A stochastic modeling framework for environmental stress screening of multicomponent systems.

Persistent Link:
http://hdl.handle.net/10150/187166
Title:
A stochastic modeling framework for environmental stress screening of multicomponent systems.
Author:
Pohl, Edward August.
Issue Date:
1995
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
Environmental stress screening (ESS) is employed to reduce, if not eliminate, the occurrence of early field failures. In this dissertation, a general stochastic modeling framework is presented for multi-component systems. Environmental stress screening can be performed at one or more assembly levels for a system. Systems are modeled as a series-series collection of components and connections. Components and connections are assumed to come from good and substandard populations and their time to failure distributions are modeled with mixture distributions. ESS models currently found in the literature assume that time to failure distributions are mixtures of exponentials. This dissertation extends previous work by examining mixtures of Weibull distributions for both components and connections. The mixed Weibull distribution is used to examine how screening strategies change when wear-out mechanisms are present. A further generalization is made by modeling components and connections with mixtures of phase-type distributions. Optimal screening strategies are developed using a variety of criteria. First, a life cycle cost model is developed for a general series-series multiple assembly level system. This is the first multi-component, multi-screening level cost model with imperfect failure detection to appear in the literature. Failure detection capability is shown to have a significant impact on the optimal screening strategy. Other criteria examined includes system mean residual life and system mission reliability. Finally, the impact of a systems structure on optimal screening strategies is explored.
Type:
text; Dissertation-Reproduction (electronic)
Degree Name:
Ph.D.
Degree Level:
doctoral
Degree Program:
Systems and Industrial Engineering; Graduate College
Degree Grantor:
University of Arizona
Committee Chair:
Dietrich, Duane L.

Full metadata record

DC FieldValue Language
dc.language.isoenen_US
dc.titleA stochastic modeling framework for environmental stress screening of multicomponent systems.en_US
dc.creatorPohl, Edward August.en_US
dc.contributor.authorPohl, Edward August.en_US
dc.date.issued1995en_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.abstractEnvironmental stress screening (ESS) is employed to reduce, if not eliminate, the occurrence of early field failures. In this dissertation, a general stochastic modeling framework is presented for multi-component systems. Environmental stress screening can be performed at one or more assembly levels for a system. Systems are modeled as a series-series collection of components and connections. Components and connections are assumed to come from good and substandard populations and their time to failure distributions are modeled with mixture distributions. ESS models currently found in the literature assume that time to failure distributions are mixtures of exponentials. This dissertation extends previous work by examining mixtures of Weibull distributions for both components and connections. The mixed Weibull distribution is used to examine how screening strategies change when wear-out mechanisms are present. A further generalization is made by modeling components and connections with mixtures of phase-type distributions. Optimal screening strategies are developed using a variety of criteria. First, a life cycle cost model is developed for a general series-series multiple assembly level system. This is the first multi-component, multi-screening level cost model with imperfect failure detection to appear in the literature. Failure detection capability is shown to have a significant impact on the optimal screening strategy. Other criteria examined includes system mean residual life and system mission reliability. Finally, the impact of a systems structure on optimal screening strategies is explored.en_US
dc.typetexten_US
dc.typeDissertation-Reproduction (electronic)en_US
thesis.degree.namePh.D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineSystems and Industrial Engineeringen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.chairDietrich, Duane L.en_US
dc.contributor.committeememberSzidarovszky, Ferencen_US
dc.contributor.committeememberFernandez, Emmanuelen_US
dc.contributor.committeememberWirsching, Paulen_US
dc.contributor.committeememberKececioglu, Dimitrien_US
dc.identifier.proquest9534673en_US
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