AMSAA Reliability Growth Guide

RésuméCe papier, dans le cadre du programme commun de recherche et technologie du CNES et de SNECMA, porte sur une méthodologie d'estimation de la fiabilité observée à partir de le retour d'expérience (REX) lors des essais de développement des propulseurs (moteurs-fusées). La méthode consiste une proposition du modèle de croissance de fiabilité qui doit prendre en compte le vieillissement des équipements modélisé par la loi de durée de vie (Weibull) suivant des essais de développement et des risques concurrents suivant les différents incidents des équipements des moteurs-fusées. La performance d'estimation de croissance de fiabilité du modèle proposé est étudié par le calcul de fiabilité des moteurs-fusées par rapport à une mission de vol et par la comparaison au modèle usuel de croissance de fiabilité (AMSAA). Le modèle a été ensuite appliqué à des données réelles d'essais de développement de moteur-fusées. SummaryThis paper, in the framework of common research with CNES and SNECMA, concerns a reliability estimation methodology observed from return on operating experience (REX) during development tests plan of rocket engines. This approach consists a proposal reliability growth model which takes into account the equipments ageing modelled by lifetime law (Weibull) following development tests and the concurrent risks following the different equipment incidents of rocket engines. In order to evaluate the performance of estimation of proposed reliability growth model, the reliability calculation of rocket-engines versus a mission is studied and a comparison with usual model of reliability growth (AMSAA) is pointed out. This method is applied on real case study of rocket engine development test plan.Communication 5C-1

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“…Les modèles d'AMSAA détaillés dans Broemm et al (2000) sont considérés comme un modèle benchmark très usuel par rapport à notre modèle.…”

Section: La Fonction De Log-vraisemblance Se Décompose Suivant Les Obunclassified

Modèle de croissance de fiabilité pour des systèmes réparables en essais de développement

Son¹,

Saintis²,

Guérin³

et al. 2015

Congrès Lambda Mu 19 De Maîtrise Des Risques Et Sûreté De Fonctionnement

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“…The first is the reliability growth tracking model found in [1] and [2]. The underlying assumption of the tracking model is that individual failures in a test event occur according to a nonhomogeneous Poisson process with a failure intensity represented by…”

Section: Crow Extended Modelmentioning

confidence: 99%

“…No Type-A modes are assumed in the projection component because they are accounted for in the tracking portion of the model. The extended model failure intensity is given in [2] as…”

Section: Crow Extended Modelmentioning

confidence: 99%

“…Depicting how the reliability changes throughout the developmental testing of the system is important, as it provides an indication of whether or not the system will be able to meet it requirements. These reliability depictions are usually made with established reliability growth models such as those specified in Military Handbook 189 [1] or the AMSAA Reliability Growth Guide [2]. The growth relationship depicted is between reliability and a continuous measure of test duration such as time or mileage.…”

Section: Introductionmentioning

confidence: 99%

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A reliability growth simulation test bed

Wayne¹

2009

2009 Annual Reliability and Maintainability Symposium

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This paper presents a reliability growth simulation test bed that is useful in examining the reliability growth of complex systems.It has many potential applications, including cost vs. reliability growth analyses and reliability growth program planning. The most significant application of the simulation though, is that it provides a method for examining the robustness of existing reliability growth models under varying assumptions and test conditions.The simulation allows for a user to more accurately model the test event, in that corrective action strategies and corrective action delay times and can be employed. Because these events tend to violate the assumptions of some models, two existing and widely used reliability growth models are examined under a variety of test conditions and assumptions. The simulated system reliabilities from the test bed are compared to the projections obtained from both the Crow Extended Model and the AMSAA Maturity Projection Model (AMPM).The results indicate that both models perform acceptably under test conditions that adhere to the assumptions of the models themselves. The performance of the Crow-Extended Model tends to degrade rapidly as the assumptions are violated, more specifically when the classification of modes is altered in any way. The AMPM appears to be robust to varying test conditions due to its limited assumptions. Other issues do exist though involving the selection of the proper form of the estimator which could have a significant impact on the accuracy of its projections.

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“…In [5] it is shown that the expression in (4) is the expected failure intensity due to all the modes not surfaced by t. To show this observe that the failure intensity due to these modes can be expressed as the random variable ) (t U Λ where…”

Section: Derived Reliability Growth Patternsmentioning

confidence: 99%

An approach to reliability growth planning based on failure mode discovery and correction using AMSAA projection methodology

Ellner¹,

Hall²

RAMS '06. Annual Reliability and Maintainability Symposium, 2006.

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Exact expressions for the expected number of surfaced failure modes and system failure intensity as functions of test time are presented under the assumption that the surfaced modes are mitigated through corrective actions. These exact expressions depend on a large number of parameters. Functional forms are derived to approximate these quantities that depend on only a few parameters. Such parsimonious approximations are suitable for developing reliability growth plans and portraying the associated planned growth path. Simulation results indicate that the functional form of the derived parsimonious approximations can adequately represent the expected reliability growth associated with a variety of patterns for the failure mode initial rates of occurrence. A sequence of increasing MTBF target values can be constructed from the parsimonious MTBF projection approximation based on the following:(1) planning parameters that determine the parsimonious approximation; (2) corrective action mean lag time with respect to implementation and; (3) test schedule that gives the number of planned Reliability, Availability, and Maintainability (RAM) test hours per month and specifies corrective action implementation periods.

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AMSAA Reliability Growth Guide

Cited by 22 publications

References 1 publication

Modèle de croissance de fiabilité pour des systèmes réparables en essais de développement

Modèle de croissance de fiabilité pour des systèmes réparables en essais de développement

A reliability growth simulation test bed

An approach to reliability growth planning based on failure mode discovery and correction using AMSAA projection methodology

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