Tag Archives: Automotive Manufacturing

 

Technology is crucial in most industries to advance safety and efficiency. The automotive sector is an excellent example of how advanced technology transforms products and, thus, the world. Big data and analytics have become an integral part of it all. So, how exactly has the automotive industry taken advantage of analytics, especially with maintenance and predictive diagnostics? How can using it benefit manufacturers? Let’s find out…

How Did Big Data Analytics Emerge in the Automotive Industry?

Big data is a relatively new concept, but its modern adaptations originated in the 1960s. For example, in 1964, IBM introduced the System/360, offering processors 100 times more potent than their predecessors. This technology is primitive in retrospect, but it was an essential first step for data processing. In the 1970s and 1980s, tech companies improved this technology to include the automotive industry.

By the 1990s, automotive technology producers began using big data analytics for vehicles. For example, global positioning systems (GPS) became more prominent this decade. These devices allowed consumers to use navigation technology well-known in the U.S. military. Many luxury cars came with this feature installed to entice consumers.

While GPS devices are still prominent, big data has improved cars enough to where they can be self-reliant. Soon, automakers will remove GPS devices once autonomous vehicles become widespread. These vehicles know where they’re going and do not need a GPS for navigation.

What Role Does Big Data Analytics Play in Automotive Maintenance and Predictive Diagnostics?

The last two decades have seen incredible growth for big data and its role in the automotive industry. Automotive professionals have used advanced technology for maintenance and predictive diagnostics. Using data helps technicians know precisely what the problem is and the necessary methods for mitigation.

Automakers primarily take advantage of big data analytics through embedded sensors in their vehicles. These devices allow the manufacturers to track cars anywhere in the world and detect where the problems lie. With this information, the automaker can notify the consumer of issues, find trends and develop solutions for widespread problems. Then, they know what issues to correct for future models of the same vehicle.

What software and technologies do automotive professionals use? These examples demonstrate how industry experts use big data for predictive maintenance and predictive diagnostics.

Machine Learning

Machine learning (ML) has become a critical part of the automotive industry because it solves complex problems and creates algorithms. For auto manufacturers, ML has helped technicians predict equipment failures.

For example, automakers use ML to analyze historical data from their vehicles. Their computers use sensor data to detect trends and see what abnormalities led to the issues. Therefore, manufacturers can catch what problems may arise when they see a particular pattern occurring in a vehicle.

Another use for ML is creating maintenance schedules for vehicles. Historical data indicate when owners of a particular model should bring their cars for routine maintenance. The algorithm is intelligent enough to combine the data with driver performance to alert when service is necessary for the vehicle.

Telematics

Telematics is one of the earliest examples of big data in the automotive industry, and it’s become vital for car owners and fleet managers worldwide. Research shows about 80% of Class 8 trucks in North America use telematics for safety and efficiency.

Telematics is essential for maintenance because it monitors vehicle health. These devices often detect problems earlier than the operator can, allowing companies to act swiftly on their machines. Early detection and mitigation save money and improve safety by not putting drivers in harmful situations.

What Are the Benefits of Big Data in Automobiles?

Big data analytics is a win-win for manufacturers and consumers. All parties can have peace of mind knowing their machines are safe and efficient. The following three benefits demonstrate how automotive professionals benefit from big data.

Improving Safety

Cars are essential for daily travel, but they can be dangerous. The National Highway Traffic and Safety Administration (NHTSA) says nearly 43,000 people died in motor vehicle traffic crashes in 2022. Reasons for accidents vary, but they can originate from fixable mechanical failures.

Big data analytics decreases the likelihood of these failures by scheduling preventive maintenance and alerting when serious problems arise. Users can know if their brakes, steering wheel or battery needs attention before a catastrophe happens.

Decreasing Downtime

Big data analytics has become invaluable for fleet managers worldwide. The average fleet manager may have 10, 100 or 1,000 vehicles under their wing, making it difficult to track all of them simultaneously. However, advanced data allows them to monitor all the cars and detect trends.

Warning systems send information to the fleet manager, allowing them to act immediately. The modern supply chain demands maximum productivity from fleets, so taking advantage of big data analytics is essential.

Supporting Sustainability

Sustainability has become a significant focus for auto manufacturers. The push for more renewable energy and less waste has led to innovation across the industry. How are they achieving sustainability standards? Big data analytics is helping automakers care for the environment.

Using big data analytics extends the life of cars and reduces the need for customers to consume resources by purchasing cars. Instead, they can keep the same vehicle longer and spend less time at the mechanic.

When cars reach their end of life, many head to the scrapyard. While recycling has improved, parts and pieces still go to waste. For example, the European Union scrapped 5.4 million passenger cars in 2020. Installing telematics devices and using big data would extend their time on the road and reduce waste.

Big Data Analytics in the Automotive Industry

Automotive technology has come a long way and only improves yearly. Modern software allows auto manufacturers to utilize big data analytics with maintenance and predictive diagnostics. With this technology, manufacturers lower the cost for themselves and consumers and make their processes more efficient.

*This article is written by Jack Shaw. Jack is a seasoned automotive industry writer with over six years of experience. As the senior writer for Modded, he combines his passion for vehicles, manufacturing and technology with his expertise to deliver engaging content that resonates with enthusiasts worldwide.

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The automotive industry has faced many challenges since the first cars rolled out of factories in the 1800s. Automobiles have become an integral part of society as a means of transportation for people and goods.

Given the importance of vehicles, many automotive companies focus on research, development, and innovation to deliver the best products to customers.

Automobiles Are Getting Smarter

The future of automobiles involves offering additional smart technology and features. We’ve come a long way since the days of steam-powered cars. In those times, vehicles consisted of a seat with wheels powered by an engine. In contrast, today’s automotive companies are in a constant battle for the latest features.

Car manufacturers first removed the need to shift with automatic transmission, and then they removed the need for maps with GPS. Now, they’re working on removing the need for drivers to control cars.

With automakers hard at work developing self-driving cars, experts see future roads filled with cars that can drive themselves. Radar sensors and complex algorithms can help accomplish this.

Machine-learning technology plays a significant role in the safety and navigation of self-driving cars. It creates a map of the surrounding area based on sensors. Meanwhile, control features monitor other vehicles. The data powers the understanding of the surroundings.

Complex software could process the data to operate the vehicle. With this technology, the car knows the direction to take, how to steer, when to accelerate, and when to hit the brakes. In the future, automobiles will operate themselves, with vehicle occupants becoming mere passengers.

Development is expected to wane in 2023. However, companies continue to take steps toward this goal, albeit at a slower pace.

Self-Reliant Cars

Not only are cars becoming smarter, but they are also more self-reliant. Companies are working on features to reduce vehicle maintenance. One example is regenerative braking.

Automobile brakes rely on tremendous force to stop the vehicle. Regenerative braking takes the excess kinetic energy that otherwise goes to waste and turns it into electricity. The motor then receives the electricity as power.

Mobile information integration is another factor. Many car owners frequently worry whether their vehicle is in good condition. Drivers do not want to take on a cross-border drive only to find something is wrong in the middle of the trip. Information integration could prevent that.

One future service possible through mobile integration information is preventive maintenance. With this, the car becomes capable of monitoring its own systems and doing self-diagnosis. It relays key information to the owner. As a result, car owners get an early warning about their vehicles’ operational performance and potential issues.

Technology Integration

Another key feature of future cars is integration with technology. We live with smart technology everywhere. From computers to smartphones, we are a voice command away. Why not integrate cars into the mix?

Volvo has already taken a step toward this. Partnering with Google, the automotive company is planning to introduce features to allow car owners to use voice commands with their vehicles. Examples include the following:

Integrating technology could also mean making better use of time spent on the road. Most people equate their daily commute to lost time. That could change with the right technology. The goal is to deliver productivity apps in the car.

Future vehicles would allow owners to do the following on the road:

What is lost in the commute could be brought back with the right technology integration. However, with all the new features and integration, the issue of privacy comes up. Customers expect personalization, but that means providing personal data. This means automotive companies must have safeguards in place to protect car owners’ personal information.

Meeting Customer Expectations

Modern customers have varying expectations, and there is no single vehicle that can meet all customer needs. Instead, car manufacturers offer a variety of options.

That has led to the development of crossover vehicles. The idea is to give people an in-between option. Need more space than a car without going with a truck? You can now choose from a wide range of crossover vehicle models.

Innovation Is the Mindset

Having an innovative mindset is the key to remaining competitive in the automotive industry. These new features improve customer experience. When people choose between cars, they typically go with one that offers the functions they need. Advanced technology could influence consumers’ choices of vehicles.

Either manufacturers disrupt the industry, or they will get disrupted. Everyone is trying to create the next best thing to offer the public. They should never stop innovating, not only in terms of car features and performance. Using new technology, manufacturers could develop new business models.

Traditional business models for automakers include vehicle sales, after-sales services, and financial services such as loans. Advancements in technology can improve these services. For instance, social media platforms create an opportunity for market research. These platforms can also be a channel for after-sales services.

Moreover, websites and apps can now process financial data. These processes are more accessible to customers through technology.

New business models are developed, too. Mobility as a service (MaaS) and cars as a platform are good examples. With MaaS, customers can book vehicles for specific tasks. Ride-sharing apps are an example of that, as they are starting to eliminate the need for some people to own a car. That does not mean doom for automakers; it presents an opportunity to adjust their focus instead.

Innovation provides flexibility for manufacturers. It allows automotive companies to be prepared for disruption, which can happen anytime.

Learning From the Past

As the recent COVID-19 pandemic has proven, the supply chain is highly vulnerable. One small change can cause a ripple effect, disrupting the entire chain. Costs tend to go up in that scenario, and it is the customer who pays for that.

The COVID-19 pandemic severely affected the entire global supply chain. All industries felt the consequences of shutdowns. According to studies, the auto industry was among the hardest hit. Study results showed that over 50% of the auto sector said the disruption to them was very significant. That was the highest proportion across all other industries in the survey.

The biggest supply chain issue that affected the automotive industry was the automotive microchip shortage. Semiconductors and computer chips are crucial in powering modern vehicles’ advanced features. The semiconductor shortage resulted in production almost grinding to a halt.

Automotive production processes have not yet fully recovered from these shortages. As a result, auto experts remain unsure about whether now is a good time to buy a car.

The silver lining is digitization. The pandemic accelerated automotive companies’ progress in adopting new technology. It helped them recover and develop new supply chain processes.

The pandemic was not the first disruption the auto industry experienced, and it surely will not be the last. Automakers should expect more to come, as future disruptions could come from their progress.

What the Future Holds for the Automotive Industry

It is interesting to see how individual vehicle ownership could become obsolete. The current popularity of ride-sharing apps and other MaaS platforms shows that many customers prefer this means of transportation. This is also why automakers are focusing on driverless technology.

That means innovation is turning the automotive industry away from its current business model. Instead of losing to new customer preferences, automotive companies are leaning toward these changes. In doing so, they remain in control. This flexibility could be a significant aspect of future innovations in the automotive industry.

* This article is written by Cedric Jackson. Cedric is a freelance writer who is passionate about internet marketing, automotive, travel, and the entertainment world.

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