Smart Manufacturing for Automotive
RTInsights talks with Siemens about the need to convert to smart factories, the technologies that can help, and the benefits that automakers can derive from making the change.Read more
Virtual commissioning and digital twins can help automakers and their Tier 1 parts suppliers ensure that their human-robot collaboration projects achieve their desire objectives without posing a safety threat to the human operators.Read Now
Automakers can successfully address compressed development and launch timelines by embracing Agile methodologies, advanced digital tools, and flexible supply chain strategies.Read more
Smart Automotive Manufacturing Becomes a Necessity
Emerging from the pandemic, automotive manufacturers faced a number of challenges that persist today. Supply chain problems frequently shut down production lines. Customers are demanding the incorporation of sophisticated technologies to make their drive easier and more enjoyable. And governments are pushing for a transition to electric vehicles (EVs).
As a result, on the customer-facing side of the business, automotive manufacturers find they must constantly innovate to reduce costs, improve quality, and deliver value to customers (better fuel economy, advanced features, features-as-a-service, etc.). And on the operational side, they must find ways to adapt to changing conditions and become more responsive when changes occur.
Increasingly, the path to addressing all of these issues is to transition to a smart automotive manufacturing strategy. Elements of such a strategy typically include having a virtual representation of production lines, digital twins, that allow the manufacturer to virtually design, simulate, test, and commission products. Such an approach helps Identify issues virtually, avoiding the costly “design, build, test, break” iteration cycle that delays product launches and shuts down working production lines.
To accomplish this, an automotive manufacturer must establish intelligent manufacturing excellence. That typically includes:
- Moving to an environment with connected production lines.
- Making use of edge devices to collect data from every line.
- Migrating to a cloud environment, making use of data lakes to convert data into valuable insights into performance, energy use, raw material consumption, and more.
- Employing prescriptive insights to optimize line performance, do predictive maintenance, and eventually have the line manage itself.
Factors driving the need for smart automotive manufacturing
The automotive industry is in transition. For years, automotive manufacturers have had to meet ever-more stringent global regulations on fuel economy and emissions. That still remains the case. But now, there is growing pressure to make the move to EVs. Additionally, the cars themselves are becoming much more complex electronically to support new features and provide differentiation with competitors and among cars in the same model line.
Smart manufacturing can help. But to show how, it makes sense to look at the issues in a bit more detail to appreciate where and why smart automotive manufacturing is needed.
Perhaps the biggest reason smart manufacturing is needed is the inter-dependencies of modern automotive production. Every advance potentially introduces new issues.
For example, over the years, automotive manufacturers have improved the aerodynamic design of their vehicles. That not only helped improve fuel economy, but a side benefit is that it reduced wind noise from entering car cabins – especially at high speeds. No one would argue that this is a problem. But wait, it is. Reducing a major source of noise (the wind rushing past the car as it traveled down a highway) made previously masked lower decibel noises, such as clatter from the engine, now noticeable. As a result, manufacturers had to increase the use of sound-deadening materials like foam, rubber seals, paint sealers, and insulating spray foam in every nook and cranny of their vehicles.
Similarly, manufacturers are making use of new composite materials for structural elements to lighten an auto’s weight (and thus helping to improve fuel economy). Or a manufacturer might use a smaller engine running at higher speeds to save weight. The issue here is that engine temperatures can be much higher than before.
The impact: traditional lubricants used when a car was all-metal construction or engines ran at lower speeds do not perform well or break down. So many had to find new lubricants that worked equally well at higher temperatures or when different elements made of different materials (metal and composite) came together.
The main issue is that everything is interrelated. A slight change in a manufacturing process can have unforeseen implications. In the old days, manufacturers making a change would only find out about a problem once the auto was off the line and delivered to the customer. Smart manufacturing has the potential to address these and many other issues before a single car is built or a production line is created.
Supply chain issues dominate
Supply chain problems permeated the global economy after the pandemic. All types of parts and components were in short supply or took extraordinarily long times to arrive. The automotive manufacturing industry was highly impacted, like many other industries.
But one aspect that greatly impacted automotive was the shortage of processors and chips. Besides core supply chain issues, chip supplies are also affected by political and global conflicts. Why does this matter? It is estimated that the average modern car has between 1,400 and 1,500 semiconductor chips. And some cars can have as many as 3,000 chips. They are used in emissions systems, advanced driver assistance systems, and engine control units.
How much of an impact did this have on manufacturers? In 2021, the automotive industry lost more than $200 billion due to chip shortages. Eleven million fewer vehicles were produced. Manufacturing plants sat idle. Ford suspended operation at some plants to focus efforts on truck assembly, where the margins are better, according to an MIT Management, Sloan School article.
In 2022, many automakers decided to ship some of their most popular models without all the chips they were designed to include. For example, Automotive News reported that “Ford told its dealers it would start building Explorers, its best-selling SUV in the U.S., without the computer chips that enable rear-seat climate control, meaning that backseat passengers won’t be able to adjust the air conditioner and heat.” The company said it would install the missing chips once they become available.
The transition to EVs is leading to a different type of supply chain issue. Many auto manufacturers must now work with suppliers and vendors that are outside their previously normal supply chains.
The important point here is that managing the supply chain has radically changed over the last year due to the changing nature of cars. In the past, supply chain operations only needed to be concerned with raw materials and traditional automotive parts and components. Now, they must deal with the supply of chips, Lithium-Ion batteries, composite materials, and more.
Software is software
Modern cars offer many sophisticated features and functions, all of which are delivered via software. That includes advanced driver assistance systems, software-defined engine performance and handling, emission control systems, infotainment systems, and more.
Software is such an important of modern cars. When there is a problem, it can stop production. That was the case in early 2023. According to Ford Authority, “Production of the 2023 Ford Escape and 2023 Lincoln Corsair was on hold for several weeks due to a software bug impacting pre-production versions of both crossovers.”
So, automotive manufacturers are now in the software business. And like any software vendor, they must make software development, quality assurance, installation, and testing part of any end-to-end production.
How smart automotive manufacturing helps
Every aspect of the auto manufacturing business environment and the economics that drives it, from raw materials to supply and demand to the way a company deals with customers and partners, is changing.
Fortunately, many new technologies that can help are reaching a level of maturity to deal with these issues. Auto manufacturing is seeing increased use of smart sensors and Industrial Internet of Things (IIoT) devices. Plants now have ubiquitous connectivity, allowing the data from such devices to be collected, shared, and analyzed easily. Such data from legacy OT systems is increasingly being combined with enterprise IT data such as that found in ERP and CRM systems.
Many are applying advanced analytics (predictive analytics) to that collective data to spot issues in the making, improve maintenance efficiency, reduce downtime, and optimize supplies. More advanced organizations are making use of virtualization technologies and digital twins that allow for the melding of digital and physical worlds. A manufacturer bringing these technologies and elements together can realize many benefits.
Enter the world of smart manufacturing, which lets an auto manufacturer plan, optimize, and test operations virtually before physically commissioning anything.
Using a digital twin, a smart manufacturer can develop and try out work cells, manufacturing lines, and even an entire plant virtually. The data from this digital representation can be used to virtually identify obstacles, test solutions, and validate new scenarios.
Virtualizing operations using digital twins lets manufacturers design new production lines that are highly optimized from scratch. With virtual development, a manufacturer can practice the launch of a new product to ensure that costly last-minute changes do not delay a launch. Virtual manufacturing development allows a company to optimize production processes, pre- and post-launch; practice a product launch with virtual commissioning; share product design data with manufacturing early in the development cycle; and easily duplicate or relocate manufacturing lines anywhere in the world. Using such an approach, one company was able to realize a 30% reduction in development time and a 200% gain in productivity.
One issue that comes up when talking about smart manufacturing and virtual operations is how to bring legacy plants, production lines, and systems into the mix. Obviously, not every manufacturing line can be built from the ground up, which makes it challenging to implement cutting-edge technologies as they become available.
A smart manufacturing solution should provide a way for a manufacturer to update legacy equipment with sensors and edge devices to collect and analyze data for trends and prescriptive insights. Technologies like artificial intelligence (AI) and IIoT can connect work cells, assembly lines, and the entire plant to optimize production processes and resolve real-time issues.
Once legacy systems are brought into the fold, a manufacturer can make use of continuous communication loops that take insights from the generated data to take action. Such a feedback loop can be used to create manufacturing lines that can manage themselves to prevent errors, minimize downtime, and produce quality parts at launch and throughout the product lifecycle. A virtual environment like this offers the flexibility to quickly fine-tune and adjust production to match changing customer demands.
Feeding the data back into a digital twin of the product and manufacturing operations also improves the quality of future production. For example, a manufacturer might set up a feedback loop with products in the field and engineering so that they may see something unexpected and make changes based on how the driver is using different features.
Poised for a rapidly changing market
Companies in the automotive industry are pushing to develop the next generation of autonomous, electric, connected, and shared vehicles, which are becoming more and more software-defined. As noted above, they are thus facing new design challenges.
A main issue when trying to embrace customer-demanded changes is unpredictable supply chains with disruptions affecting materials, parts, and components availability, leading to unexpected downtime. There are also ongoing labor shortages, especially in some of the new technology areas.
Many manufacturers do not have an infrastructure in place to help. They rely on employees manually pulling together data that could help, or they use some mix of manual processes plus software. A smart manufacturing approach can help a company quickly evolve to adopt and implement more intelligent factory capabilities that meet the needs of today and address the challenges of tomorrow. Virtual technologies and digital twins can reduce the time to launch, improve quality, decrease warranty costs, eliminate recalls, and increase throughput to maximize efficiency.
A final word about smart automotive manufacturing
Modernizing manufacturing processes by connecting the data of all engineering disciplines to the knowledge of the shop floor is essential. It allows a manufacturer to monitor performance and predict operational issues in real time. By using sensors, smart devices, and IIoT technology, a plant will have a complete loop of manufacturing communication.
With that data and a digital twin, virtual replication of an entire production plan, a manufacturer can eliminate the iterative element of physical commissioning.
The bottom line: A smart manufacturing solution helps automotive manufacturers in many ways. It can help boost flexibility and allow a manufacturer to react faster to issues on the line. That can be accomplished by deploying edge technology that incorporates automation and self-correcting capabilities. It also reduces energy use and carbon footprint by leveraging advanced scheduling technologies.
Optimize automotive manufacturing processes with Siemens simulation software. Sign up for a free trial.