Fostering maintenance management’s evolution in the Industry 4.0 era: an innovative approach to maintenance planning and fault detection

The deep transformation that the industrial reality has been undergoing in recent years and that is most commonly referred to as “Industry 4.0” has opened new opportunities for improvement for all organizations in terms of efficiency, flexibility and effectiveness. In this context, maintenance management is acknowledged as one key factor to successfully achieve this revolution and one field capable of great improvements. However, the technologies and, consequently, the new arising opportunities of innovation are various and quite diversified and there is still lack of clear comprehension of the scenario truly available in the maintenance management field and a lack of a systematic approach to guide this change in a conscious and effective way. Thus, a methodological approach to improve maintenance planning and fault detection has been here proposed. The work started with a literature study in order to map all the characteristics associated with the Industry 4.0 paradigm and their possible applications to maintenance. This study provided a strong foundation to create a framework of reference to decline the digitalization opportunities against the maintenance policies applied by organizations. Afterwards, a methodological approach to maintenance planning was proposed. Based on Reliability Centered Maintenance, the proposed approach is aimed at providing an operative tool for organizations to foster the evolution of their maintenance plan towards the paradigm of digitalization, highlighting hidden opportunities for improvement not identifiable by the traditional approach. Moreover, to provide a methodology to fault detection applicable to different industrial scenarios, an approach based on the use of Artificial Neural Networks has been proposed. These methodologies have been applied to real industrial cases in order to test their validity: a manufacturing plant, two photovoltaic plants, a compressed air generation system and wind turbines.