Quantifying the added value of an imperfectly performing condition monitoring system—Application to a wind turbine gearbox

Horenbeek, Adriaan Van; Ostaeyen, Joris Van; Duflou, Joost R.; Pintelon, Liliane

doi:10.1016/j.ress.2012.10.010

Cited by 40 publications

(32 citation statements)

References 22 publications

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“…A condition monitoring system (CMS) plays a critical role in beating the maximum potential of wind energy through wind turbine by minimizing the idle time. The cost of CMS design and installation is significant in comparison to other maintenance approaches but in the longer run CMS provides benefits exceeding the costs [12][13][14][15]. In fig.1 indicates the failure patterns that can be identified by condition monitoring and highlights the importance of the P-F curve and P-F interval.…”

Section: Condition Monitoring System (Cms)mentioning

confidence: 99%

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Computational Intelligence, Condition Monitoring and Optimization in Mechanical System- A Review

Kumar¹,

Ganesan²

2014

IJETT

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Energy is considered as the essential part for the national development in the form of mechanical power or any other which has major contribution for improving the quality of life and enhancing the economic growth. Thus, the use of wind turbine in the form of a renewable energy has become as one of the most viable alternative resource of power generation due to some compensations of it such as cost-effective and ecofriendly. In condition monitoring system it is difficult to implementation due to many uncertain parameters. For that uncertain parameters the computational intelligence technique is implemented like Neuro fuzzy, Fuzzy logic and FMECA. For that technique optimization is performed. And literature review is conducted for condition monitoring, computational intelligence and optimization.

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Section: Condition Monitoring System (Cms)mentioning

confidence: 99%

“…The expected life cycle cost of two maintenance strategies is determined and compared by a stochastic simulation model, that the performance of a CMS should be taken into account in order to draw the right conclusions on the real economic value [12].…”

Section: Fig1 P-f Curvementioning

confidence: 99%

Computational Intelligence, Condition Monitoring and Optimization in Mechanical System- A Review

Kumar¹,

Ganesan²

2014

IJETT

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“…The use of data exploration is also reported for fault diagnosis in condition monitoring signal data, for instance, in vibration signal data collected through sensors attached to mechanical drives [5][6]. Sharma et al Developed methodology for system failure behavior and maintenance decision making, policy [7].…”

Section: Introductionmentioning

confidence: 99%

Mechanical Failure Analysis of a Rake Unloading System using FTA and FMECA

Singh¹

2017

IJMPERD

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Iron and Steel industries, raw materials are mostly transported, through the railway rakes.The railway provides some stipulated free time, for unloading the rakes and charges a penalty for the delay beyond the free time. This penalty charge increases the cost of the final products. This paper discusses the mechanical failure problem, which is the major cause of the delay in the unloading process, using Fault Tree Analysis (FTA) and Failure Mode Effect and Criticality Analysis (FMECA), to find the critical component of the failure, which helps the management to minimize the breakdowns.

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“…Therefore, CBM becomes useful to set maintenance policies even with different levels of monitoring restrictions. Compared to usual time-based maintenance strategies, condition monitoring systems offer significant potential to add economic value to spares management performance (Van Horenbeek, Van Ostaeyen, Duflou, & Pintelon, 2013).…”

Section: Ordering Decisions Using Conditional Reliability and Stochasmentioning

confidence: 99%

“…Compared to usual time-based maintenance strategies, condition monitoring systems offer significant potential to add economic value to spares management performance (Van Horenbeek et al, 2013). Particularly, this paper uses CBM models to calculate conditional reliability in order to make ordering or replacement decisions.…”

Section: Critical Spare Parts and Maintenance Strategymentioning

confidence: 99%

Integrated models for critical spare parts management in asset intensive industries

Ramos¹,

David²

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Spare parts are of key importance for equipment intensive industries -such as Mining, Aeronautic, or Defense-since their role is to efficiently support the operation of critical equipment and enhance system performance, thereby meeting business success.Organizations within such industries face continuous challenges to improve utilization, reduce costs, and manage risks. Miscalculating these decisions might lead to overstress on equipment and associated spare components, thus affecting availability, reliability, and system throughput. Critical spare parts therefore merit complex modeling. However, an asset management perspective -a systemic means of optimally managing resources to ensure sustainable business goals-has not been integrated into every vital decision stage of spares policies.In an effort to include this type of approach, this research has modeled the spares process from selection of the most important resources to supply chain requirements. The general objective of this thesis is to develop an asset management-based framework to optimize the life cycle of critical spare parts by integrating five key decision areas, namely: prioritization, ordering, replacement, maintenance outsourcing, and pool allocation. These areas are crucial to performance excellence for asset intensive firms.The resulting support system is documented by five ISI journal articles dealing with the key decision areas. The methodology is illustrated by an introduction, real-industry case studies, and sequential addressing of aims and contributions for each appended paper. They are summarized as follows. First, Paper I "Throughput centered prioritization of machines in transfer lines" delivers the graphical tool called System Efficiency Influence Diagram, which prioritizes the critical resources for system throughput considering intermediate buffers.Second, Paper II "Critical spare parts ordering decisions using conditional reliability and stochastic lead time" introduces the concept of Condition-Based Service Level to define the spares ordering time at which the system operation is sufficiently reliable to withstand lead time variability. Third, Paper III "Value-based optimization of intervention intervals for critical mining components" shows the influence of business value for accelerating versus postponing the optimal epoch to perform the spares replacement. Fourth, Paper IV "Optimizing maintenance service contracts under imperfect maintenance and a finite time horizon" sets contract conditions for motivating service receivers and external providers ii to reach win-win coordination. Lastly, Paper V "A decision-making framework to integrate maintenance contract conditions with critical spares management" profitably allocates the components pool within the maintenance service contract. The enriched models and graphical tools developed in these papers are useful for operations design and major planning.This thesis provides asset managers with integrated decision-making models to optimize the life cycle of critical spare par...

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Quantifying the added value of an imperfectly performing condition monitoring system—Application to a wind turbine gearbox

Cited by 40 publications

References 22 publications

Computational Intelligence, Condition Monitoring and Optimization in Mechanical System- A Review

Computational Intelligence, Condition Monitoring and Optimization in Mechanical System- A Review

Mechanical Failure Analysis of a Rake Unloading System using FTA and FMECA

Integrated models for critical spare parts management in asset intensive industries

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