Reliability metrics and the REMM model

James, Ian; Marshall, Jessica; Evans, Michael; Newman, B.

doi:10.1109/rams.2004.1285493

Cited by 5 publications

(6 citation statements)

References 3 publications

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“…While it is acknowledged by designers of hardware systems that the customer's requirements of the item are of paramount importance [71,111], there are few recent published articles compared with requirements setting for software systems [108]. In our experience with hardware systems it seems that systematic modeling is not performed in the derivation of requirements, and historical precedent (i.e., the requirements that were set for the last version) is used as an alternative.…”

Section: Requirements Capture and Concept Definitionmentioning

confidence: 99%

Expert Elicitation for Reliable System Design

Bedford¹,

Quigley²,

Walls³

2006

Statist. Sci.

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This paper reviews the role of expert judgement to support reliability assessments within the systems engineering design process. Generic design processes are described to give the context and a discussion is given about the nature of the reliability assessments required in the different systems engineering phases. It is argued that, as far as meeting reliability requirements is concerned, the whole design process is more akin to a statistical control process than to a straightforward statistical problem of assessing an unknown distribution. This leads to features of the expert judgement problem in the design context which are substantially different from those seen, for example, in risk assessment. In particular, the role of experts in problem structuring and in developing failure mitigation options is much more prominent, and there is a need to take into account the reliability potential for future mitigation measures downstream in the system life cycle. An overview is given of the stakeholders typically involved in large scale systems engineering design projects, and this is used to argue the need for methods that expose potential judgemental biases in order to generate analyses that can be said to provide rational consensus about uncertainties. Finally, a number of key points are developed with the aim of moving toward a framework that provides a holistic method for tracking reliability assessment through the design process.Comment: This paper commented in: [arXiv:0708.0285], [arXiv:0708.0287], [arXiv:0708.0288]. Rejoinder in [arXiv:0708.0293]. Published at http://dx.doi.org/10.1214/088342306000000510 in the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

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Section: Requirements Capture and Concept Definitionmentioning

confidence: 99%

Expert Elicitation for Reliable System Design

Bedford¹,

Quigley²,

Walls³

2006

Statist. Sci.

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show abstract

“…An example of the application of reliability growth models to the estimation of the reliability metrics of telecommunication switches was presented in [9]. However, once the software is deployed in production, reliability is usually estimated by observing actual failures and estimating the overall system failure rate [7]. When the system under study is composed of very reliable nodes, failures are likely to be rare events, and the failure sample size is usually small.…”

Section: Introductionmentioning

confidence: 99%

“…In [7] important issues related to reliability metrics interpretation by designers, project managers and other stakeholders within a project organization were discussed. The authors showed how difference in interpretation of reliability metrics could lead to increased costs to the organization due to misunderstandings of the meaning of Mean Time to Failure and its confusion with measurements of failure rates that were based on small samples.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, the authors recommended the use of statistically-proven approaches for reliability modeling. In [7], it was shown that the shape of the reliability function is usually a bathtub curve as shown in Figure 1. Therefore, it is important for data analysis approaches to statistically validate that the nodes under test are after infant-mortality phase and before wearout phase.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, it is important for data analysis approaches to statistically validate that the nodes under test are after infant-mortality phase and before wearout phase. It was also reported in [7] that a twelve-month aggregate average should be used to estimate the constant hazard rate. As the testing period in the case study presented in this paper was three months, we used a combination of vendor data and failure data to ensure the nodes under test were in the constant failure rate phase and to adjust for error introduced by the short three-month reliability period for data collection.…”

Section: Introductionmentioning

confidence: 99%

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Reliability estimation for large distributed software systems

Avritzer

Duarte

Leão

et al. 2008

Proceedings of the 2008 Conference of the Center for Advanced Studies on Collaborative Research Meeting of Minds - CASCON '08

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No Fault Found events in maintenance engineering Part 1: Current trends, implications and organizational practices

Khan

Phillips

Jennions

et al. 2014

Reliability Engineering & System Safety

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This paper reviews the literature dealing with the nature and characteristics of no-fault found events within maintenance lines. Increasing systems complexities have seen a rise in the number of unknown faults that are being reported during operational service. Units tagged as 'No-Fault Found' are evidence that a serviceable component was removed, and attempts to troubleshoot the root cause have been unsuccessful. This scenario worsens when faults occurring at the component level are intermittent in nature. Here, the paper describes the prominent issues that have persisted across a variety of industrial applications and processes for decades. Some recent developments including standards, financial implications and safety concerns are highlighted.

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Reliability metrics and the REMM model

Cited by 5 publications

References 3 publications

Expert Elicitation for Reliable System Design

Expert Elicitation for Reliable System Design

Reliability estimation for large distributed software systems

No Fault Found events in maintenance engineering Part 1: Current trends, implications and organizational practices

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