Way back in 1913, Henry Ford, founder of Ford Motor Company, introduced the assembly line technique in mass production manufacturing. Essentially, this is what converted the automobile from being an expensive luxury, to a practical conveyance. A major revolution in the automotive industry.

Now, a century later, the automotive industry is undergoing an additional revolution, otherwise known as the fourth industrial revolution.

The fourth industrial revolution revolves around the digitization of manufacturing, and is called Industry 4.0. It is defined by the enhancement of smart systems fueled by data and machine learning. 

While Industry 4.0 has made, and continues to make, a huge impact on manufacturers across different industries, I will focus this post specifically on Industry 4.0 in the Automotive industry. 

The automotive manufacturing industry is typically divided into two sectors: car manufacturers (OEMs), and car part manufacturers (Tier 1 and Tier 2). As the cars we see on the roads continue to evolve and improve, the number of parts has grown since previous years, which naturally, has led to an increase in parts being manufactured by suppliers. 

With the complexity of today’s vehicles, and the continuous strive to perfect the end product, car manufacturers are increasingly facing quality challenges that are time-consuming and labor-intensive to resolve. 

Introducing Industry 4.0 to the automotive industry

Industry 4.0 is defined by the understanding of data captured by machines, their behavior and how to leverage that information to improve production outcomes.

And while most automotive facilities haven’t yet reached the perfect state of connectivity where humans and machines seamlessly work together, the industry is beginning to embrace the principles of Industry 4.0. This is a great opportunity for them to solve quality challenges they are facing in the production line.

Fortunately, the automotive industry, is one of the more enthusiastic ones to adopt industry 4.0.

According to a recent report by Capgemini, by the end of 2022, automotive manufacturers expect that 24% of their plants will be smart factories and 49% of automakers have already invested more than 250 million dollars in smart manufacturing.

Let’s dive into the different business benefits that automotive manufacturers gain in implementing Industry 4.0 technologies:

Discovering primary causes of process inefficiencies

By implementing process-based artificial intelligence, production engineers can identify different process inefficiencies in their production line that damage quality and yield. This is done with Automated Root Cause Analysis

Automated Root Cause Analysis applies different machine learning algorithms to production line data, automatically tracing the chain of events that lead to specific production failures. This enables teams to easily investigate the causes of the failures, allowing them to mitigate the root causes.

Predicting and preventing when process inefficiencies will happen

Now, with the ability for production teams to understand the cause of specific production failures, they will want to prevent them from happening again.

This can be done with predictive analytics, which essentially translates the captured data into predictive insights. This allows for production teams to identify when specific process inefficiencies will occur, giving them the ability to prevent them before it happens. By having this ability, process teams are able to increase yield and prevent quality failures.

How Bosch Automotive Benefited from Industry 4.0

Let’s take a look at the business benefits that Bosch Automotive Diesel System factory realized after implementing Industry 4.0 to optimize production processes.

Bosch was experiencing production failures and losses, leading them to search for a way to identify bottlenecks in their production operations in order to prevent them.

As combining IIoT and big data is a big part of the digital transformation Bosch is undergoing, they connected their machinery to monitor the overall production process at the core of its plant. By using data analytics to process the data in real-time, they were able to predict production failures, enabling them to prevent future losses from happening before they even occur.

They saw more than a 10% increase in throughput, and continually improved delivery time and customer satisfaction.

The implementation of an AI-powered data solution, ultimately allowed for data-driven decision making, resulting in optimized production.

By leveraging Industry 4.0 technologies, automotive manufacturers can address processes-driven quality and throughput losses in production and assembly processes. For example, surface quality issues, coating issues, paint thickness problems, dashboard assembly issues, interiors and more, can all be mitigated. By doing so, they experience the long term business benefits that translate to increased ROI.