The industry revolution 4.0 brought a new paradigm to the industrial sphere, it integrates technologies such as Cyber Physical Systems, Internet of Things added to Internet of Industrial Things, among others. With this revolution the process concepts in the industry have evolved, among which maintenance needs special attention, because it is through it that the factory ensures its productivity. Among the existing types of maintenance, predictive maintenance is one of the most efficient solutions in the industry 4.0 scenario, as it works with data analysis from equipment to predict failures and prevent damage. In this work we used the Systematic Mapping research technique to identify the methods used to implement predictive maintenance in the industry, and in the case of this work, focused on the scenario of a television factory in industrial welding equipment in order to create an application to collect real-time data from a machine and create predictions about possible future failures. This paper presents an architecture that meets industry requirements 4.0 and an application that has a relevant hit rate to add value to the factory.
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