基于MT生态系统的KSA预测性维护与PHM

H. Srinivasan, Rajaram Madhavan
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引用次数: 0

摘要

技术生命周期管理(TLM)是一个将设备维护和设备维持工程整合在一起的组织,为运营提供技术保障。这意味着更好地管理和不断改进现场设备。在中东可靠性和效率中心(MECRE),我们每天的目标是确保设备保持在正确的水平,缺陷得到适当的报告,维修,调查,工作订单正确完成,团队高效安全地工作。在Well Services中,通过开发定制的移动业务系统来维护复杂的流程和任务,实现了这一愿景。这个数字系统被称为MTEcosystem (mt维护工具)。它可以利用大数据,并聪明有效地处理它们。MTEcosystem捕获与资产维护、报告和实时设备数据相关的所有信息。有了这种数字化支持,就需要重新考虑设备性能和监控,从传统的被动或预防性维护转变为不断发展的预测性维护。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predictive Maintenance & PHM in KSA Using MT EcoSystem
Technology Lifecycle Management (TLM) is an organization that was developed to bring Equipment Maintenance and Equipment Sustaining Engineering into a single umbrella to deliver Technology Assurance to Operations. This means to better manage and continuously improve the equipment in the field. In the Middle East Center for Reliability and Efficiency (MECRE) we aim every day to ensure that the equipment is maintained at the right level, defects are properly reported, repaired, investigated, work orders are rightly completed, and the team works efficiently and safely. In Well Services this vision was enabled by developing a customized mobile business system to maintain complex processes and tasks. This digital system is referred to as MTEcosystem (MT-Maintenance Tool). It can harness bigdata and process them smartly and efficiently. MTEcosystem captures all the information related to asset maintenance, reporting and real time equipment data. With this digital enablement, there is a need to rethink the equipment performance and monitoring to move from the traditional reactive or preventive maintenance to an evolving predictive maintenance.
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