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Failure Data (failure + data)

Distribution by Scientific Domains

Mathematics and Statistics	60%

Selected Abstracts

Control Charts for Monitoring Field Failure Data

QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, Issue 7 2006
Robert G. Batson
Abstract One responsibility of the reliability engineer is to monitor failure trends for fielded units to confirm that pre-production life testing results remain valid. This research suggests an approach that is computationally simple and can be used with a small number of failures per observation period. The approach is based on converting failure time data from fielded units to normal distribution data, using simple logarithmic or power transformations. Appropriate normalizing transformations for the classic life distributions (exponential, lognormal, and Weibull) are identified from the literature. Samples of size 500 field failure times are generated for seven different lifetime distributions (normal, lognormal, exponential, and four Weibulls of various shapes). Various control charts are then tested under three sampling schemes (individual, fixed, and random) and three system reliability degradations (large step, small step, and linear decrease in mean time between failures (MTBF)). The results of these tests are converted to performance measures of time to first out-of-control signal and persistence of signal after out-of-control status begins. Three of the well-known Western Electric sensitizing rules are used to recognize the assignable cause signals. Based on this testing, the ,X -chart with fixed sample size is the best overall for field failure monitoring, although the individual chart was better for the transformed exponential and another highly-skewed Weibull. As expected, the linear decrease in MTBF is the most difficult change for any of the charts to detect. Copyright © 2005 John Wiley & Sons, Ltd. [source]

Parameter Estimation for Partially Complete Time and Type of Failure Data

BIOMETRICAL JOURNAL, Issue 2 2004
Debasis Kundu
Abstract The theory of competing risks has been developed to asses a specific risk in presence of other risk factors. In this paper we consider the parametric estimation of different failure modes under partially complete time and type of failure data using latent failure times and cause specific hazard functions models. Uniformly minimum variance unbiased estimators and maximum likelihood estimators are obtained when latent failure times and cause specific hazard functions are exponentially distributed. We also consider the case when they follow Weibull distributions. One data set is used to illustrate the proposed techniques. (© 2004 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [source]

Piecewise analysis and modeling of circuit pack temperature cycling data

BELL LABS TECHNICAL JOURNAL, Issue 3 2006
Toby Joyce
Temperature cycling environmental stress testing (EST) of circuit packs is a standard test procedure for the precipitation of latent defects in order to minimize early product lifecycle customer returns. EST is an expensive, energy-intensive bottleneck in the manufacturing process, one that is based on empiricisms that may be out of date. This presents great opportunity for optimization and test cost reduction. This paper describes the characterization of temperature cycling through analysis and modeling of process data in order to optimize the test parameters,ramp rate, temperature extremes, dwell times, and number of cycles. Failure data from circuit packs tested at a Lucent facility is analyzed using a regression technique and graphical inspection. The dwell and ramp periods of the test are considered in a piecewise manner. A cost model is applied based on distributions fitted to the failure data. The analysis yields a methodology for the dynamic, value-based optimization of temperature cycling EST. © 2006 Lucent Technologies Inc. [source]

Network reliability assessment in a random environment

NAVAL RESEARCH LOGISTICS: AN INTERNATIONAL JOURNAL, Issue 6 2003
S. Özekici
Abstract In this paper we consider networks that consist of components operating under a randomly changing common environment. Our work is motivated by power system networks that are subject to fluctuating weather conditions over time that affect the performance of the network. We develop a general setup for any network that is subject to such environment and present results for network reliability assessment under two repair scenarios. We also present Bayesian analysis of network failure data and illustrate how reliability predictions can be obtained for the network. © 2003 Wiley Periodicals, Inc. Naval Research Logistics 50: 574,591, 2003 [source]

Refined Rank Regression Method with Censors

QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, Issue 7 2004
Wendai Wang
Abstract Reliability engineers often face failure data with suspensions. The rank regression method with an approach introduced by Johnson has been commonly used to handle data with suspensions in engineering practice and commercial software. However, the Johnson method makes partial use of suspension information only,the positions of suspensions, not the exact times to suspensions. A new approach for rank regression with censored data is proposed in this paper, which makes full use of suspension information. Taking advantage of the parametric approach, the refined rank regression obtains the ,exact' mean order number for each failure point in the sample. With the ,exact' mean order number, the proposed method gives the ,best' fit to sample data for an assumed times-to-failure distribution. This refined rank regression is simple to implement and appears to have good statistical and convergence properties. An example is provided to illustrate the proposed method. Copyright © 2004 John Wiley & Sons, Ltd. [source]

A non-parametric approach to software reliability

APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY, Issue 1 2004
Axel Gandy
Abstract In this paper we present a new, non-parametric approach to software reliability. It is based on a multivariate counting process with additive intensity, incorporating covariates and including several projects in one model. Furthermore, we present ways to obtain failure data from the development of open source software. We analyse a data set from this source and consider several choices of covariates. We are able to observe a different impact of recently added and older source code onto the failure intensity. Copyright © 2004 John Wiley & Sons, Ltd. [source]

On testing of parameters in modulated power law process

APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY, Issue 4 2001
K. Muralidharan
Abstract The modulated power law process (MPLP) is often used to model failure data from repairable system, when both renewal type behaviour and time trends are present. The MPLP allows for the failure rate of a system to be affected by the failure and repair. Since the MLEs of the estimates do not have closed form expressions, they have to be approximated, and hence deriving a test procedure will be difficult. Black and Rigdon (1996) have proposed asymptotic MLEs and asymptotic likelihood ratio tests for the parameters which also do not have closed form expressions and hence are not easy for application. In this paper, we derive a closed form expression for the test statistics which is simple and easy to apply for testing (i) H0: ,=1 versus H1: ,,1 when , is known and (ii) H0: (,=1 and ,=1) versus H1: (,,1 or ,,1). The simulation study for percentiles and powers are given. We also compare the performance of the test with that of Black and Rigdon's (1996) test. Some numerical examples are also provided to illustrate the testing procedures. Copyright © 2001 John Wiley & Sons, Ltd. [source]

Piecewise analysis and modeling of circuit pack temperature cycling data

Parameter Estimation for Partially Complete Time and Type of Failure Data

Capture,Recapture Studies Using Radio Telemetry with Premature Radio-Tag Failure

BIOMETRICS, Issue 3 2005
Laura Cowen
Summary Radio tags, because of their high detectability, are often used in capture,recapture studies. A key assumption is that radio tags do not cease functioning during the study. Radio-tag failure before the end of a study can lead to underestimates of survival rates. We develop a model to incorporate secondary radio-tag failure data. This model was applied to chinook smolts (Oncorhynchus tshawytscha) on the Columbia River, Washington. Estimates of fish survival from this model were much larger than those from the standard Cormack,Jolly,Seber analysis. [source]