way to the paint line. Though invisible to the human eye, these particles can affect the quality of the finish. Until recently, these potential defects went undiscovered until after the painting process, where they were revealed only by automatic surface inspection. These imperfections must be reworked. In some cases, the body might even have to be completely repainted.

Now, every paint shop system incorporates sensors that measure dust levels in the air and allow the quality of paintwork to be predicted. “We can now tell quickly if the environmental parameters are not quite right at some point, either within the paint shop or in one of the buffer areas. It takes a lot of data to do this, which we collect throughout the process, evaluate historically and analyze in real time,” explains Hilt.

Additional sensors measure dust levels on body parts at the beginning of the painting process, before and after they are cleaned by emu feather rollers. In the future, when dust levels are too high, car bodies will pass through the paint shop untreated and be sent for further cleaning.

AI is even being applied on the assembly line. The technology is used to evaluate images of a component and compare them in milliseconds with hundreds of other images from the same sequence. The system then identifies any deviations from the norm, such as parts that are absent or incorrectly positioned.

Automated image recognition allows the production team to identify whether the hazard warning triangle, wiper caps and door sills have all been correctly fitted to each car. Previously, small bubbles in the foil cover of a door sill were often enough to prevent the conventional camera gates from seeing if the logo on the door sill was correct. Now, an associate photographs each part in turn and can even use the mobile equipment to check parts that are more difficult to access. Distance, angle and light don’t effect these AI evaluations, which reveal whether everything is in place within fractions of a second.

The AI system is trained by associates. They start by photographing the component from various perspectives and marking potential deviations on the images. This allows them to develop an image database that can be used to build up a neural network for evaluating the images. Evaluations are carried out automatically; the machine decides by itself whether or not a part meets all the specifications.

5G Enables Flexibility at Audi

A small collaborative robot approaches an air bag, grips it gently and sets it precisely into a steering wheel assembly. It’s a process that might be repeated daily in the Audi factory of the future. For now, however, it’s happening only in the Production Lab at Audi’s assembly plant in Neckarsulm, Germany.

The future of cobots and other Industry 4.0 technologies on Audi assembly lines could hinge on the implementation of another new technology: 5G wireless communication.

5G is nothing new to anyone who owns a smartphone. Now, 5G is being applied to intra-factory communication, and it could transform the way that conveyors, fastening tools, robots and other equipment perform and interact on the plant floor. The technology will drive numerous Industry 4.0 initiatives, improving the automation of production processes and real-time monitoring of machinery.

The technology provides the ability to connect multiple devices at once and move more data faster than ever. As 5G is adopted, it will improve the ability of engineers to deploy AI, data analytics, digital twins and other smart factory tools. It will also enable millions of devices, such as actuators, cameras, motors and sensors, to be connected wirelessly with each other.

In Audi’s air bag assembly application, for example, the robot needs to stop instantly if, say, a human hand appears within its radius of action. That capability exists now, but it must be created with hard-wired safety circuits. 5G gives engineers flexibility. Control of the robot would be decentralized and wireless, yet data transfer would be just as efficient as with a wired connection.

The technology behind the 5G-networked robotic arm is being developed by Audi in cooperation with Swedish networking and telecom giant Ericsson. 

“We will be able to connect more automation applications with 5G that we have previously been able to connect with cables,” says Christopher Kolb, a member of the IIoT team at the Audi Production Lab. 

So far, the robots in the production facilities at Audi are connected with each other with cables, which limits their mobility. A 5G network would enable the machines to operate completely wirelessly and be deployed wherever they’re needed. 

“That has many practical benefits. On the one hand, there just aren’t any cables in the way anymore. That makes us more independent,” explains Kolb.

On the other hand, the production processes are becoming increasingly complex and must become more flexible. 5G technology would enable engineers to quickly reconfigure production lines as needs change.

5G provides a secure and stable connection in multiple ways: It offers a mobile communications spectrum that is available exclusively for industrial use, and it provides a “quality of services” mechanism—the possibility to prioritize various applications within the network.

Low latency—meaning a short sending and receiving time for wireless signals—makes it possible to wirelessly control smart factory systems in real-time.

This sort of communication is not possible with 4G (LTE) networks. 5G is said to be 10 times faster than 4G, but what really makes it unique is a fundamental change in the wireless technology. With 5G, the focus is placed—for the first time—on availability and low latency, which is necessary for production in a smart factory.

Kolb explains the difference using an example from daily life: “In the current network standards, it’s important that Netflix streaming works well, for example. But because the streaming services rely on data buffering, the fluctuating transfer rates found in LTE aren’t noticeable. But it won’t be until 5G that we have a stable data transfer rate without interruptions.”

Existing wireless technologies are not capable of meeting the future needs of a smart factory. An assembly plant, with its enormous, complex automation systems, simply cannot be compared with the wireless telephones and Wi-Fi-enabled televisions. The Industrial Internet of Things (IIoT) needs more. 

“We are seeing more and more networked devices, more and more mobile connections for which a cable connection is just no longer feasible. For these cases, we see 5G as a complement to Wi-Fi. The technology is so powerful that it will make many new use cases possible,” explains Kolb.

A good example would be mobile, autonomous transport systems. These currently communicate via Wi-Fi, but they still struggle with lost connections and errors. Cordless screwdrivers, scanners and other portable electronic devices could also benefit.