Accession Number : ADA591776


Title :   Modeling Reliability Growth in Accelerated Stress Testing


Descriptive Note : Doctoral thesis


Corporate Author : AIR FORCE INSTITUTE OF TECHNOLOGY WRIGHT-PATTERSON AFB OH GRADUATE SCHOOL OF ENGINEERING AND MANAGEMENT


Personal Author(s) : Freels, Jason K


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a591776.pdf


Report Date : Dec 2013


Pagination or Media Count : 240


Abstract : Qualitative accelerated test methods improve system reliability by identifying and removing initial design flaws. However, schedule and cost constraints often preclude sufficient testing to generate a meaningful reliability estimate from the data obtained in these tests. In this dissertation a modified accelerated life test is proposed to assess the likelihood of attaining a reliability requirement based on tests of early system prototypes. Assuming each prototype contains an unknown number of independent competing failure modes whose respective times to occurrence are governed by a distinct Weibull law, the observed failure data from this qualitative test are shown to follow a poly-Weibull distribution. However, using an agent-based Monte Carlo simulation, it is shown that for typical products subjected to qualitative testing, the failure observations result from a homogenous subset of the total number of latent failure modes and the failure data can be adequately modeled with a Weibull distribution. Thus, the projected system reliability after implementing corrective action to remove one or more failure modes can be estimated using established quantitative accelerated test data analysis methods. Our results suggest that a significant cost and time savings may be realized using the proposed method to signal the need to reassess a product?s design or reallocate test resources to avoid unnecessary maintenance or redesigns. Further, the proposed approach allows a significant reduction in the test time and sample size required to estimate the risk of meeting a reliability requirement over current quantitative accelerated life test techniques. Additional contributions include a numerical and analytical procedure for obtaining the maximum likelihood parameter estimates and observed Fisher information matrix components for the generalized poly-Weibull distribution. Using this procedure, we show that the poly-Weibull distribution outperforms the best-fit modified Weibull a


Descriptors :   *AIR FORCE EQUIPMENT , *AIR FORCE OPERATIONS , *INVENTORY CONTROL , ACCELERATED TESTING , FAILURE , GROWTH(GENERAL) , MONTE CARLO METHOD , PROTOTYPES , RELIABILITY , STRESS TESTING , SYSTEMS ENGINEERING , THESES , WEIBULL DENSITY FUNCTIONS


Subject Categories : Logistics, Military Facilities and Supplies


Distribution Statement : APPROVED FOR PUBLIC RELEASE