Industrial Asset Management using IIoT and performance indicators

Abstract

With the advance of the Fourth Industrial Revolution and the emergence of the Industrial Internet of Things (IIoT), the integration of information in the industrial sector has become essential in order to meet the demands of a competitive market, which increasingly requires efficiency and productivity from companies. In this context, this study presents the results of the implementation and operation of an IIoT-based maintenance supervision system on a pallet transportation line. The proposed strategy highlights IIoT-based monitoring and detection using piezoelectric transducers, with a focus on industrial maintenance, especially key performance indicators. The main objective is to identify potential process failures and reduce operational downtime, enabling management and decision-making based on indicators such as mean time between failures (MTBF), mean time to failure (MTTF), availability and throughput, which are fundamental to industrial asset management. Over a period of five months, these indicators were used to assess the effectiveness of the Maintenance Planning and Control applied to the line. The implementation of the proposed system resulted in observable improvements in production performance following maintenance activities, as well as facilitating the monitoring of asset deterioration over time.