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The Pandemic is Pushing Automotive to Adopt Industry 4.0 Tech

EmilyNewton
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The COVID-19 pandemic had a devastating impact on various industries. Between temporary factory closures and the long-term inability of dealerships to sell products in person due to lockdowns, the auto sector did not emerge unscathed.

Analysts at McKinsey & Company anticipated profit declines of approximately $100 billion for the 20 leading original equipment manufacturers in the worldwide auto sector for 2020. That prediction would mean an approximately six-point decrease from the totals logged in 2018.

Many automobile brands saw the pandemic as an ideal reason to make good on intentions to create high-tech, connected factories. Here are some ways that focusing on Industry 4.0 in automotive could bring a return to profitability after an intensely challenging period.

Implementing Artificial Intelligence To Improve Quality Control

Manufacturers often use artificial intelligence (AI) to assist with inspections. For example, using computer-vision cameras equipped with machine learning algorithms could largely automate quality checks, reducing the number of people needed for the task. Minimizing the required staff members in an area became crucial during the pandemic to address new social distancing rules.

AI is also useful because it can detect flaws that even the most focused, detail-oriented assembly line inspectors may miss. At a German Audi factory, decision-makers wanted to improve the quality control measures for the welds on the 1,000 cars they produced daily. Each vehicle has an average of 5,000 welds, giving you an idea of the inspection processes’ scope.

Eighteen engineers use ultrasound probes to scrutinize the welds on one car daily. However, Audi relies on a machine-learning algorithm to check the other 999 vehicles. It got trained by comparing quality predictions with actual data gathered by the company’s quality control team.

The machine learning model also analyzes welding control data, weld configurations, metal types and other specifics. Employees can see the data on a dashboard and get alerts if the algorithm detects a defect. Additionally, this machine learning application highlights alternative equipment configurations to minimize or eliminate the flaws. Also, since it infers the results of each weld within 18 milliseconds, this technology is ideal for helping Audi keep output high as it attempts a pandemic recovery.

Companies outside the automotive sector — such as Amazon and Staples — invested in AI to reduce supply chain mistakes that could cause over or under-stocking. Some solutions entirely automate steps in picking and packing processes. Others keep digital records that prevent people from making data entry errors on paperwork for shipped goods. These examples show that quality control happens at all phases of production, and AI can improve it.

Using Robots To Keep Pace With Electric Car Interest

With much progress made in areas such as range capabilities and overall price, many consumers view electric cars as increasingly appealing options. According to one 2020 report, worldwide electric vehicle sales exceeded 2.1 million in 2019, exceeding the record year set in 2018. Moreover, the sales in 2019 represented a 40% year-on-year increase from 2018’s numbers.

People’s increasing desire for electric vehicles won’t be enough by itself for auto manufacturers to pull out of a pandemic slump. However, some automobile manufacturers will use smart technologies to raise production output, making the companies better able to meet their targets.

In one example, Volkswagen ordered 800 robots to supplement electric vehicle production plans. Decision-makers plan to install the machines at a Hannover, Germany factory. More specifically, the bots will assist with body construction tasks for the all-electric ID. Buzz van. Volkswagen will modernize the iconic campervan by making it electric-powered.

The size of Volkswagen’s order strongly suggests the brand is ready to go all-in with its efforts to apply Industry 4.0 in automotive. If those actions pay off, it may not be long before other companies start seeing the benefits robotics can bring.

Removing the Labor-Intensive Parts of Car Painting

A car’s exterior paint job is typically one of the things people notice most often about a vehicle. It can add beauty and style while protecting the surface from environmental damage. However, it’s equally or even more important to use specialized coatings in places that most people don’t typically see. For example, fluoropolymer coatings resist corrosion and tolerate under-hood temperatures, making them ideal for internal car parts.

Using automation to take care of painting and coating tasks on an automotive assembly line is an accessible and attractive option, particularly when brands use coatings on parts, plus offer their models in a wide assortment of colours. Companies sell numerous paint booth configurations with robots installed inside.

For example, one modular booth fits cars ranging from compact vehicles to medium-sized sport utility vehicles. It contains up to eight painting robots, plus another four that open the car’s doors. Other models sold elsewhere offer quick setup times or space-saving sizes. Manufacturers welcome both of those advantages when deciding whether to automate painting procedures.

Choosing to do it can result in numerous perks. For example, some robots utilize an innovative application approach that causes less waste. Others can adjust their speed and cycle times to accommodate when one or more robots go offline for maintenance.

Deploying Digital Twins During Development

Moving forward with Industry 4.0 in automotive might include using digital twins. They offer virtual versions of real-life assets, such as equipment or property. Manufacturers reduce risk by deploying changes in those test environments to see the effects before implementing them in factories.

Some car manufacturers also use digital twins when planning their new offerings. BMW recently began using that approach. Representatives believe it’ll increase speed and efficiency when determining production requirements.

The solution used at BMW offers real-time simulations. Perhaps most importantly for the post-pandemic era is the collaborative features that allow stakeholders to communicate and suggest changes. Then, engineers or other people heavily involved in car development can weigh in with thoughts, regardless of whether they’re in the same room.

Another benefit of the digital twin is that it features simulations for autonomous vehicle testing. Then, a development team can get relevant data that shows how the cars should perform in road tests. Digital twins won’t replace physical testing. However, it allows saving money and time by trying something in the digital realm first and making tweaks if needed.

Promoting Post-COVID-19 Profitability

These examples show why many decision-makers in the automotive industry decided that putting resources towards Industry 4.0 in automotive could help them recover. Advanced technologies alone won’t provide the outcomes that automakers want and need. However, they could prove crucial for bringing a company’s capabilities to new levels.

Additional note: RS and Zerynth offer exclusive kits and video workshops for engineers who are looking to learn about and deploy Edge Computing for IoT applications, more information can be found here on DesignSpark or at RS (219-6059) .

IoT training modules

Emily Newton is the Editor-in-Chief of Revolutionized Magazine. She has over three years experience writing articles for the tech and industrial sectors. Subscribe to the Revolutionized newsletter for more content from Emily at https://revolutionized.com/subscribe/

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