Nowadays, the maintenance activities are the ones that most draw the attention of companies due to the increased costs of sudden machines stop, and consequently, stop the production processes. These stops are mostly caused by wear-out of its components that lead to machine breakdown and a close monitoring of the manufacturing processes need to be made. Based on this, and to increase the production line efficiency, there's a need to continuously monitor the machines' performance, and together with all the historical maintenance data, create strategies to minimize the maintenance phases and costs. These strategies may lie in the prediction of a suitable time periods to perform maintenance operations, a based on that, group a set of machines together to perform maintenance activities between day-off and day-on shifts. This represents a difficulty mainly because the increased complexity of scheduling and planning activities of a production line, being necessary to minimize the impact of maintenance activities based on failure prediction in all the already existing plan
