Maintenance 4.0: Intelligent and Predictive Maintenance System Architecture

A. Cachada, J. Barbosa, P. Leitão, Carla A. S. Gcraldcs, Leonel Deusdado, J. Costa, Carlos Teixeira, J. Teixeira, António H. J. Moreira, Pedro Miguel, Luís Romero
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引用次数: 97

Abstract

In the current manufacturing world, the role of maintenance has been receiving increasingly more attention while companies understand that maintenance, when well performed, can be a strategic factor to achieve the corporate goals. The latest trends of maintenance leans towards the predictive approach, exemplified by the Prognosis and Health Management (PHM) and the Condition-based Maintenance (CBM) techniques. The implementation of such approaches demands a well structured architecture and can be boosted through the use of emergent ICT technologies, namely Internet of Things (IoT), cloud computing, advanced data analytics and augmented reality. Therefore, this paper describes the architecture of an intelligent and predictive maintenance system, aligned with Industry 4.0 principles, that considers advanced and online analysis of the collected data for the earlier detection of the occurrence of possible machine failures, and supports technicians during the maintenance interventions by providing a guided intelligent decision support.
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维护4.0:智能预测性维护系统架构
在当前的制造业中,维护的作用受到越来越多的关注,而公司也明白,如果维护执行良好,可以成为实现公司目标的战略因素。最新的维修趋势倾向于预测方法,例如预后和健康管理(PHM)和基于状态的维修(CBM)技术。这些方法的实施需要一个结构良好的架构,并可以通过使用新兴的信息通信技术,即物联网(IoT)、云计算、先进的数据分析和增强现实来促进。因此,本文描述了一个符合工业4.0原则的智能和预测性维护系统的架构,该系统考虑对收集的数据进行高级和在线分析,以便更早地检测可能发生的机器故障,并通过提供指导式智能决策支持,在维护干预期间为技术人员提供支持。
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