A Predictive Maintenance Deployment Model for IoT Scenarios
A Predictive Maintenance Deployment Model for IoT Scenarios

Author(s): Albana Gorishti, Klaidi Gorishti
Subject(s): Social Sciences, Economy
Published by: Udruženje ekonomista i menadžera Balkana
Summary/Abstract: The Internet of Things (IoT) concept describes the intelligent connectivity of smart devices using Internet connectivity. In a continuously developing IoT environment, companies try different approaches for predictive maintenance as a solution to reduce costs and the frequency of maintenance activities. Such an environment can natively foster predictive maintenance as it integrates information from different equipment to derive insights and predictions.This paper proposes a deployment model for predictive maintenance approaches on industrial equipment by processing and analyzing their audio signals. Proper maintenance scheduling is necessary to prevent business costs and maintain the equipment in operational capability.The authors propose a system architecture to make predictive maintenance applicable in different industrial scenarios. The implementation exploits deep learning neural networks to detect anomalies and further classify them into categories. These machine learning techniques enable predictions of equipment’s conditions and thus maintenance services can be performed.

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