The fourth industrial revolution has already happened. In industry 4.0, factories and machines are instrumented with sensors able to acquire data along the production process and the produced product. Fault prediction is one of the solution provided by industry 4.0 to reduce wastes in terms of time and resources due to problems in the production line. Until now, in order to deal with production errors, a domain expert has been charged to analyze all the parameters and processes related to the production line to figure out what caused manufacturing defects. The goal of this thesis is to improve this process by reducing the time spent on identifying which are the factors responsible for failures and remove the bias introduced by the domain expert who is involved in the analysis.