This industry group comprises establishments primarily engaged in (1) manufacturing complete automobiles, light duty motor vehicles, and heavy duty trucks (i.e., body and chassis or unibody) or (2) manufacturing motor vehicle chassis only.
A High Production Rate Solves Many Ills
A walk-through of ‘Production Line : Car Factory Simulation’, Elon Musk’s catch phrases, and how Industry 4.0 technologies are critical to manufacturing success. Recycling drives new business models in apparel and metals.
Cities and States Vie for Emerging Manufacturing
The emerging manufacturing sectors of semiconductors and electric vehicles are being heavily recruited by cities and states. The build out may permanently change supply lines.
Automotive Industry Clusters Across the World
Tesla bucks the trend of settling in traditional automotive regions. The supply chain crisis bottlenecks the Port of Los Angeles. Industry 5.0 takes focus in Europe.
🚙 Digital Twins: The Benefits and Challenges of Revolutionary Technology in Automotive Industries
With the advent of Industry 4.0, an increasing number of organizations have implemented digital twin technology to optimize their performance, enhance their educational initiatives, or facilitate advanced maintenance. Even the automotive industry has readily embraced this transformational technology. However, organizations must acknowledge that the adoption of digital twin technology may simultaneously expose them to potential cyber threats. Thus, securing digital twins within an organization should be viewed as an essential priority, on par with their implementation.
One of the challenges of implementing digital twin technology is maintaining consistency between the physical and virtual twins. In the case of a model corruption attack, it can be difficult to detect the issue, as developers may not notice the problem until they inspect the repository or run jobs on an infected digital twin. Running an infected digital twin not only leads to inconsistencies, but it can also compromise the CPS, as the malicious code sent by the infected twin may cause additional harm.
BMW Group Celebrates Opening the World's First Virtual Factory in NVIDIA Omniverse
DENSO reduce component simulation time by 80 percent using its Simcenter 3D and NX integrated process
A major challenge today is to improve productivity in the design and simulation of automotive parts. Even before the rise of software solutions, designers focused on geometry and turned to analysts to test and validate performance. However, simulation teams have always been much smaller than design teams – creating a bottleneck in the development process.
With Siemens tools, DENSO saw an opportunity to streamline the traditional workflow between design and engineering analysis, uniting the disciplines. This was particularly true for component design and analysis where simulation processes are more routine. DENSO’s goal was to reduce or eliminate the iteration with a new workflow.
🖨️🚙 How to Build a 3D Printing Setup in Automotive Industry
Depending on the performed task, whether it is developing an entirely new vehicle, making custom parts on demand, or renewing classic cars, 3D printing is a reliable solution in several ways. First, it facilitates the prototyping stages where each iteration can be flexibly redesigned when required and 3D printed for pre-production evaluation. This can relate to a variety of car components in the chassis, interior, or engine. Also, 3D printing is a cost-effective method employed when restoring or personalizing vehicles to specific needs. In car-tuning projects, 3D prints can substitute damaged and worn parts, as well as components which are too expensive or no longer available on the market. Therefore, 3D printed parts can be found in cars’ interior, dashboard, bodywork, and even under the hood.
AI Keeps Assembly Conveyor Rolling
The overhead conveyor is the backbone of the plant. It handles almost 1,250 cars per day during a three-shift operation. There is no back-up equipment, so failure is not an option. The conveyor’s parts are exposed to relatively high forces, causing them to wear in a relatively short time. Given that the conveyor is several meters above the floor, it is difficult to access for inspection.
ŠKODA engineers developed the Magic Eye to continuously monitor the condition of the conveyor’s moving parts without the need for maintenance personnel to climb ladders and physically do the job.
Six cameras are mounted on the conveyor frame at strategic locations to monitor the condition of various conveyor elements. Rapid assessment of each trolley’s condition is carried out as the conveyor is running. Images collected by the camera are transmitted via WiFi to a central database, where they are analyzed by artificial intelligence algorithms. The software detects wear by comparing each new image of the trolley with previously collected images. If an anomaly is detected, the software sends an alert to maintenance personnel, who can fix the trolley before it can create unexpected downtime.
How EVs Are Reshaping Labor Markets
The impact of EVs on auto manufacturing and supplier jobs is hard to assess. Electric vehicles require new or retooled factories, each requiring thousands of employees. How many will be new hires versus existing workers who are retrained is not clear. BMW, for example, claims it will not cut jobs in the transition to EVs, but it is likely that it will still reduce its workforce by both reskilling and attrition as other German automakers are contemplating. Further, given that EVs are said to need 30 percent less labor to produce than ICE vehicles, coupled with more automation that will be used for their manufacturing, many assembly line jobs may disappear.
High-end engineering and computer software and systems jobs at auto suppliers are also at risk, as auto manufacturers are moving to shift those jobs in-house. Former Volkswagen CEO Herbert Diess said, for example, that he expected by 2030 that software “will account for half of our development costs.” VW, like every other automaker, wants to control those costs.
The state of Michigan has been the epicenter of the U.S. auto industry for the past century with 11 assembly plants, 2,200 auto-research or design facilities, and 26 automaker and supplier headquarters. However, Michigan is finding the auto industry center of gravity moving away, as EV battery factories pop up across the Midwest “battery belt.” Automakers like to colocate EV factories near their battery factories, meaning the auto industry will not be the job creator in Michigan it once was.
How Toyota Factory Works with Zortrax 3D Printers
Toyota factories in Poland use a Zortrax M300 Plus 3D printer to make manufacturing jigs on demand. According to Toyota, investment in the 3D printing technology in automotive can pay for itself within one year. The key advantage of the Zortrax 3D printing technology, according to Toyota engineers are its agility.
“We have been using 3D printers for years now. They were already here when I came to work at Toyota four years ago.”, says Kondek. According to him, jigs that are 3D printed in automotive industry today used to be made by a separate tooling division equipped with CNC machines and other subtractive manufacturing tools. Fabrication of more demanding designs were simply outsourced to external subcontractors.
“Obviously, using such tools severely limited what we could do design-wise. Every time we thought about a new jig, we had to think twice about whether it could be fabricated or not. 3D printing in automotive sector solve this problem.”, explains Kondek. He adds that currently over 95% of the 3D printed jigs made at Toyota factory are manufactured in the LPD technology. The rest is 3D printed in other 3D printing technologies.
Digitise and dematerialise: Divergent CEO Kevin Czinger on supplying automotive structures to the world's biggest brands
The manufacture of lithium-ion phosphate battery cells at Coda’s facility in China relies heavily on coal-fired power. And because of that, ‘well over’ 200 kilogrammes (kg) of Co2 per kilowatt hour (kWh) is being produced in battery manufacture. At this time, kg of Co2 per kWh is the most important metric on Czinger’s mind and the cogs whirring in his head only intensify as he does the workings out to reveal that these batteries and EVs aren’t having enough impact.
Post Coda, Czinger educated himself on lifecycle assessments, figuring only a holistic approach would return the energy emission reduction that is required in an era of climate emergency. He also came to realise that the way automotive structures are manufactured, and the costs required to do so, need optimising – particularly as EVs, hybrid cars and internal combustion engine vehicles (and all the tooling and fixturing to come with them) continue to emerge. “The amortisation period, the competition, the driving down of values, you’re looking and saying, ‘this is environmentally and economically broken,’” Czinger says.
Czinger and his team developed the Divergent Adaptive Production System (DAPS) to ‘digitise and dematerialise’ automotive production and provide the technical competency for the company, in time, to become a Tier One supplier to the automotive industry. What Divergent is willing to talk about, however, is how its DAPS workflow works. Its engineers start by understanding the static stiffness targets of a structure, then the typical load cases it will be exposed to, then what its boundary conditions are, then its crash requirements, durability requirements and dynamic stiffness response requirements. This information is the input for the Divergent design algorithm, which is where the company enters the concept phase. Here, Divergent gives the OEM ‘optionality’ to, for example, reduce stiffness in a certain area of the structure to reduce mass. After the concept phase comes the detailed design phase, and after that, it’s time to print the part.
Who Makes America's Semi-Trucks
Inside Rivian and Ford’s Plants, as They Race to Build EVs Faster
Conveyor-Less Micro Factories for Urban Car Production
The automobile manufacturing value chain consists of a press shop, body shop, paint shop and assembly. The assembly process is different from other processes in terms of automation. The level of automation in press shops, body shops and paint shops is usually very high. Many are nearly 100 percent automated. However, final assembly is difficult to automate due to the complexity of the tasks and diversity of the parts.
One way to achieve mass individualization while maintaining various automation levels is to decouple final assembly from the value chain. The press shop, body shop and paint shop would continue as mass production centers in central locations, while final assembly would be carried out in separate micro factories located in urban areas. The assembly process does not need to be physically located with the other manufacturing processes. Instead, it can be moved to an urban area where the labor supply is elastic. Low-volume, high-mix production can be realized with this model.
An urban automotive assembly plant should be designed for maximum flexibility, minimal capital investment and asynchronous production. That points away conveyors and favors autonomous transport technologies. Two options are available: autonomous mobile robots (AMR) and VaaC. AMRs are vehicles that are equipped with on-board sensors to autonomously move vehicles or materials along predefined paths without the need for magnetic tapes on the floor. In VaaC, the EV guides itself through the assembly process. A sensor skid, temporarily attached under the EV, guides the EV based on local sensing and communication with a high-level fleet management system. The skid is designed to be easily removed at the end of the assembly. The skid body has a set of pins that temporarily engage with locating holes in the underbody. The skid is equipped with numerous sensors that detect objects around the EV.
Inside Ather's new manufacturing facility focused on efficiency
The production plant is expected to provide a huge fillip for Ather in terms of meeting the demand and reducing wait times. But more than that, it serves as a model for Ather Energy’s future plants as it incorporates automation and IoT capabilities. Addressing a room full of reporters, Ather’s CTO and Co-founder Swapnil Jain said the new facility is 100% IoT-based, whereas Gen 2, Ather’s first big plant—also in Hosur—only uses IoT in its battery line.
Comau Leverages Advanced Automation to Deliver Faster Time-to-Market and Enhanced Flexibility for the New Alfa Romeo Tonale
As part of Comau’s lean manufacturing approach, the automated and semi-automated production solution is based on the proprietary ComauFlex technology, nicknamed Butterfly due to its impressive agility and use of suspended robots. This set-up allows Alfa Romeo to change or modify a specific vehicle model by adjusting the robot tooling, not the arrangement of the robots themselves. In addition to protecting the scalability of the customer’s initial investment, the solution is designed to enable the introduction of new models in the future for a fraction of the initial expenditure. Indeed, the entire system features 468 welding robots, 148 of which are completely new and 320 taken from existing lines. Comau utilized advanced simulation tools during the entire development period, guaranteeing the best quality product and throughput.
LG, Altair build AI-powered validation platform for automotive parts
LG Electronics Inc., an industry frontrunner in applying artificial intelligence to home appliances, said on Wednesday it has joined forces with Altair Engineering Inc., a US tech firm, in developing an AI-powered validation platform for automotive parts.
Integrating AI technology into the vehicle component development process will provide LG’s clients with more reliable and high-quality solutions for products, including infotainment systems, LG said. The South Korean electronics company said the new platform leverages a machine learning algorithm to accurately predict and measure product performance from an early stage of the design validation process.
Market Dynamics, Technologies Drive Automotive Design
The ground underneath is constantly shifting: Supply chain constraints, software defined architectures, functional safety requirements, and the changing dynamics among original equipment manufacturers (OEMs), tier 1 suppliers, and semiconductor companies are altering the landscape of automotive electronics. This dynamic environment was the subject of discussion in a recent panel hosted by ProteanTecs, and, judging from that talk, “changing” may be an understatement.
“For each and every little functionality, there’s a single ECU,” that’s about to change drastically as OEMs move to a domain-based architecture with high-performance computers. Sustainability is also going to be viewed through a new lens because of data, as the car now has so many sources that will inform optimal charging times and where charging stations are placed.
Yorii Automobile Plant, Saitama Factory, Honda Motor Co., Ltd.
AI Driven Vision Inspection Automation for Forged Connecting Rods
2022 Assembly Plant of the Year: Continuous Improvement Culture Thrives at Brose
The complex world inside a car door or under a seat is Brose’s domain. The $7 billion Tier One supplier does business with just about every automaker in the world. Customers include legacy firms ranging from Audi to Volkswagen, in addition to startup electric vehicle manufacturers such as Lucid and Rivian. One of Brose Group’s most important facilities is its 18-year-old assembly plant in Vance, AL, which generates more than $400 million in annual revenue. The 302,000-square-foot factory is strategically located between Birmingham and Tuscaloosa, near Daimler’s sprawling Mercedes-Benz assembly plant that produces sport utility vehicles.
“During the last three years, we have conducted numerous process improvements and implemented procedures to reduce our plant costs and improve our overall quality,” says Jim Barbaretta, plant manager. “We have improved productivity and production costs by 25 percent over the last four years. “We also improved our productivity by 14 percent and have achieved an average continuous improvement savings of more than $2 million annually,” adds Barbaretta.
How Volkswagen and Google Cloud are using machine learning to design more energy-efficient cars
Volkswagen strives to design beautiful, performant, and energy efficient vehicles. This entails an iterative process where designers go through many design drafts, evaluating each, integrating the feedback, and refining. For example, a vehicle’s drag coefficient—its resistance to air—is one of the most important factors of energy efficiency. Thus, getting estimates of the drag coefficient for several designs helps the designers experiment and converge toward more energy-efficient solutions. The cheaper and faster this feedback loop is, the more it enables the designers.
This joint research effort between Volkswagen and Google has produced promising results with the help of the Vertex AI platform. In this first milestone, the team was able to successfully bring recent AI research results a step closer to practical application for car design. This first iteration of the algorithm can produce a drag coefficient estimate with an average error of just 4%, within a second. An average error of 4%, while not quite as accurate as a physical wind tunnel test, can be used to narrow a large selection of design candidates to a small shortlist. And given how quickly the estimates appear, we have made a substantial improvement on the existing methods that take days or weeks. With the algorithm that we have developed, designers can run more efficiency tests, submit more candidates, and iterate towards richer, more effective designs in just a small fraction of the time previously required.
How to Speed Up EV Cable Assembly
High-voltage connectors used in EV harness applications have many components that require precise assembly. Automation can improve productivity, quality and throughput when stripping and crimping cables. High-voltage connectors require several production steps that must be performed in a specific sequence. While most engineers want to automate every process, the cost of a fully automatic system cannot always be justified. Some process steps are more challenging and require more precision. For instance, removing the foil layer or cutting the shield is critical, because connector performance or safety may be affected significantly. In addition, some process steps are required for almost all connectors and cable types, while other steps are required only for certain connectors.
To achieve precision and throughput, manufacturers must invest in automation. It can provide not only high precision, but complete flexibility so that processing requirements can change in the future. It is important that systems can be expanded so they can grow and adapt as demand changes. Different connectors often have very different individual process steps because of their unique functions and constructions. However, there are some basic steps that apply to almost all of them. These steps pertain to properly stripping the cable and loading the ferrules.
Stories From The Field: Automotive Plant Tour
Throughout my years I have been in many manufacturing facilities. Oddly enough, I have seen nearly every part of a passenger car manufactured and then fully assembled. The amount of compressed air applications in automotive supplier and manufacturing facilities are tremendous. Here are some stories from just a few we have encountered over the years, and all of them can be found in our Application Database.
BMWs to Drive Themselves During Production
BMW Group project manager Sascha Andree explained: “Automated driving within the plant is fundamentally different from autonomous driving for customers. It doesn’t use sensors in the vehicle. In fact, the car itself is more or less blind and the sensors for maneuvering them are integrated along the route through the plant.”
Initially, the vehicles will only move through the assembly area and then to a parking area, ready for their onward journey by train or truck. But in reality, it is possible to use the tech as soon as the cars are capable of driving independently in the production process.
Smart Manufacturing at Audi
Some 5,300 spot welds are required to join the parts that make up the body of an Audi A6. Until recently, production staff used ultrasound to manually monitor the quality of spot welds based on random sampling. Now, however, engineers are testing a smarter way of determining weld quality. They are using AI software to detect quality anomalies automatically in real time. The robots collect data on current flow and voltage on every weld. An AI algorithm continuously checks that those values fall within predetermined standards. Engineers monitor the weld data on a dashboard. If a fault is detected, they can then perform manual checks.
Industry 4.0 at Škoda
Over the past few years, Škoda has invested millions of dollars in state-of-the-art assembly technologies to increase productivity, improve worker safety, and decrease the company’s environmental footprint. As part of an overall Industry 4.0 strategy, the company has implemented additive manufacturing, artificial intelligence, augmented reality, autonomous mobile robots and other technology.
Adding a new workstation to an assembly line requires careful planning—especially if regular operations are expected to continue at the same time. When engineers at Škoda’s assembly plant in Vrchlabí, Czech Republic, wanted to integrate a new robot into a gearbox production line, the project was fully operational in just three weeks—thanks to digital twin technology. Within a cycle time of less than 30 seconds, the new workstation installs bearings into each gearbox. Robots install the bearings to meet the precision requirements of the application.
Optikon uses mathematical combinatorial analysis methods to find various solutions to what is known as the “knapsack problem.” It addresses the question of how certain objects can be optimally fitted into a limited space. While the classic knapsack problem only takes into account the weight and value of the items to be packed, Optikon also considers floor space, the volume of the item, and when the goods have to be shipped.
The Race To Zero Defects In Auto ICs
While semiconductor test engineers are making great strides on isolating fab-generated defects, assembly engineers are quietly focusing attention on improving inspection and processing of equipment data to catch latent defects. This is a big deal for automotive electronics. According to a BMW presentation at the 2017 Automotive Electronics Council reliability workshop, most semiconductor devices fail within the car’s warranty period.
The carmaker noted that 22% of warranty costs are due to electronics and electrical control units. Of those failed parts, BMW said 77% of the failures are semiconductor devices, and 23% of the parts are isolated to active and passive components. Of those semiconductor failures, 48% were due to systematic fails, 24% to test coverage, 15% to random failures, and 6% were retested and did not fail the second time. The failure pareto was also broken down to 41% final test, 24% front-end processing, 22% design, and 12% assembly.
For assembly facilities to deliver 10 dppb quality to their automotive customers, they need to learn from customer returns. This requires investment in assembly equipment data collection and traceability. Latent defects that become activated during the warranty period yet pass electrical test necessitates 100% inspection to screen for these failures. Yet all this investment in more inspection and data collection places a financial strain on traditionally inexpensive assembly operations. There is constructive tension between assembly facilities and their automotive customers, as they are both cost-sensitive. Still, somehow this pathway to 10 dppb will be funded.
Engine block assembly line for Scania's trucks of tomorrow
BMW Creates Fully Automated Production Lines for 3D Printed Car Parts
By utilizing systems made up of laser powder bed fusion (LPBF) platforms, combined with AI and robotics, that it has developed, the IDAM consortium can print 50,000 series parts a year, as well as 10,000 new and individual parts. Opened in 2020, BMW’s campus at Oberschleißheim has 50 3D printers for both metal and plastics. Aside from investing in a variety of 3D printing startups, including Desktop Metal and Xometry, the company also employs HP MultiJet Fusion (MJF) and EOS machines, among other brands.
Towards a more circular production in Scania Oskarshamn
Great achievements towards a more circular production are made at Scania’s cab factory In Oskarshamn, Sweden, since 2019. The production is fossil free since 2020, more material is recycled, and the energy consumption has decreased with several thousand MWh.
Virtual Factory Tour―Automobile Production Plant
Audi Production Factory Tour 2022
Ford rolls out autonomous robot-operated 3D printers in vehicle production
Leveraging an in-house-developed interface, Ford has managed to get the KUKA-built bot to ‘speak the same language’ as its other systems, and operate them without human interaction. So far, the firm’s patent-pending approach has been deployed to 3D print custom parts for the Mustang Shelby GT500 sports car, but it could yet yield efficiency savings across its production workflow.
“This new process has the ability to change the way we use robotics in our manufacturing facilities,” said Jason Ryska, Ford’s Director of Global Manufacturing Technology Development. “Not only does it enable Ford to scale its 3D printer operations, it extends into other aspects of our manufacturing processes – this technology will allow us to simplify equipment and be even more flexible on the assembly line.”
At present, the company is utilizing its setup to make low-volume, custom parts such as a brake line bracket for the Performance Package-equipped version of its Mustang Shelby GT500. Moving forwards though, Ford believes its program could be applied to make other robots in its production line more efficient as well, and it has filed several patents, not just on its interface, but the positioning of its KUKA bot.
UVeye - Vehicle Inspection for the 21st Century
Hyundai Motor’s Alabama plant: World’s second most productive
At Hyundai’s Alabama plant, it took 24.02 hours to fully assemble a vehicle, more productive than 28.71 hours at General Motors’ Fairfax plant, 29.99 hours at GM’s Lansing Delta assembly plant, and 31.92 hours at Toyota Motor’s Georgetown plant, according to the consulting firm.
Hyundai’s US plant is also more productive than its main Korean manufacturing plant in Ulsan in terms of units produced per hour. Hyundai Motor Manufacturing Alabama LLC (HMMA) produces 68 cars an hour, compared with 45 cars at Hyundai’s Ulsan plant, according to the auto industry.
Why Tesla Soared as Other Automakers Struggled to Make Cars
GM and Ford closed one factory after another — sometimes for months on end — because of a shortage of computer chips, leaving dealer lots bare and sending car prices zooming. Yet Tesla racked up record sales quarter after quarter and ended the year having sold nearly twice as many vehicles as it did in 2020 unhindered by an industrywide crisis.
“Tesla, born in Silicon Valley, never outsourced their software — they write their own code,” said Morris Cohen, a professor emeritus at the Wharton School of the University of Pennsylvania who specializes in manufacturing and logistics. “They rewrote the software so they could replace chips in short supply with chips not in short supply. The other carmakers were not able to do that.”
How Elon Musk’s Software Focus Helped Tesla Navigate Chip Shortage
Tesla has been able to keep production lines running in part by leaning on in-house software engineering expertise that has made it more adept than many rival auto makers at adjusting to a global shortfall of semiconductors, industry executives and consultants said. Chips are used in everything from controlling an electric motor to charging a phone.
Gigafactories Help Battery Manufacturers Meet Growing EV Demand
Independent cart conveyance systems rely on linear motor technology. Linear synchronous motors (LSM) use electromagnetic force to index carriers more quickly and efficiently than traditional conveyance systems. Linear motors use components that don’t wear or come into contact with one another, which drastically reduces maintenance needs and decreases downtime.
The system’s capabilities range from individual cell sorting to full battery module and pack assembly, while also performing required testing. The machine incorporates linear servo motors that position loads in precisely the correct direction at high speeds. And changeovers simply involve selecting the correct mode from the operator interface.
Free from the constraints of a traditional conveyor, this system can improve your operations by helping you create faster, more flexible battery lines using independent, programmable movers. Time to market is improved by new LSM technology thanks to built-in full-line simulation capabilities that include an integrated track-and-trace system that eliminates the need for external sensing.
The Role Of Blockchain In The Development Of The EV Industry
Blockchain-based applications come with a track-and-trace feature. This feature allows EV manufacturers to keep tabs on the materials as they are brought for production. Certain types of materials, such as wolframite and cobalt, are sourced from hard-to-trace developed countries. Such materials change hands several times before they’re brought to factories for processing and production. Therefore, blockchain is useful to accurately store the provenance-related details of raw materials so that the manipulation of such materials coming from such sources can be prevented. Using blockchain for EV production also enables manufacturers to monitor any diversions while materials are being brought into factories for EV production. Blockchain-enabled tracking allows EV manufacturers to react to vehicle recalls in a cost-effective way. If there are any material issues that require vehicles to be recalled, the manufacturers can call back only those EVs that were built using parts or materials from the partner who supplied them. This makes your supply chain much leaner and cost-effective. A leaner supply chain results in lower production costs for EV makers.
Stellantis Goes All-In With its Software Strategy
A transformative strategy is needed to manage software requirements for 14 distinct brands, perhaps the largest number of diverse brands of any auto OEM—across price range and vehicle segments ranging from consumer to commercial vehicles. This software complexity provides major cost savings and revenue opportunities after the software platform transformation is completed. The risk is significant development cost over the next four to five years.
Stellantis estimates that 80 percent of software platforms can be shared among brands, with 20 percent requiring brand-specific software—mostly related to user interfaces. Stellantis is clearly aiming to own a significant portion of its software value chain for all of its brands. Nearly all auto OEMs are on this path, adding software expertise to their core competencies.
A key software goal is decoupling software from hardware platforms. Hardware-software decoupling has become standard procedure due to its many advantages. The latest advantage is the potential to swap out chips when supply chains are disrupted.
The Big Automotive Semiconductor Problem
BMW uses Nvidia’s Omniverse to build state-of-the-art factories
BMW has standardized on a new technology unveiled by Nvidia, the Omniverse, to simulate every aspect of its manufacturing operations, in an effort to push the envelope on smart manufacturing. BMW has done this down to work order instructions for factory workers from 31 factories in its production network, reducing production planning time by 30%, the company said.
Product customizations dominate BMW’s product sales and production. They’re currently producing 2.5 million vehicles per year, and 99% of them are custom. BMW says that each production line can be quickly configured to produce any one of ten different cars, each with up to 100 options or more across ten models, giving customers up to 2,100 ways to configure a BMW. In addition, Nvidia Omniverse gives BMW the flexibility to reconfigure its factories quickly to accommodate new big model launches.
BMW succeeds with its product customization strategy because each system essential to production is synchronized on the Nvidia Omniverse platform. As a result, every step in customizing a given model reflects customer requirements and also be shared in real-time with each production team. In addition, BMW says real-time production monitoring data is used for benchmarking digital twin performance. With the digital twins of an entire factory, BMW engineers can quickly identify where and how each specific models’ production sequence can be improved. An example is how BMW uses digital humans and simulation to test new workflows for worker ergonomics and efficiency, training digital humans with data from real associates. They’re also doing the same with the robotics they have in place across plant floors today. Combining real-time production and process monitoring data with simulated results helps BMW’s engineers quickly identify areas for improvement, so quality, cost, and production efficiency goals keep getting achieved.
Optimized quality control data keep the automotive supply chain flowing
“What the FARO ScanArm allowed me to do was protect my company by proving to the customer that the issue started with their engineering print. With this particular issue, I provided a full layout to the customer with all of the profile call outs from the engineering drawing that showed where the issues were.”
Without FARO solutions and the more accurate data they provided, Taylor Metal Products might have been held financially responsible for these “no build conditions.” Thanks to the fact that the ScanArm was being used, however, Jason was able to “quickly address and correct these severe issues.”
“CAD is your perfect master; it can’t be refuted,” Jason explained. “The great thing about the FARO scans is that I can use color maps. One of the overseas manufacturers is really big about pulling those color maps because with the nature of our product, you’re taking a piece of metal and you’re bending it in different directions. The natural tendency of steel is to conform back to its original state. So, the stamping world is not like the machining world where you’re dealing with really tight tolerances, cutting and threading a hole, or boring out a hole. In the stamping world, you’re pushing metal. So that’s where the scans really come into play. The color maps show any deviation from CAD throughout the entire part. You can scan a profile with a fixed CMM, but it is a linear format, not 3D — and the CMM has to be programed to do this. With the FARO ScanArm after the CAD is locked in, it’s just one click to produce the color map. And the Japanese automotive manufacturers are big on using this technology.”
2021 Assembly Plant of the Year: GKN Drives Transformation With New Culture, Processes and Tools
All-wheel drive (AWD) technology has taken the automotive world by storm in recent years, because of its ability to effectively transfer power to the ground. Today, many sport utility vehicles use AWD for better acceleration, performance, safety and traction in all kinds of driving conditions. GKN’s state-of-the-art ePowertrain assembly plant in Newton, NC, supplies AWD systems to BMW, Ford, General Motors and Stellantis facilities in North America and internationally. The 505,000-square-foot facility operates multiple assembly lines that mass-produce more than 1.5 million units annually.
“Areas of improvement include a first-time-through tracking dashboard tailored to each individual line and shift that tracks each individual failure mode,” says Tim Nash, director of manufacturing engineering. “We use this tool to monitor improvements and progress on a daily basis.
“Overhaul of process control limits has been one of our biggest achievements,” claims Nash. “By setting tighter limits for assembly operations such as pressing and screwdriving, we are able to detect and reject defective units in station vs. a downstream test operation. This saves both time and scrap related to further assembly of the defective unit.”
“When we started on our turnaround journey, our not-right-first-time rate was about 26 percent,” adds Smith. “Today, it averages around 6 percent. A few years ago, cost of non-quality was roughly $23 million annually vs. less than $3 million today.”
Europe’s new €1.6bn chip plant needs only 10 workers on factory floor
A 60,000 square meter facility built specializing in power semiconductors seeks ease bottlenecks for major automotive clients. The increase in automation solutions has made localized European production of semiconductors possible. By reducing comparable personnel needed to run the facility from 150 to 10 makes the factory cost competitive with factories in Asia.
Can a Green-Economy Boom Town Be Built to Last?
The epicenter of that boom is an electric-vehicle maker named Rivian, which brought in Mr. Mosier’s company and others in the Normal, Ill., area to work on the city’s costliest construction project in decades: a massive auto plant.
As it prepares to deliver its first electric pickup trucks and sport utility vehicles this year, Rivian has spent around $1.5 billion renovating and expanding a factory once owned by Mitsubishi. On a typical day the 3.3-million-square-foot plant hosts several hundred construction workers alongside more than 2,500 workers employed by the company, which expects to eventually double its local head count.
This Tesla co-founder has a plan to recycle your EV batteries
Circular Car Factories
The next big shift will be an environmentally friendly movement dubbed the “circular auto factory.” According to some experts, the circular cars initiative will reshape the auto industry during the next two decades, as OEMs and suppliers attempt to achieve net-zero carbon emissions across the entire vehicle life cycle.
The term “circular car” refers to a theoretical vehicle that has efficiently maximized its use of aluminum, carbon-fiber composites, glass, fabric, rubber, steel, thermoplastics and other materials. Ideally, it would produce zero material waste and zero pollution during manufacture, utilization and disposal.
One of the key elements of a circular car factory is a closed-loop recycling program where disassembly lines are housed in the same facility as traditional final assembly lines. All vehicle components and materials are remanufactured, reused and recycled at the end of life.
Applying Artificial Intelligence to Paint Shop Robots
Häcker says that factories in the automotive industry have “enormous amounts of latent data about manufacturing processes, raw materials, and products. The key to leveraging these data assets is connectivity with the right interface at the control level to get at the information provided by robots, ovens, cathodic electrocoating systems or conveyor technology. Operators in existing plants are often constrained because most of their systems do not have connectivity and the right interface for data acquisition.”
Industry 4.0 and the Automotive Industry
“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.
Accelerating the Design of Automotive Catalyst Products Using Machine Learning
The design of catalyst products to reduce harmful emissions is currently an intensive process of expert-driven discovery, taking several years to develop a product. Machine learning can accelerate this timescale, leveraging historic experimental data from related products to guide which new formulations and experiments will enable a project to most directly reach its targets. We used machine learning to accurately model 16 key performance targets for catalyst products, enabling detailed understanding of the factors governing catalyst performance and realistic suggestions of future experiments to rapidly develop more effective products. The proposed formulations are currently undergoing experimental validation.
Why Tesla Needed The Giga Press
BMW-led study highlights need for AI-based AM part identification
With time-to-market in the automotive industry steadily decreasing, demand for prototyping components is higher than before and the vision of large-scale production, delivering just-in-time to assembly lines, is emerging. This is not only a question of increasing output quantity and production speed but also of economic viability. The process chain of current available AM technologies still includes a high amount of labor intensive work and process steps, which lead to a high proportion of personnel costs and decreased product throughput. Also, these operations lead to bottlenecks and downtimes in the overall process chain.
Nissan Accelerates Assembly Line with 3D Printing Solution
Previously Nissan outsourced all of its prototypes and jigs to mechanical suppliers who used traditional manufacturing methods, such as CNC and drilling. Although the quality of the finished product was good, the lead times were long and inflexible and the costs were high. Even simple tools could cost in the region of 400€ for machining. By printing some of these parts in-house with 3D printers, Nissan has cut the time of designing, refining and producing parts from one week to just one day and slashed costs by 95%.
Eric Pallarés, chief technical officer at BCN3D, adds: “The automotive industry is probably the best example of scaling up a complex product with the demands of meeting highest quality standards. It’s fascinating to see how the assembly process of a car – where many individual parts are put together in an assembly line – relies on FFF printed parts at virtually every stage. Having assembled thousands of cars, Nissan has found that using BCN3D 3D printing technology to make jigs and fixtures for complex assembly operations delivers consistently high quality components at a reduced time and lower cost”.
Circular Economy 3D Printing: Opportunities to Improve Sustainability in AM
Within the 3D printing sector alone, there are various initiatives currently underway to develop closed-loop manufacturing processes that reuse and repurpose waste materials. Within the automotive sector, Groupe Renault is creating a facility entirely dedicated to sustainable automotive production through recycling and retrofitting vehicles using 3D printing, while Ford and HP have teamed up to recycle 3D printing waste into end-use automotive parts.
One notable project that is addressing circular economy 3D printing is BARBARA (Biopolymers with Advanced functionalities foR Building and Automotive parts processed through Additive Manufacturing), a Horizon 2020 project that brought together 11 partners from across Europe to produce bio-based materials from food waste suitable for 3D printing prototypes in the automotive and construction sectors.
John Deere and Audi Apply Intel’s AI Technology
Identifying defects in welds is a common quality control process in manufacturing. To make these inspections more accurate, John Deere is applying computer vision, coupled with Intel’s AI technology, to automatically spot common defects in the automated welding process used in its manufacturing facilities.
At Audi, automated welding applications range from spot welding to riveting. The widespread automation in Audi factories is part of the company’s goal of creating Industrie 4.0-level smart factories. A key aspect of this goal involves Audi’s recognition that creating customized hardware and software to handle individual use cases is not preferrable. Instead, the company focuses on developing scalable and flexible platforms that allow them to more broadly apply advanced digital capabilities such as data analytics, machine learning, and edge computing.
Ford's Ever-Smarter Robots Are Speeding Up the Assembly Line
At a Ford Transmission Plant in Livonia, Michigan, the station where robots help assemble torque converters now includes a system that uses AI to learn from previous attempts how to wiggle the pieces into place most efficiently. Inside a large safety cage, robot arms wheel around grasping circular pieces of metal, each about the diameter of a dinner plate, from a conveyor and slot them together.
The technology allows this part of the assembly line to run 15 percent faster, a significant improvement in automotive manufacturing where thin profit margins depend heavily on manufacturing efficiencies.
How Delphi Technologies Reduced Scrap and Improved Transparency with Smart Work Station
In Delphi’s Torreon Plant, they manufacture sensors with specific elements that detect specific changes or issues in how the engine is working. Due to untracked quality issues and incorrect parameters, they were producing a higher than acceptable volume of scrap, from which it was not possible to recover materials. While these quality issues did not impact customers, they led to increased materials costs. They believed they could reduce the volume of scrap by tracking and addressing key elements of the production process, but did not have a software tool that supported that level of granularity. They selected Smart Work Station to address the problem.
Smart Work Station offers Delphi the flexibility to document key elements of the process on the floor, including the recording of personalized data to correlate with performance and quality metrics. Using checklists and digital work instructions, they have been able to ensure consistent execution of processes and measure the results of those efforts.
How Tesla Builds Batteries So Fast
Missing Chips Snarl Car Production at Factories Worldwide
Semiconductor shortages may persist throughout the first half as chipmakers adjust their operations, researcher IHS Market predicted on Dec. 23. Automakers will start to see component supply gradually ease in the next two to three months, China Passenger Car Association, which groups the country’s largest carmakers, said Monday.
Chipmakers favor consumer-electronics customers because their orders are larger than those of automakers – the annual smartphone market alone is more than 1 billion devices, compared with fewer than 100 million cars. Automaking is also a lower-margin business, leaving manufacturers unwilling to bid up chip prices as they avoid risking their profitability.
How Ford, GM, FCA, and Tesla are bringing back factory workers
In the last week, factory employees have returned to work across the United States to make cars for the country’s four main auto manufacturers: Ford, General Motors, Fiat Chrysler Automobiles, and Tesla. And each of those companies has published a plan showing how it will try to keep those workers from contracting or spreading COVID-19.
Those plans largely take the same shape. They’re presented in glossy PDF pamphlets, each starting with a letter to employees from the respective company’s highest-ranking executive overseeing workplace safety. Like any corporate document, they occasionally get bogged down with platitudes. But they all largely describe a lot of the same basic precautions, including supplying employees with Personal Protective Equipment (PPE) like masks or enforcing physical distancing of at least six feet.
How GM and Ford switched out pickup trucks for breathing machines
In the most severe cases of COVID-19, a patient’s lungs become so inflamed and full of fluid that they no longer deliver enough oxygen to the bloodstream to keep that person alive. One way to counteract this is by using a ventilator, which helps the patient’s lungs operate while the rest of the body fights off the virus.
As the spread of the new coronavirus bloomed into a pandemic, it became clear that there may not be enough ventilators in the United States (and around the world) to treat the coming wave of patients with these severe symptoms.