How are artificial intelligence and machine learning helping in Industry 4.0?

Author: Nivedha Varun

Introduction

Artificial intelligence and, in particular, machine learning have contributed significantly to the industrial revolution 4.0.

Currently, industries of all types already use devices based on some AI technology and the number of companies using AI in Europe is expected to grow in the coming years. On the other hand, machine learning techniques used in organizations have simplified and reduced the "manual" work of many workers.

We've been hearing about industry 4.0 for a few years now, but what exactly is that and how does it relate to various technologies?

What is industry 4.0

Industry 4.0 is a term that was used for the first time in 2011 in Germany and describes an organization of production processes based on software development solutions and devices that communicate with each other autonomously throughout the value chain. In simpler words...

Industry 4.0 consists of the digitalization of the industry and all services related to the company.

It is also known as the fourth industrial revolution, cyber industry, smart industry, etc.

According to the previous figure we have:

  • Industry 1.0: the first industrial revolution emerged in 1784 with the first machining system implemented thanks to the steam engine.

  • Industry 2.0: in this era the invention of the conveyor belt stands out. What is known as mass production begins.

  • Industry 3.0: in the 1960s, semiconductors appeared and with them the first programmable controllers that allowed production to be automated.

  • Industry 4.0: the fourth industrial revolution is characterized by the digitalization of all production processes and their connection to the internet.

How AI is impacting the industry

In practically all production companies we find machines, as well as industrial robots that perform tasks in an automated manner, but this does not mean that they use AI. The main difference between artificial intelligence and automation is that:

  • Automation uses software that follows pre-programmed rules and steps.

  • Artificial intelligence is capable of performing tasks and making decisions for which it has not been specifically programmed in advance.

We are clear about which tasks or in which areas of our company we can apply automation, but what about artificial intelligence? Where would it be useful?

Obviously there is no magic formula and each company has different needs and a different culture. However, if automating an organization usually results in cost savings ranging from 40% to 75% percent and a payback of several months to several years, what would we expect if we employ artificial intelligence?

These are some of the areas of a production company in which artificial intelligence is really useful when it comes to transforming said organization:

Maintenance

Predictive maintenance causes equipment to be maintained when necessary, while preventive maintenance causes work to be performed according to a set schedule, whether it is necessary or not.

To apply predictive maintenance, the company must collect and subsequently analyze data from various manufacturing sources such as machines, sensors, switches, etc. using AI techniques. Using advanced machine learning algorithms, companies are able to predict any anomaly that could cause equipment failure before it happens.

With the use of AI, companies would move from carrying out preventive maintenance to predictive maintenance, before failures occur and anticipating them with a high level of confidence, with the cost savings that this would entail.

Quality

Currently, in industrial processes, quality systems are based on the evaluation of finished products and verification of their correct functioning.

Thanks to the use of data science and artificial intelligence, it is possible to obtain and process a large amount of information that makes it possible to predict complicated situations that would cause significant quality problems.

Leading manufacturers use artificial intelligence, and more specifically machine learning, to help ensure their products are defect-free before they leave the plant, resulting in cost savings.

Thanks to the use of AI, it is possible to control quality before the product is finished.

Security

Safety in the workplace is very important; Production workers are constantly at risk, but with today's software development services, manufacturers can limit threats and improve the security of their most valuable assets: their people. Let's see examples:

3D work instructions

We all know that work instructions and, especially, machine manuals, are sometimes texts that are not as didactic or as clear as one might expect.

Including augmented reality in process instructions, as well as manuals, can help workers better understand tasks and be aware of safety risks and dangerous conditions when working with certain machinery. Printed text lacks the visual context that AR provides.

Real-time monitoring

Monitoring the status of machines, lines and facilities allows you to predict and respond to possible safety problems before they happen. For example, if an anomaly is detected within a piece of equipment regarding aspects such as temperature, air quality or noise levels, it would allow faulty equipment to be proactively shut down or unsafe areas cleared, anticipating safety problems with high confidence. With this type of operational information at your fingertips and analyzed in real time, you can not only improve compliance with prevention regulations, but also make the workplace and the environment significantly safer.

Thanks to AI, there is now custom enterprise software development available that can improve safety in the industry and prevent injuries and illnesses to workers.

Human-robot interaction

Compared to fully automated solutions, collaborative robots ( cobots ) are highly cost-effective, making them attractive to SMEs and other businesses that may not have thought about investing in automation. In addition to this, they allow companies to make better use of their staff and, thanks to simple programming and fast setup times, provide a viable option in small production runs.

Using AI (specifically neural networks) to modify operations performed by the robot based on measured and predicted human movements opens up a whole new world of possibilities for more efficient and flexible work.

Using AI we could model, track and predict human movements within a robot's workspace.

Summary

Artificial intelligence (AI) and Machine Learning (ML), supported by data science, sensors and new communications networks, are quickly becoming indispensable for a wide variety of industries, transforming the way inspections are carried out. (quality control), maintenance and assembly, among other operations, saving costs, improving products and increasing safety.