Pattern Based Software Architecture for Predictive Maintenance

Abstract

AbstractMany industrial sectors are moving toward Industry Revolution (IR) 4.0. In this respect, the Internet of Things and predictive maintenance are considered the key pillars of IR 4.0. Predictive maintenance is one of the hottest trends in manufacturing where maintenance work occurs according to continuous monitoring using a healthiness check for processing equipment or instrumentation. It enables the maintenance team to have an advanced prediction of failures and allows the team to undertake timely corrective actions and decisions ahead of time. The aim of this paper is to present a smart monitoring and diagnostics system as an expert system that can alert an operator before equipment failures to prevent material and environmental damages. The main novelty and contribution of this paper is a flexible architecture of the predictive maintenance system, based on software patterns - flexible solutions to general problems. The presented conceptual model enables the integration of an expert knowledge of anticipated failures and the matrix-profile technique based anomaly detection. The results so far are encouraging.