We are currently evolving rapidly in the use of Machine Learning and Deep Learning, terms that are often treated interchangeably.

Both concepts are encompassed in Artificial Intelligence, which we must understand in order to know Machine Learning and Deep Learning in depth.

What is Artificial Intelligence?

Artificial intelligence, also known as AI, is the technology capable of imitating human reasoning. Sometimes it is as simple as programming it to follow a logical flowchart, or a computer programmed to think almost like a human and apply that knowledge to new situations and scenarios.

AI includes the concepts of Machine Learning and Deep Learning, which we will get into below.

Machine Learning
This is a branch of AI that involves the creation of algorithms capable of modifying themselves, without human intervention. It is a method of data analysis, based on the idea that systems can learn from this data, identify patterns and make decisions without the help of a human being.

Deep Learning
Deep Learning uses a specific class of algorithms, called neural networks. There are numerous layers of these algorithms, each providing a different interpretation of the data. Neural networks work in an attempt to mimic the function of neural networks in the human brain. This concept includes speech recognition, object detection and image identification.

How do these technologies work?

Machine learning algorithms learn from the data submitted to them and, in this way, machines are trained to learn to perform different tasks autonomously. Then, when exposed to new data, they adapt from previous calculations and patterns are moulded to provide reliable answers.

Deep Learning are those complex algorithms built from a set of several layers of “neurons”, fed by immense amounts of data, that are able to recognise images and speech, process natural language and learn to perform extremely advanced tasks without human interference. The main application of Deep Learning algorithms is classification tasks, in particular image recognition.

How is Machine Learning and Deep Learning applied in Industry 4.0?

Industry 4.0 is in charge of inserting information technologies into industry in order to carry out a digital transformation that makes industries smart. This is where Machine Learning comes into play to create models that give value to the data extracted thanks to the Internet of Things or IoT, and optimise decision-making, as the implementation of this technology in industry contributes to improving productivity, manufacturing efficiency and enables faster, more flexible and more efficient processes.

The goal of every industry is to offer products or services of the highest possible quality at the lowest possible cost. Machine Learning and Artificial Intelligence are the technologies in charge of transforming traditional industries to Industry 4.0, thus helping manufacturers to achieve their main goal.

There are different applications of Machine Learning in industry:

Machine Learning applied in production, manufacturing and quality.
This technology provides flexible solutions to the complexity of production systems. The term Intelligent Manufacturing Systems refers to the new generation of production systems that use the results of research in artificial intelligence to solve problems linked to the lack of information.

Machine Learning applied to logistics.
The data generated and exported are processed and interpreted like human beings thanks to algorithms based on Deep Learning technology.

Machine Learning applied in maintenance.
Machine Learning is responsible for creating models from operating data obtained, in order to detect possible anomalies before they occur. This is called predictive maintenance, and its application is one of the most reliable ways to prevent machines from failing and damaging the production process.

Machine Learning applied to safety.
Powerful Machine Learning and Deep Learning algorithms in cybersecurity are mainly used for malware analysis and intrusion detection and prevention.

Machine Learning applied in ergonomics.
Motion analysis systems are used to create reports on the productive and ergonomic movement of the worker. This is achieved with hardware called MOCA, integrated with software based on neural networks specialised in image and video processing.



Apply Machine Learning with Nexus Integra

Nexus Integra is the integrated operations platform that will allow you to drive the digital transformation of your organisation. It connects all your assets and information systems through Big Data technology. Monitor, manage and analyse the assets of your business, obtaining a 360º vision of the company.

Nexus Integra’s machine learning application allows you to take advantage of specialised algorithms and Artificial Intelligence to provide advanced analysis to understand process behaviours in an easy, intuitive and scalable way. The platform employs different algorithms to make the best business decisions by comparing historical trends and real-time data.

Take advantage of the benefits of digital transformation with Nexus Integra and make way for the new way to exploit your business data for the benefit of efficiency and savings.

Contact us and find out how!