- Irene Bohoyo
That we live immersed in a phase of profound social and economic transformation is a reality. The use of new digital technologies extends to all layers of the population, to all productive sectors: it is what has been called by experts the Fourth Industrial Revolution or industry 4.0.
Changes are rapid and constant, and in this context the challenges that companies face may seem contradictory: speed in adaptation is key, but the solutions to these new challenges must be long-term , facilitating decision-making in an entirely digital environment.
This Fourth Revolution has been implemented for some time, but it has been the crisis derived from the Covid-19 pandemic that has provided the final accolade. Companies were forced to digitize overnight both their products and services, as well as their strategies and mindsets; they had to resort to tools and solutions unknown to them.
In this context of revolution and rapid transformation, there were sectors that adapted more quickly, by their very nature, such as commerce or culture. Online sales in Spain skyrocketed, even changing consumer habits, who lost their fear of buying online; televisions adapted their formats to video streaming platforms; events went virtual. On the other hand, teleworking brought with it online meetings, generating a whole digitized work ecosystem that seems to have come to stay.
This new reality in which face-to-face attendance was impossible contributed to technological advances, which are already rapid, developing vertiginously.
Applications such as those based on Artificial Intelligence evolved rapidly to be able to respond to the challenges posed by an anomalous situation, unprecedented and full of difficulties, but full of opportunities for improvement and innovation. It is a technology with which we have lived for years, in the form of voice assistants such as Siri or Alexa, chatbots that assist in e-commerce, or virtual or augmented reality systems applied, for example, to training . However, the accelerated digitalization that has taken place since March 2020 until today has contributed to Artificial Intelligence reaching defining achievements, multiplying its applications.
Even so, it should be noted that these advances in terms of AI are not applicable without a set of transformations in other areas.Industry 4.0 implies the combination of advanced production techniques and operations with intelligent technologies (AI) that must be integrated into organizations, people and assets. It is a Revolution in all senses and directions.
The most significant disruption brought about by the implementation of these new technologies has to do with the data flow : companies have access to information in real time. The digital integration of information from different points, sources and locations helps businesses operate in a continuous cycle.
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A cycle that occurs between the physical and the digital through a series of steps better known as PDP (Physical-To-Digital-To-Physical): information from the physical world is collected, digitized, shared the data always analyzing the information in the digital environment, and finally algorithms are used to translate the decisions of the digital world into effective data that stimulates changes.
So that all this can happen, that is, that companies can take advantage of digitization to optimize their processes, such as the flow of data that feeds that artificial intelligence, giving it the necessary information to make it work properly. In an autonomous way, a location is necessary where said data is stored and access is guaranteed from any point. This Fourth Industrial Revolution uses the cloud to do this: its storage capacity allows companies to do without media and physical locations that limit their freedom of movement.
The next-generation cloud uses technologies such as 5G, withlow latency, to ensure the connection and transport of data from one location to another. Through digitalization and migration to the cloud, companies achieve greater efficiency.
While there are sectors that have a longer history in the use of digital tools, and specifically in the implementation of Artificial Intelligence in their production processes, in others, by their very nature and ecosystem, the introduction of these new technologies requires a longer journey. This is the case of the industry, whose production processes are highly mechanized, but not so digitized.
In the Spanish industrial sector, key in the economy, the use of artificial intelligence is relatively recent; in full digital transformation, companies with a higher degree of industrialization have changed their vision, analyzing and including these technologies in their strategies to optimize their productivity, efficiency and sustainability. The use of these automated tools makes the difference between forward-thinking companies and those bound to fall behind.
An example of a company with a vision of the future is Cepsa. The energy company has become a pioneer in Spain and in the world by using Amazon Lookout for Equipment at its facilities, the new Amazon Web Services (AWS) solution based on Artificial Intelligence that facilitates large-scale predictive maintenance< /b> in industrial facilities.
With the firm conviction that the use of new digital tools is the key to the future of the industry, Cepsa has already tested the Amazon Lookout for Equipment technology at its refineries in La Rábida (Huelva) and Gibraltar-San Roque ( Cádiz) with excellent results. Specifically, they have focused on the detection and prediction of anomalies in rotating equipment, such as pumps or compressors, confirming their effectiveness in early detection of abnormal behavior in the equipment.
This type of analysis of equipment data was something that companies traditionally did using much simpler approaches: they were based on rules or models that identified problems based on past behavior. However, this is a rudimentary system that sometimes identifies problems when it is too late to take action, because it does not allow the anticipation that Amazon Lookout for Equipment does. In other cases, a misdiagnosis of the problems leads to incorrectly identifying failures, sending false alarms, and on these occasions a punctual inspection is required that is unnecessary.
Amazon Lookout for Equipment uses state-of-the-art predictive models that are capable of detecting anomalies in industrial equipment (motors, pumps, etc.), preventing future failures as well as breakages of said assets. The main features include being a native cloud solution, the prediction of failures and anomalies days and even weeks in advance, its pay-per-use method and, finally, the possibility of having productivized models at click hit.
Cepsa takes a giant step by allying with Amazon Web Services and positions itself as one of the companies most focused on digital transformation.
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