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The Stryker Mobile Gun System (MGS) is a major, complex weapon system that presented a challenge in meeting its reliability requirement due to new technology revolving around the system's automatic ammunition handling system (AHS)...
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The Stryker Mobile Gun System (MGS) is a major, complex weapon system that presented a challenge in meeting its reliability requirement due to new technology revolving around the system's automatic ammunition handling system (AHS). However, as a result of a successful reliability growth management program, the Stryker MGS program experienced an unprecedented growth rate during developmental testing that led the program to meet its requirement. The program employed an effective systems engineering process to identify and implement effective corrective actions and adopted the Reliability Growth Analysis methodology to accurately track the resulting reliability growth. These tools provided the product manager with the information necessary to allocate resources and maintain support for the program throughout its development. Other similar complex systems may benefit by applying these processes and tools.
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Reliability growth testing, i.e. the 'growth' of reliability, is a consolidated systematic method used by Fiat Auto to increase and 'demonstrate' reliability while testing vehicles. If a new car model is not very different from th...
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Reliability growth testing, i.e. the 'growth' of reliability, is a consolidated systematic method used by Fiat Auto to increase and 'demonstrate' reliability while testing vehicles. If a new car model is not very different from the previous one (being used as reference), a single 'verification' experimental phase on the vehicles which is consistent with the end product may be sufficient for a reliability statistical demonstration. In this case, the resultant confidence interval may be very large, especially when we want to predict the in field failure frequency after applying corrective actions. Conversely, if the new product shows too many problems, we could obviously define, at any moment, a specific (and more demanding) reliability growth plan and restart the experiments. This paper suggests the cases in which we should choose a reliability growth test or a reliability verification test, whilst considering the total amount of design variations with respect to the reference model: completely new model, resryling, face lifting, etc.
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When performing system-level developmental testing, time and expenses generally warrant a small sample size for failure data. Upon failure discovery, redesigns and/or corrective actions can be implemented to improve system reliabi...
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When performing system-level developmental testing, time and expenses generally warrant a small sample size for failure data. Upon failure discovery, redesigns and/or corrective actions can be implemented to improve system reliability. Current methods for estimating reliability growth, namely the Crow (AMSAA) growth model, stipulate that parameter estimates have a great level of uncertainty when dealing with small sample sizes. For purposes of handling limited failure data, we propose the use of a modified GM(1,1) model to predict system reliability growth parameters and investigate how parameter estimates are affected by systems whose failures follow a poly-Weibull distribution. Monte-Carlo simulation is used to map the response surface of system reliability, and results are used to compare the accuracy of the modified GM(1,1) model to that of the AMSAA growth model. It is shown that with small sample sizes and multiple failure modes, the modified GM(1,1) model is more accurate than the AMSAA model for prediction of growth model parameters.
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Singpurwalla presents an insightful proposal on foundations of reliability [Statist. Sci. 31 (2016) 521-540], suggesting to consider reliability not as a probability but as a propensity, in particular as the unobservable parameter...
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Singpurwalla presents an insightful proposal on foundations of reliability [Statist. Sci. 31 (2016) 521-540], suggesting to consider reliability not as a probability but as a propensity, in particular as the unobservable parameter in De Finetti's famous representation theorem. One specific issue considered is reliability growth, with example scenario the performance of software as it evolves over time. We briefly discuss some related aspects, mainly based on applied research on statistical methods to support software testing and insights from our research on system reliability.
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Reliability growth models are commonly used in the Department of Defense (DoD) to plan, track, and project reliability during system acquisition and testing. We describe two commonly used classes of reliability growth models for c...
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Reliability growth models are commonly used in the Department of Defense (DoD) to plan, track, and project reliability during system acquisition and testing. We describe two commonly used classes of reliability growth models for continuous failure time data and the metrics appropriate for their use. We also present two Bayesian reliability growth models that are based on the DoD models. The Bayesian models are easily interpretable in a statistical framework, which supports estimation and uncertainty quantification. Our goal is to provide a practical understanding of the development, implementation, and use of reliability growth models across a sequence of DoD testing events.
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This paper presents a new method for projecting the reliability growth of a complex continuously operating system. The model allows for arbitrary corrective action strategies, and it differs from other models of this type by using...
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This paper presents a new method for projecting the reliability growth of a complex continuously operating system. The model allows for arbitrary corrective action strategies, and it differs from other models of this type by using all available data rather than failure mode first occurrence times only. It also differs from other reliability growth projection models in that it provides a complete inference framework via the posterior distribution on the system failure intensity. A unique feature of this approach relative to other Bayesian techniques is the analytic expression for the failure intensity contribution from unobserved failure modes. Expressions for estimating the initial failure intensity, growth potential failure intensity, and the cumulative number of failure modes expected in future testing are also developed. Extensions to the basic framework are also developed. The first accounts for multiple systems under test, and the second develops the posterior distribution while allowing for uncertainty on the Fix Effectiveness Factor values that are assessed. Two separate goodness-of-fit procedures are presented for assessing the appropriateness of the underlying model assumptions.
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Relying on reliability growth testing to improve system design is neither usually effective nor efficient. Instead it is important to design in reliability. This requires models to estimate reliability growth in the design that ca...
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Relying on reliability growth testing to improve system design is neither usually effective nor efficient. Instead it is important to design in reliability. This requires models to estimate reliability growth in the design that can be used to assess whether goal reliability will be achieved within the target timescale for the design process. Many models have been developed for analysis of reliability growth on test, but there has been much less attention given to reliability growth in design. This paper describes and compares two models: one motivated by the practical engineering process; the other by extending the reasoning of statistical reliability growth modelling. Both models are referenced in the recently revised edition of international standard IEC 61164. However, there has been no reported evaluation of their properties. Therefore, this paper explores the commonalities and differences between these models through an assessment of their logic and their application to an industrial example. Recommendations are given for the use of reliability growth models to aid management of the design process and to inform product development.
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Reliability demonstration test (RDT) is a critical and necessary step before the acceptance of an industrial system. Generally, a ROT focuses on designing a test plan through which one can judge whether the system reliability indi...
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Reliability demonstration test (RDT) is a critical and necessary step before the acceptance of an industrial system. Generally, a ROT focuses on designing a test plan through which one can judge whether the system reliability indices meet specific requirements. There are many established RDT plans, but few have incorporated the reliability growth aspects of the corresponding products. In this paper, we examine a comprehensive test plan that involves information concerning the reliability growth stage. An approach for RDT under the assumption of the power-law model is proposed. It combines data related to the growth stage with those pertaining to the test stage of the product to reduce the cost of the test. Through simulation studies and numerical examples, we illustrate the characteristics of the test plan and significant reduction in test costs through our approach. Copyright (C) 2017 John Wiley & Sons, Ltd.
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Sustainment costs typically represent 60 - 70 percent of a programs life-cycle costs. System reliability is a key component of maximizing system availability and minimizing life-cycle costs. Key areas affected by system reliabilit...
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Sustainment costs typically represent 60 - 70 percent of a programs life-cycle costs. System reliability is a key component of maximizing system availability and minimizing life-cycle costs. Key areas affected by system reliability changes include maintenance labor, repair material, and spares. Overall, an improvement in reliability can represent a significant savings in the support costs for any major weapon system (often in the tens of hundreds or millions of dollars or higher). The Reliability Program Scorecard and Reliability Growth Planning and Assessment Models are two methods which can be implemented to assist management in meeting system reliability requirements and enable the implementation of both Office of the Secretary of Defense and Army reliability policies (Directive-Type Memorandum 11-003 entitled "Reliability Analysis, Planning, Tracking, and Reporting," 21 March 2011 [DOD 2011], and the Army Reliability Policy, December 2007, respectively [Bolton 2007]).
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