Automakers face challenges – and the industrial edge is crucial to solving them

This audio was created using Microsoft Azure Speech Services

A pair of trends in the automotive industry is driving the need for manufacturers to invest in technology that helps them reduce time to market, improve resiliency and support emerging applications such as artificial intelligence. For many automakers, the solution will be in the industrial edge and micro data centers that can support today’s requirements while providing scalability for the future.

The first of the two trends is the digital transformation of the automotive supply chain. Today you can go online and order a car from a dealer, sometimes even having it built to your specs. What’s more, auto manufacturers are streamlining communications with their own suppliers, with unprecedented visibility into and control over supply chains that help them deliver on the promise of just-in-time manufacturing.

The second trend is the emergence of connected autonomous vehicles. In 5 to 10 years, it’s likely we’ll have autonomous cars all around us, even in cities. These cars will require reliable connections to surrounding infrastructure, including street lights and other cars. What’s more, it’s likely we’ll see more technology involved in diagnosing and troubleshooting car problems. I can picture a car being scanned upon entering a repair shop and diagnostic data being immediately returned from a cloud-based service.

Digital transformation challenge and promise

The digital transformation of the supply chain means manufacturers have to reduce their time to market in order to compete effectively. That means investing in new IT infrastructure, such as to support research and development centers that are now dispersed throughout Europe, the U.S. and China. They also need data centers located closer to production facilities to collect data and help improve the quality of the finished product. That will support solutions such as artificial intelligence, which enables automakers to learn from data they collect during production and provide actionable advice to avoid production disruptions.

Visibility into production also helps improve efficiency. If you know exactly how many cars will be coming off the line next week, and therefore how many wheels you’ll need, you can adjust your supply chain such that those wheels arrive exactly when needed. You spend less capital on inventory, as well as managing and storing that inventory.

That has long been the promise of just-in-time manufacturing but now the tools exist to take it to the next level. Today, for example, we have machine-to-machine communications that enable an automaker’s production line to communicate directly with a supplier’s production line – freeing up human time for more strategic tasks.

Connected cars drive high demand for data

Autonomous, connected cars present even greater challenges. Consider the tests of self-driving cars that Volkswagen recently began in Hamburg, Germany. Each Golf vehicle has compute power equivalent to 15 laptops on board, along with “laser scanners, radars, ultrasonic sensors and cameras,” Volkswagen said.

The city is constructing a 9-kilometer digital test bed to support the effort, which apparently was crucial to Volkswagen’s decision to test there. “In order to make driving even safer and more comfortable in the future, vehicles not only have to become autonomous and more intelligent – cities must also provide a digital ecosystem that enables vehicles to communicate with traffic lights and traffic management systems as well as with one another,” said Axel Heinrich, Head of Volkswagen Group Research.

At Hamburg Airport, Volkswagen is also testing technology that enables cars to park themselves. Instead of driving around looking for a spot, drivers would instead reserve a spot in an airport lot, leave the car at the entrance, and the car would then find an available spot and park itself.

Advancing driverless vehicle technology is also the reason Audi, BMW and Mercedes-Benz spent $3.1 billion (€2.8) to acquire the digital map business from Nokia in 2015. Driverless cars need to understand the roads on which they travel, making mapping technology extremely important.

Mercedes is also investing in technology that enables cars to gather map data on their own, as they travel, to create highly precise maps. The vehicles then upload the map data to a central database, from where it can be shared back with other vehicles. As more vehicles travel the same routes, the maps continually become more accurate.

Industrial edge offers a solution

As you can imagine, making such visions a reality will require a lot of new, highly distributed compute power. While we’ll still need large, centralized data centers, such as to collect all that map data, we’ll also need a series of edge data centers closer to where data is generated and used – whether that’s on city streets or in a manufacturing plant.

Many of them will be micro data centers – small, self-enclosed facilities that can be located just about anywhere, indoors or out. Others may be somewhat larger facilities built with scalability in mind, to support the inevitable growth in these new applications.

In either case, there are modular, prefabricated data center solutions that fit a variety of these needs. No matter if the requirement is a small micro data center that sits outdoors to support traffic lights and communications, or a somewhat larger modular unit that will live inside an auto manufacturing plant – there are customizable solutions that provide a perfect fit.

To learn more, visit our Automotive solutions page. I’m confident you’ll find a solution that’s a fit for your automotive and digital transformation needs.

Tags: , , , , , ,