Degradation models and implied lifetime distributions
In experiments where failure times are sparse, degradation analysis is useful for the analysis of failure time distributions in reliability studies. This research investigates the link between a practitioner's selected degradation model and the resulting lifetime model. Simple additive and mult...
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| Published in | Reliability engineering & system safety Vol. 92; no. 5; pp. 601 - 608 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
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Oxford
Elsevier Ltd
01.05.2007
Elsevier |
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| Abstract | In experiments where failure times are sparse, degradation analysis is useful for the analysis of failure time distributions in reliability studies. This research investigates the link between a practitioner's selected degradation model and the resulting lifetime model. Simple additive and multiplicative models with single random effects are featured. Results show that seemingly innocuous assumptions of the degradation path create surprising restrictions on the lifetime distribution. These constraints are described in terms of failure rate and distribution classes. |
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| AbstractList | In experiments where failure times are sparse, degradation analysis is useful for the analysis of failure time distributions in reliability studies. This research investigates the link between a practitioner's selected degradation model and the resulting lifetime model. Simple additive and multiplicative models with single random effects are featured. Results show that seemingly innocuous assumptions of the degradation path create surprising restrictions on the lifetime distribution. These constraints are described in terms of failure rate and distribution classes. |
| Author | Kuo, Way Kvam, Paul H. Bae, Suk Joo |
| Author_xml | – sequence: 1 givenname: Suk Joo surname: Bae fullname: Bae, Suk Joo organization: Department of Industrial Engineering, Hanyang University, Seoul, Korea – sequence: 2 givenname: Way surname: Kuo fullname: Kuo, Way organization: Department of Electrical & Computer Engineering, The University of Tennessee, Knoxville, USA – sequence: 3 givenname: Paul H. surname: Kvam fullname: Kvam, Paul H. email: pkvam@isye.gatech.edu organization: School of Industrial & Systems Engineering, Georgia Institute of Technology, USA |
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| Cites_doi | 10.2307/3556181 10.2307/1427627 10.2307/1271503 10.1063/1.357062 10.2307/1269661 10.1198/004017004000000464 10.1109/TR.1981.5221168 10.1002/qre.524 10.1002/1520-6750(198712)34:6<823::AID-NAV3220340607>3.0.CO;2-R |
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| Keywords | Stochastic ordering Bathtub and increasing failure rates Random effects Additive model Probabilistic approach Durability Failure rate Modeling Lifetime Break up time Failure analysis Ordering Random effect Reliability Time analysis |
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| SubjectTerms | Additive model Applied sciences Bathtub and increasing failure rates Exact sciences and technology Operational research and scientific management Operational research. Management science Random effects Reliability theory. Replacement problems Stochastic ordering |
| Title | Degradation models and implied lifetime distributions |
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