How to use Machine Learning and Neural Networks in industries?

Artificial Intelligence is one of the most important technologies in the contemporary world. In industries, it has been widely applied for predictive maintenance, scenarios simulations, and budget optimization. The relationship between the technology and this kind of maintenance tied up during COVID-19, when the growing digitalization and increasing adoption of IoT (Internet of Things) amplified the AI market due to the high volume of data obtained.?

Previous to 2022, worldwide industries invested in IoT and other kinds of continuous monitoring technologies to improve maintenance in industrial plants. However, it didn’t take long for industry leaders to realize that just collecting data wasn’t enough, more in-depth, automated analyses and pattern discovery procedures were needed.?

In this scenario, North America is expected to hold the largest market size in adopting and developing both Predictive Maintenance and Artificial Intelligence. According to different reports, government actions during and rising investments in technologies during the pandemic are the main ones responsible for the growth in both areas, holding over 40% share of global revenue in AI during 2020.?

So what is AI and what are the applications for industries??

Artificial Intelligence is not an isolated technology, but rather, a set of technologies that enable applications in the most varied functions within an industrial process. Neural Networks, Deep Learning, Machine Learning, and optimization algorithms are just some of the many computational study fields that exist, and that play a fundamental role in the contemporary industrial process.?

These computational study fields are continuously employed to seek for improving and developing applications in areas related to Search and Optimization, Planning and Scheduling, Knowledge Representation, and Machine Learning.??

Machine Learning has been one of the most mainstream applications of Artificial Intelligence and can be described as algorithms capable of extracting hidden patterns, which can be applied to Classification, Regression, Clustering, and Anomaly Detection, for instance.?

But it is the Artificial Neural Networks (ANN) that have been making a fuzz in industries. The report published by Grand View Research points out that:?

“ANN is substituting conventional machine learning systems to evolve precise and accurate versions. For instance, recent advancements in computer vision technology, such as Generative Adversarial Networks (GAN) and Single Shot Multi-Box Detector (SSD), have led to digital image processing techniques. [...] The continuous research in computer vision has built the foundation for digital image processing in security and surveillance, healthcare, and transportation, among other sectors. Such emerging machine learning methods are anticipated to alter the manner AI versions are trained and deployed.”

So, what are Neural networks??

As the name suggests, Neural Networks are a type of predictive algorithm that is based on and intends to mimic the cerebral functions of our brain. The technology is like a pack of interconnected “neurons” passing messages to each other and can be used in multiple layers to identify hidden patterns present in the data. This is the perfect way to solve image classification tasks, being applied in image recognition and computer vision activities.?

This can be very useful for a long-known problem in industries: corrosion detection/classification. Neural networks can be applied to the automatic detection and localization of defects present in industrial structures and components. Furthermore, this can be the next step for predictive (and even prescriptive) maintenance!?

Therefore, with the aid of Artificial Intelligence techniques and study fields, the ideal time for intervention in tasks related to maintenance, scenario simulation, and budget optimization can be performed based on treated and contextualized data, resulting in higher productivity, lower risks to the operation, and, consequently, greater profitability on the operation.?

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