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Prognostic control-enhanced maintenance optimization for multi-component systems

机译：多组件系统的预测性控制增强维护优化

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摘要

In the last decades, the fast evolution of the industrial scenario has boosted the economic relevance of maintenance in all sectors of industry, and interests in maintenance can be expected to continue increasing in the next future. Maintenance has gained in importance as a support function for ensuring equipment availability, quality products, on-time deliveries, and plant safety. This paper presents a novel maintenance optimization strategy for multi component systems that uses local prognostic control to improve health statue of operating systems at component level and solves a global optimal problem to find proper maintenance interval at system-level, the combination of which can increase maintenance economy effectively. The proposed strategy can be demonstrated by a case study of braking system of rail vehicles. Compared with traditional dynamic maintenance methodologies, the results show that the maintenance cost can be reduced significantly when both health-oriented prognostic control and global optimization are utilized together. (C) 2017 Elsevier Ltd. All rights reserved.
机译：在过去的几十年中，工业情景的快速发展增强了维护在各行各业中的经济意义，预计维护的兴趣在未来会继续增长。维护作为确保设备可用性，优质产品，按时交货和工厂安全的支持功能而变得越来越重要。本文提出了一种新的多组件系统维护优化策略，该策略使用局部预后控制来改善组件级别的操作系统的运行状况，并解决了全局最优问题以在系统级别找到合适的维护间隔，两者相结合可以增加维护量经济有效。可以通过铁路车辆制动系统的案例研究来证明所提出的策略。与传统的动态维护方法相比，结果表明，同时使用面向健康的预测控制和全局优化可以显着降低维护成本。 （C）2017 Elsevier Ltd.保留所有权利。

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