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A cost-benefit approach for the evaluation of prognostics-updated maintenance strategies in complex dynamic systems

机译:一种成本效益方法,用于评估复杂动态系统中的预测更新的维护策略

摘要

The implementation of maintenance strategies which integrate online condition data has the potential to increase availability and reduce maintenance costs. Prognostics techniques enable the implementation of these strategies through up-to-date remaining useful life estimations. However, a cost-benefit assessment is necessary to verify the scale of potential benefits of condition-based maintenance strategies and prognostics for a given application. The majority of prognostics applications focus on the evaluation of a specific failure mode of an asset. However, industrial systems are comprised of different assets with multiple failure modes, which in turn, work in cooperation to perform a system level function. Besides, these systems include time-dependent events and conditional triggering events which cause further effects on the system. In this context not only are the system-level prognostics predictions challenging, but also the cost-benefit analysis of condition-based maintenance policies. In this work we combine asset prognostics predictions with temporal logic so as to obtain an up-to-date system level health estimation. We use asset level and system level prognostics estimations to evaluate the cost-effectiveness of alternative maintenance policies. The application of the proposed approach enables the adoption of conscious trade-off decisions between alternative maintenance strategies for complex systems. The benefits of the proposed approach are discussed with a case study from the power industry.
机译:整合在线状态数据的维护策略的实施有可能提高可用性并降低维护成本。预测技术可通过最新的剩余使用寿命估算来实现这些策略。但是,必须进行成本效益评估,以验证针对给定应用的基于状态的维护策略和预测的潜在收益规模。大多数预测应用程序都专注于评估资产的特定故障模式。但是,工业系统由具有多种故障模式的不同资产组成,这些故障模式又可以协同工作以执行系统级功能。此外,这些系统还包括与时间有关的事件和有条件的触发事件,它们会对系统造成进一步的影响。在这种情况下,不仅系统级的预测预测具有挑战性,而且基于条件的维护策略的成本效益分析也极具挑战性。在这项工作中,我们将资产预测的预测与时间逻辑相结合,以获得最新的系统级运行状况估计。我们使用资产级别和系统级别的预测预测来评估替代维护策略的成本效益。所提出方法的应用使得可以在复杂系统的替代维护策略之间采用有意识的权衡决策。通过电力行业的案例研究,讨论了该方法的好处。

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