Integrating condition-based monitoring with process sensors information for operation and maintenance in a functional modeling framework

Jing Wu, Xinxin Zhang
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Abstract

Safe operations and adequate maintenance are two main means to achieve reliable production and reduce downtime of a plant. While the tasks of operations and maintenance are carried out by two different groups of staff, as a result, the close relationship between the two tasks is split. In this paper, this challenge is handled by a proposed integrated functional modeling framework. In this framework, the Multilevel Flow Modeling (MFM) method with its cause-consequence reasoning rules is used. Condition-based monitoring is a well-accepted strategy for predictive maintenance and fault detection based on measurements is a well-developed technology for operation support. Information fusion including monitoring conditions of assets and process sensors information for both operation and maintenance in the same modeling framework is desired. The qualitative relationship distribution between operations and maintenance can be established based on the function states of the system. In addition, these relationships are visible for both groups of staff. As a result, the detected information in the early stage of the development of the unpleasant scenarios is used to improve their situation awareness, so that the undesired emergency shutdown from both perspectives of operation and maintenance is prevented. Consequently, it can reduce production loss. A case study of operations and maintenance of a seawater injection system is carried out and shows the industrial applicability of the proposed framework. The case study strongly reveals that there is a highly close relation between operation and maintenance for ensuring the system working properly. It demonstrates that the proposed integrated framework is not only able to support operational tasks but also for the maintenance tasks by including relevant maintenance information of the system. The results show that it can potentially help with decreasing downtime of the system.
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在功能建模框架中集成基于状态的监测与操作和维护的过程传感器信息
安全操作和充分的维护是实现可靠生产和减少工厂停机时间的两个主要手段。虽然操作和维护任务由两组不同的工作人员执行,因此,这两项任务之间的密切关系是分开的。在本文中,提出了一个集成功能建模框架来处理这一挑战。在该框架中,采用了多层流建模(MFM)方法及其因果推理规则。基于状态的监测是一种被广泛接受的预测性维护策略,而基于测量的故障检测是一种成熟的操作支持技术。需要在同一建模框架内实现资产监控状况和运维过程传感器信息的信息融合。根据系统的功能状态,可以建立运维之间的定性关系分布。此外,这些关系对两组工作人员都是可见的。因此,利用不良场景发展初期检测到的信息,提高其态势感知能力,从而从运维两方面防止意外的紧急停机。因此,它可以减少生产损失。以一个海水注入系统的运行和维护为例进行了研究,并证明了所提出的框架在工业上的适用性。案例分析充分表明,为了保证系统的正常运行,运维之间有着密切的联系。结果表明,所提出的集成框架不仅能够支持运行任务,而且能够通过包含系统的相关维护信息来支持维护任务。结果表明,它可能有助于减少系统的停机时间。
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来源期刊
CiteScore
4.50
自引率
19.00%
发文量
81
审稿时长
6-12 weeks
期刊介绍: The Journal of Risk and Reliability is for researchers and practitioners who are involved in the field of risk analysis and reliability engineering. The remit of the Journal covers concepts, theories, principles, approaches, methods and models for the proper understanding, assessment, characterisation and management of the risk and reliability of engineering systems. The journal welcomes papers which are based on mathematical and probabilistic analysis, simulation and/or optimisation, as well as works highlighting conceptual and managerial issues. Papers that provide perspectives on current practices and methods, and how to improve these, are also welcome
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