Predictive maintenance in a pellet production factory

Academic Coordinator | Manuel Febrero Bande, Full Professor of Statistics and Operational Research (USC)

Business Coordinator | Laura Vázquez Pardo, I+D Manager at Grupo Gestán

Description |  Biomasa Forestal has a factory dedicated to manufacturing wood pellets, which operates 24 hours a day, 365 days a year. Therefore, it is essential to be able to predict and anticipate problems in the machines that lead to unscheduled production stops. Currently, the company collects information about preventive maintenance and breakdowns. In addition, they are equipping the machines with sensors that provide information about their operation (vibrations, energy consumption, etc.)

The aim is to find an algorithm that based on all the information being collected is capable of anticipating the breakdown.

Scope | Statistics and Big Data