There is a lot of talk these days about Industry 4.0, but what does this really mean and what does this term have to do with aeronautics? Industry 4.0 consists of creating the concept “Smart Factory”, a new way of organising resources and achieving greater efficiency. This industrial concept can be realised thanks to a number of cutting-edge technologies, such as IoT (Internet of Things or Internet of Things) or AI (Artificial Intelligence).
Artificial Intelligence will bring many exciting developments over the coming years in all branches of the aerospace industry.
The latter will certainly improve/transform aeronautics in the years to come in several aspects and in all fields. From the manufacture of aeronautical components, systems and structures to safety and passenger experience in the case of airports.
But what is artificial intelligence? A colloquial definition would be something like: “a machine that mimics the cognitive functions that humans associate with other human minds”. We could take as an example robots that know how to play chess and that gradually improve. In addition to their initial knowledge, they learn as they play and analyse the results of their actions and their opponent's reactions. Just like a human being.
When we talk about AI (Artificial Intelligence)1 in aeronautics we are talking about something that is already present and part of our lives. It is already being used, even if we do not know it or do not perceive it. In artificial intelligence we distinguish four evolutions or generations:
In the first generation we can find the rule-driven reasoning which may include, for example, all the information received by a pilot or the automatic cabin pressurisation system.
In the second generation comes into play the term Big Data, In this context, the fundamental issue is the large amount of data we collect for further study. For example, in the context of aviation, all security processes linked to facial recognition.
In the third generation is also related to Big Data, but with more “humane” reasoning”. It does not require as much data as previous generations and is arguably an improved version. It optimises inter-departmental communication and will shorten “data collection” times.
In the fourth generation, If we talk about the not too distant future, the idea is to obtain changing patterns with the data we have already obtained and depending on each situation. It is the closest thing to the way human beings deal with information. As an example, we could create autonomous aircraft that take into account all the necessary parameters for a safe flight and know how to act effectively in any situation that is not foreseen thanks to the data available to them.
At present, the European TATEM project carried out a line of research to improve the prediction of aircraft brake wear. To do this, two Artificial Intelligence techniques were used, the data mining (Data Mining) and learning (Machine Learning). The two main objectives were to minimise aircraft maintenance costs and to reduce waiting times between flights, which are often delayed because some aircraft components are checked between flights. With all the data obtained, they determined that the route of the flights could be optimised so that aircraft maintenance could be carried out in certain countries where it is cheaper to carry out maintenance or where it is more convenient due to availability, specialisation or other factors.
A common by-product when discussing such innovations is that many of the people involved ask how will AI affect my job? The answer is simple: AI will not only transform businesses but also people., The new systems of work will have to be readapted to new systems of work. As an example, in a repetitive type of work (industrial, collection, project or analytical) it is obvious that it can be replaced.
AI will bring many exciting developments in the years to come. In the airport context, for example, there are myriad possibilities for development to meet the demands of improving the passenger experience. In the industrial environment, meanwhile, trends will be geared towards improving process efficiency, minimising errors or optimising factory management, to name but a few examples. Looking at it from a more general, business perspective, it will also help to reduce costs and improve service, undoubtedly an objective pursued by any company.
1 - According to Takeyas (2007), AI is a branch of computer science that studies computational models capable of performing human-like activities based on two of their primary characteristics: reasoning and behaviour.
