Predictive maintenance, its implementation and latest trends
Predictive maintenance, its implementation and latest trends
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DOI：
10.1177/0954405415601640
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发表时间：
2017-07
期刊：
影响因子：
--
通讯作者：
Ş. Selçuk
中科院分区：
文献类型：
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作者：
Ş. Selçuk
本研究涵盖了预测性维护领域的新趋势和新技术，至少在一定程度上已经取代了传统的管理策略。它还提出了如何在工厂/场所实施预测性维护计划等建议。预测性维护主要包括通过检测故障的早期迹象来预测要维护的系统的故障，从而使维护工作更加主动。除了在故障发生前采取行动的目的外，它还旨在注意任何故障，即使没有立即发生故障的危险，以确保平稳运行并降低能耗。为了提高可靠性、安全性、可用性、效率和质量以及保护环境，预测性维护已被制造业和服务业的各个部门所采用。它还创建了一个独立的部门，专门开发预测性维护仪器，提供专用的预测性维护解决方案和培训预测性维护专家。预测性维护技术与传感器技术密切相关，但为了有效的预测性维护应用，需要根据特定组织的需要调整一种综合方法，将传感与后续维护活动相结合。信息、通信和计算机技术的最新进展，如物联网和射频识别，使预测性维护应用更高效、更适用、更经济，因此更普遍，可用于各种行业。远程维修和电子维修的研究已经为预测维修活动提供了支持，特别是在不安全的工作环境和分散的地点。
This study covers new trends and techniques in the field of predictive maintenance, which has been superseding traditional management policies, at least in part. It also presents suggestions for how to implement a predictive maintenance programme in a factory/premise and so on. Predictive maintenance primarily involves foreseeing breakdown of the system to be maintained by detecting early signs of failure in order to make maintenance work more proactive. In addition to the aim of acting before failure, it also aims to attend to any fault, even if there is no immediate danger of failure, to ensure smooth operation and reduce energy consumption. Predictive maintenance has been adopted by various sectors in manufacturing and service industries in order to improve reliability, safety, availability, efficiency and quality as well as to protect the environment. It also has created a separate sector, which specializes in developing predictive maintenance instruments, offering dedicated predictive maintenance solutions and training predictive maintenance experts. Predictive maintenance techniques are closely associated with sensor technologies but for efficient predictive maintenance applications, a comprehensive approach, which integrates sensing with subsequent maintenance activities, is needed to be adapted in accordance with the needs of the particular organization. Recent advances in information, communication and computer technologies, such as Internet of Things and radio-frequency identifications, have been enabling predictive maintenance applications to be more efficient, applicable, affordable, and consequently more common and available for all sorts of industries. Researches on remote maintenance and e-maintenance have been supporting predictive maintenance activities especially in unsafe working environments and scattered locations.