Industry 4.0 is the new era of industrial production, characterized by the integration of advanced technologies such as the Internet of Things (IoT), cloud computing and Artificial Intelligence (AI). 

In Industry 4.0, AI is one of the key technologies, as it allows machines to communicate with each other, learn from real-time data, and even make autonomous decisions. With this capability, companies can improve efficiency, productivity and quality, as well as reduce costs and increase safety in the workplace.

From predictive analytics to process automation, AI is transforming how businesses operate and produce goods and services, and its use is expected to continue to grow as the technology evolves further.

Want to know more about it? So, keep reading to get to know 11 uses of Artificial Intelligence in Industry 4.0, in addition to its main benefits.

Uses of Artificial Intelligence in Industry 4.0

Although it is constantly growing, there are many possible ways to apply AI commercially that bring real benefits to the company. Indeed, many businesses already use this technology in order to increase their productivity and, especially, their results.

Below, we list 13 uses of Artificial Intelligence in Industry 4.0. It is true that they are not the only ones, but from this, you will already be able to get an idea of the potential that this technology may bring about.

1. Machine Learning

Machine learning can be used in order to optimize production, reduce costs, and predict equipment failures. It’s one of the most basic AI concepts, but still extremely powerful.

For example, elevator maker Schindler uses machine learning in order to monitor sensors in its elevators and predict when components need to be replaced before they fail.

A simple but extremely powerful application for business.

Read also: Myths about Machine Learning: 12 items to know in order understand more about the concept

2. Artificial neural networks (ANNs)

Artificial neural networks can be used in order to solve complex classification and pattern recognition problems.

BMW, for example, uses artificial neural networks in order to improve product quality by analyzing images of automotive components for defects of any kind, whether simple or severe.

3. Natural Language Processing (NLP)

Natural language processing is one of the main strands of AI used these days and Industry 4.0 is no different. In practice, it can be used in order to automate customer service and document processing.

As an example, the insurance company Allstate uses natural language processing to automate claims assessment, reducing the time it takes to process policyholder claims.

4. Computer vision

Computer vision is also one of the strands of AI that enable image processing through computers. Thus, it can work in companies that manufacture products as one of their quality control steps.

As an example, we have the chipmaker Intel that worked together with Ambev in order to improve the inspection process of delivery vehicles. This allowed for a faster, more assertive and very high-quality process.

5. Recommendation systems

The popular recommendation systems can be used in order to personalize the user experience and improve sales efficiency.

As an example, we have Amazon using technology in order to offer relevant products to customers based on their previous purchases and browsing history. This can be done through the website or smart devices such as Alexa.

6. Robotic process automation

Robotic Process Automation can be used in order to automate manual tasks such as data processing, information gathering, and data logging.

However, it is important to reinforce that RPA is not an Artificial Intelligence, but that it can, yes, work perfectly in conjunction with it. This happens because RPA operates in the process based on well-defined rules—and not through learning, as is the case with AI.

Still, RPA technology could be a “right-hand man” of artificial intelligence, performing tasks based on image patterns in a complex process chain. It is the union of the dynamism of AI with the productivity of RPA.

7. Conversational Artificial Intelligence

Another technology widely used these days is conversational AIs. They are used in order to improve user interaction with chatbots and virtual assistants, whether in chats or home smart devices.

As an example of its use in Industry 4.0, we have Banco do Brasil using chatbots powered by Artificial Intelligence in order to provide support to customers and help them solve simpler financial problems that require human service.

8. Predictive analytics

Predictive analytics can be used in order to predict maintenance problems, equipment failures, and identify opportunities for improvement. All this in a very proactive manner, as its name suggests.

Rolls-Royce, for example, uses predictive analytics to monitor the health of aircraft engines in real time, reducing maintenance costs and increasing safety. To read more about the topic, in English, simply access the article here.

9. Augmented reality

Augmented reality is a very powerful feature and can be used in order to improve user experience, training, and even maintenance services.

But Augmented reality alone is also not classified as Artificial Intelligence. However, it can be combined with an AI in order to accomplish incredible feats, as is the case with the recently released Vision Pro, Apple’s reality glasses.

Below, we have a video explaining how the AI is applied (subtitles in Portuguese), it is very much worth watching:

The Hidden AI in Apple’s new VISION PRO – Spatial Computing

10. Anomaly detection

Detecting unusual patterns in data sets is important in order to alert users to potential problems with a product. Thus, measures can be taken to avoid accidents or harm to users as a whole.

As an example, we have the German company Osram that uses anomaly detection in order to monitor its production equipment and detect performance problems, reducing downtime and improving machine efficiency.

11. Speech recognition

Speech recognition is also a well-developed feature that is present in personal devices and increasingly advancing to common uses in the workplace.

Technology company Vocollect, for example, uses voice recognition in order to help workers accomplish tasks more efficiently, such as picking up and packing items in a warehouse. All this without having to look at a screen or device.

Conclusion

As we have seen, the impact of Artificial Intelligence in Industry 4.0 is quite significant, if we consider that it is a relatively new technology still in the early stages of its discovery process.

Still, large companies already take advantage of AI and its many benefits in order to achieve surprising results in their areas of expertise. And that, over time, should only increase more and more.

Do you like the content? Then also take the opportunity to read: Digital transformation in Industry 4.0: scenario, challenges and how to evolve the concept