Valve Criticality Modeling

Casey, R. E.; Boulos, Paul F.; Orr, Chun Hou; Bros, Christopher M.

doi:10.1061/40941(247)32

Cited by 5 publications

(4 citation statements)

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“…Valve criticality analysis can be determined using various methodologies. One of the proposed methodologies can be found in [18]. The methodology proposed was intended to identify critical valves in the company's water supply network based on their potential impact on customer service levels.…”

Section: Discussionmentioning

confidence: 99%

The application of OREDA (offshore reliability data) in developing valve criticality analysis criteria

Priyanta,

Zaman,

Semin

2024

IOP Conf. Ser.: Earth Environ. Sci.

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In oil and gas processing plants, extensive networks of hundreds to thousands of valves are vital in controlling the entire process. However, not all valves have the same importance in process control. Therefore, identifying and prioritizing critical valves is essential for efficient and safe operation. Assessing the importance of valves requires a risk-based approach. However, quantifying the associated risks becomes challenging, especially when limited field data makes it difficult to model the probability of valve failure. One possible solution is to use Offshore Reliability Data (OREDA) as a valuable failure probability data source. OREDA provides valuable insight into historical failure and performance data related to oil and gas equipment such as valves. To go one step further, the new proposal presented in this paper includes implementing a modified OREDA approach that considers the cumulative operating time of the valve. By considering cumulative operating hours, a more comprehensive and accurate assessment of failure probability can be achieved, enabling more informed decision-making regarding valve criticality and prioritization of maintenance.

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Section: Discussionmentioning

confidence: 99%

The application of OREDA (offshore reliability data) in developing valve criticality analysis criteria

Priyanta,

Zaman,

Semin

2024

IOP Conf. Ser.: Earth Environ. Sci.

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“…Generating is about the analysis of the failure occurrence; whereas inferring is about making a diagnosis based on the collected data. The goal of prediction is to forecast the state of the network based on current and historical data [8][9][10]. Using a brute-force algorithm and analyzing all possible cases of one or more failures that occur simultaneously with a different number of available valves using conventional software would require the creation of separate simulation models for each case.…”

Section: Introductionmentioning

confidence: 99%

Bulletin of the Polish Academy of Sciences: Technical Sciences

Antonowicz

Urbaniak

2022

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The article discusses an example of the use of graph search algorithms with the trace of water analysis and aggregation of failures in the occurrence of a large number of failures in the water supply system (WSS). In the event of a disaster, based on the water distribution system (WDS) network model, information about detected failures, the condition and location of valves, the number of repair teams, criticality analysis, the coefficient of prioritization of individual network elements, and selected objective function, the algorithm proposes the order of repairing the failures. The approach proposed by the authors of the article assumes the selection of the following objective functions: minimizing the time of lack of access to drinking water (with or without prioritization) and minimizing failure repair time (with or without failure aggregation). The algorithm was tested on three different water networks (small, medium, and large numbers of nodes) and three different scenarios (different numbers of failures and valves in the water network) for each selected water network. The results were compared to a valve designation approach for closure using an adjacency matrix and a strategic valve management model (SVMM).

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“…This inevitably implies that some valves are more critical than others. Valve criticality is based on the probability of disruption occurring and the consequence of each valve operation with respect to the number of disconnected properties or those receiving a poor level of service (Casey et al, 2006). Similarly, pipe criticality is based on the probability of disruption occurring and consequence of each pipe isolation in the event of a burst or an emergency, with respect to the number of disconnected properties or those receiving a poor level of service.…”

Section: Introductionmentioning

confidence: 99%

“…The software offers various means of presenting, viewing and evaluating the results of a criticality analysis. Casey et al (2006) described the process of critical network valve identification and determining the impact of unplanned interruptions to customer supply around a central concept referred to as a pound. They described the pound as a collection of network components impounded by two or more closeable valves in an attempt to isolate mains, for example when there is a burst.…”

Section: Introductionmentioning

confidence: 99%

Efficient Approach to Targeted Asset Maintenance and Network Management for Water Utilities

Kalungi¹,

Croxton²

2011

proc water environ fed

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Prioritisation of network assets for routine maintenance is a complex exercise. Failure to operate key valves or to isolate critical network pipes during planned or emergency work on the network could have a significant impact on the level of service for customers in terms of disruption due to flooding, lack of water or very low pressure. The situation is further complicated by the fact that there are several thousand network valves and water utilities have a finite maintenance budget. This paper presents a case study in which an automated approach is used to identify the most critical network assets in order to prioritise them for maintenance, improve serviceability and reduce customer complaints. In the absence of this type of modelling methodology, the Water Utility has to rely on the experience of operators to identify critical assets without clear visibility of the consequence of failure.

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Valve Criticality Modeling

Cited by 5 publications

References 0 publications

The application of OREDA (offshore reliability data) in developing valve criticality analysis criteria

The application of OREDA (offshore reliability data) in developing valve criticality analysis criteria

Bulletin of the Polish Academy of Sciences: Technical Sciences

Efficient Approach to Targeted Asset Maintenance and Network Management for Water Utilities

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