Impact of intelligent wireless sensor network on predictive maintenance cost

Soukaina Sadiki, M. Faccio, M. Ramadany, D. Amgouz, S. Boutahar
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引用次数: 4

Abstract

Today's modern manufacturing demand that production systems be monitored continuously, in real time, to ensure reliability, safety of manufacturing processes and quality of products. The integration of intelligent sensors into production systems enables very specific tasks to be performed, such as remote monitoring and communicating quickly the relevant information concerning deterioration detected on these systems. This is of major interest to guide maintenance manager to make decision regarding maintenance actions. The objective of this article is to investigate the impact of maintenance policies on the performance of manufacturing systems. The integration of intelligent sensors networks is proposed for monitoring equipments to implement predictive maintenance policy. We develop simulation studies to investigate the impact of the intelligent sensor on predictive maintenance cost and reliability. The optimum predictive maintenance time can be found using the threshold of the reliability data issue from the sensors. The methods are based on the cost per unit time to show how different parameter impact the cost of maintenance, To perform this study a numerical example is illustrate the model.
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智能无线传感器网络对预测性维护成本的影响
当今的现代制造业要求对生产系统进行持续、实时的监控,以确保制造过程的可靠性、安全性和产品质量。将智能传感器集成到生产系统中,可以执行非常具体的任务,例如远程监控和快速沟通有关这些系统上检测到的恶化的相关信息。这对指导维修经理做出有关维修行动的决策具有重要意义。本文的目的是研究维护策略对制造系统性能的影响。提出了集成智能传感器网络,实现监控设备的预测性维护策略。我们进行了仿真研究,以研究智能传感器对预测性维护成本和可靠性的影响。利用传感器提供的可靠性数据的阈值,可以找到最优的预测维护时间。该方法基于单位时间成本来说明不同参数对维修成本的影响,并通过数值算例对模型进行了说明。
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