I. Introduction
Throughout modern history humanity has faced transformative events known as "industrial revolutions"; the First Industrial Revolution introduced steam machines and hydraulic energy, allowing the transition from the usage of humans and animals; this revolution is followed by the one that came with fuel and gas, alongside with the invention of telephone, which brought mass production and the origins of automatization, followed by the arrival of Programmable Logical Controllers that introducted to data analysis. Industry is currently going through the Fourth Industrial Revolution, also known as Industry 4.0 (I4.0); the goal is the integration between physical and digital systems, or as Lee [12] defines it: the pursuit of autonomous industrial systems base on Artificial Intelligence, Big Data, Data Analytics, Cloud Computing, Internet of Things, among others, implying the possibility of automatizing data collection from machines and components. Cinar [34] claims Machine learning algorithms can be applied over the collected data and allow fault detection and diagnosis. The techniques often used for this end infuse intelligence within systems so they can learn automatically and adapt to changing environments using historical experience in the training stages.