The technological data collected by WebScada systems, which have existed and been in operation for decades, offer a wealth of opportunities that can be exploited by machine learning algorithms based on artificial intelligence, which have already been proven useful in the financial and telecommunications sectors. As part of the 4th Industrial Revolution, the data mining methodologies that unfolded in the early 2000s are already available to the industry. Since the cornerstone of these applications is data and their quality, it is obvious to combine WebScada systems with these techniques. During the project, we developed algorithms and methodologies that can be integrated into the WebScada systems operated by Controlsoft Kft. Thanks to the html-based visualization solutions applied in the framework the operator displays can be presented in an html environment. In the second part of the current work phase, we have already developed data analysis techniques that are able to predict errors based on past event sequences during current operation. This documentation presents the developed framework, algorithms and shows an example for each application, together with a short case study.