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Maintenance behaviour-based prediction system using data mining

机译:使用数据挖掘的基于维护行为的预测系统

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摘要

In the last years we have assisted to several and deep changes in industrial manufacturing. Induced by the need of increasing efficiency, bigger flexibility, better quality and lower costs, it became more complex. The complexity of this new scenario has caused big pressure under enterprises production systems and consequently in its maintenance systems. Manufacturing systems recognize high level costs due equipment breakdown, motivated by the time spent to repair, which corresponds to no production time and scrapyard, and also money spent in repair actions. Usually, enterprises do not share data produced from their maintenance interventions. This investigation intends to create an organizational architecture that integrates data produced in factories on their activities of reactive, predictive and preventive maintenance. The main idea is to develop a decentralized predictive maintenance system based on data mining concepts. Predicting the possibility of breakdowns with bigger accuracy will increase systems reliability.
机译:在过去的几年中,我们协助了工业制造领域的几次深刻变革。由于需要提高效率,更大的灵活性,更好的质量和更低的成本,因此变得更加复杂。这种新情况的复杂性给企业生产系统及其维护系统带来了巨大压力。制造系统认识到由于设备故障而导致的高昂成本,这是由维修时间引起的,这相当于没有生产时间和报废场,并且花费在维修工作上。通常,企业不会共享其维护干预措施产生的数据。这项调查旨在创建一个组织架构,该架构将工厂生产的有关其被动,预测和预防性维护活动的数据集成在一起。主要思想是开发基于数据挖掘概念的分散式预测维护系统。以更高的精度预测故障的可能性将提高系统的可靠性。

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