Criticality analysis revisited

Moss, T. R.; Woodhouse, Jin

doi:10.1002/(sici)1099-1638(199903/04)15:2<117::aid-qre238>3.0.co;2-i

Cited by 42 publications

(8 citation statements)

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“…The process is based on risk analysis as a function of consequence and likelihood of failure occurring-Failure Modes, Effects and Criticality Analysis (FMECA) (e.g. Moss & Woodhouse 1998). Values for both consequence and likelihood are developed by considering a number of pipe flow and catchment characteristics which are readily available from a combination of local government and wastewater company reports.…”

Section: Introductionmentioning

confidence: 99%

Including public perception data in the evaluation of the consequences of sewerage derived urban flooding

Arthur

Crow

Karikas

2009

Water Science and Technology

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This text reports research which was undertaken to assess the failure consequences associated with sewerage systems. In an effort to move away from considering only flood volume, depth or extent, the text will focus on how a survey of public opinion was used to inform the development of a consequence scoring methodology. The failure consequences considered range from internal flooding of properties, to road closure, environmental damage and odour problems. The text reports the extent to which experience of flooding influences perceptions of failure consequence and sewerage system management. It is also outlined how this data was used, along with other data sources, to construct an objective scoring process that can be used to evaluate failure consequence and readily prioritise sewerage maintenance.

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Section: Introductionmentioning

confidence: 99%

Including public perception data in the evaluation of the consequences of sewerage derived urban flooding

Arthur

Crow

Karikas

2009

Water Science and Technology

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“…The process is based on risk analysis as a function of both consequence and likelihood of failure occurring-failure modes, effects and criticality analysis (FMECA). 9 Values for both consequence and likelihood are developed by considering a number of pipe flow and catchment characteristics that are readily available from a combination of local government and wastewater company reports. Such data may then be used to produce a rank of pipes that are at greatest 'risk' from flooding.…”

Section: Introductionmentioning

confidence: 99%

Understanding blockage formation in combined sewer networks

Arthur

Crow

Pedezert³

2008

Proceedings of the Institution of Civil Engineers - Water Manag

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This paper documents a key part of the development of a risk analysis process that may be used as a tool to manage maintenance expenditure within the context of 'serviceability' to customers, the public and the environment. Against the background of poor availability of reliable data, the text outlines the basis of a methodology that can be used to model blockage likelihood in combined sewers with limited information and without the need for additional data gathering. Specifically, the work reported here relates primarily to research undertaken to better understand what networkand catchment-specific factors influence the formation of blockages that lead to flooding in combined and foul drainage systems. The role of each of these factors is considered in turn and the significance of their impact is estimated.

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“…This requires a vast amount of expert knowledge and expertise. The idea is to represent O, S, and D using linguistic variables and rank them using fuzzy numbers (e.g., triangular or trapezoidal fuzzy numbers) instead of crisp numbers [38], [39]. To do that, the first step is to define membership functions for the three risk factors O, S, and D as shown in figure 9, that is an example of fuzzy assessment for severity S index.…”

Section: Fuzzy and Multi-criteria Approachesmentioning

confidence: 99%

A Critical Comparison of Alternative Risk Priority Numbers in Failure Modes, Effects, and Criticality Analysis

2019

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Risk priority number (RPN) is a widely used approach, and it is a powerful means to assess the criticality of modes in a failure modes, effects, and criticality analysis (FMECA) worksheet. In the application of the traditional FMECA, the RPN is determined to rank the failure modes; however, the method has been criticized several times for having many drawbacks and weaknesses, such as the presence of gaps in the range of admissible values, the duplicates value provided by different combinations of the base factors, and the high sensitivity to small changes. This paper analyses and compares some alternative RPN formulation proposed in the literature to overcome these limits. This paper takes into account only the alternative RPN, which proposes a powerful solution without increasing the computational complexity and remaining coherent to the classical idea included in the international standard IEC 60812. In order to compare the advantages and disadvantages of these alternative RPNs, an FMECA was developed for a heating, ventilation, and air condition (HVAC) system in railway application. The critical analysis of the comparison can provide recommendations and suggestions regarding the choice of the alternative RPN based on the type of application. Finally, this paper takes into account the scales reduction of possible values related to the parameters (i.e., occurrence, severity, and detection), which influence the assessment of the RPN. This approach allows the designers to mitigate the drawbacks related to the full scale and provide an easier and faster assessment of the scores to evaluate the criticality analysis and prioritization. INDEX TERMS FMECA, railway engineering, reliability theory, risk priority number.

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Criticality analysis revisited

Cited by 42 publications

References 1 publication

Including public perception data in the evaluation of the consequences of sewerage derived urban flooding

Including public perception data in the evaluation of the consequences of sewerage derived urban flooding

Understanding blockage formation in combined sewer networks

A Critical Comparison of Alternative Risk Priority Numbers in Failure Modes, Effects, and Criticality Analysis

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