A probabilistic characterization of adhesive wear in metals

Adhesive wear is one of the predominant mechanisms responsible for mechanical component failures that result in a huge economic loss. Adhesive wear has been studied; the deterministic model formulated by Archard is frequently used. However, its parameters, such as material-hardness and wear coeffici...

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Main Author: Qureshi, F.S. (author)
Other Authors: Sheikh, A.K. (author), unknown (author)
Format: article
Published: 1997
Subjects:
Online Access:https://eprints.kfupm.edu.sa/id/eprint/14673/1/14673_1.pdf
https://eprints.kfupm.edu.sa/id/eprint/14673/2/14673_2.doc
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author Qureshi, F.S.
author2 Sheikh, A.K.
unknown
author2_role author
author
author_facet Qureshi, F.S.
Sheikh, A.K.
unknown
author_role author
dc.creator.none.fl_str_mv Qureshi, F.S.
Sheikh, A.K.
unknown
dc.date.none.fl_str_mv 1997-03
2020
dc.format.none.fl_str_mv application/pdf
application/msword
dc.identifier.none.fl_str_mv https://eprints.kfupm.edu.sa/id/eprint/14673/1/14673_1.pdf
https://eprints.kfupm.edu.sa/id/eprint/14673/2/14673_2.doc
(1997) A probabilistic characterization of adhesive wear in metals. Reliability, IEEE Transactions on, 46.
dc.language.none.fl_str_mv en
en
dc.publisher.none.fl_str_mv IEEE
dc.relation.none.fl_str_mv https://eprints.kfupm.edu.sa/id/eprint/14673/
dc.rights.*.fl_str_mv info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Computer
dc.title.none.fl_str_mv A probabilistic characterization of adhesive wear in metals
dc.type.none.fl_str_mv Article
PeerReviewed
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
description Adhesive wear is one of the predominant mechanisms responsible for mechanical component failures that result in a huge economic loss. Adhesive wear has been studied; the deterministic model formulated by Archard is frequently used. However, its parameters, such as material-hardness and wear coefficient show a considerable variation around the nominal value; this variation necessitates a statistical framework for studying the wear law. This paper treats these parameters as probabilistic quantities. Investigation of the model involved an experiment consisting of a pin-on-bushing machine. Load and sliding speed are used as variables while the geometry and material of the friction couple are constant. The generated data are analyzed using simple statistical methods. The randomness of wear and hardness are best modeled by the Weibull distribution, whereas the wear coefficient is modeled by a log normal distribution. Scatter parameters and median life of wear are explored for various velocities as time progresses; the median life characteristics are mathematically modeled. The application of these models in accelerated wear testing is highlighted; accelerating by increasing the speed of operation provides a better extrapolation as compared to using heavier loads
eu_rights_str_mv openAccess
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id KFUPM_86c2c1c4e2fb64b6a725d06d24d95425
identifier_str_mv (1997) A probabilistic characterization of adhesive wear in metals. Reliability, IEEE Transactions on, 46.
language_invalid_str_mv en
network_acronym_str KFUPM
network_name_str King Fahd University of Petroleum and Minerals
oai_identifier_str oai::14673
publishDate 1997
publisher.none.fl_str_mv IEEE
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
spelling A probabilistic characterization of adhesive wear in metalsQureshi, F.S.Sheikh, A.K.unknownComputerAdhesive wear is one of the predominant mechanisms responsible for mechanical component failures that result in a huge economic loss. Adhesive wear has been studied; the deterministic model formulated by Archard is frequently used. However, its parameters, such as material-hardness and wear coefficient show a considerable variation around the nominal value; this variation necessitates a statistical framework for studying the wear law. This paper treats these parameters as probabilistic quantities. Investigation of the model involved an experiment consisting of a pin-on-bushing machine. Load and sliding speed are used as variables while the geometry and material of the friction couple are constant. The generated data are analyzed using simple statistical methods. The randomness of wear and hardness are best modeled by the Weibull distribution, whereas the wear coefficient is modeled by a log normal distribution. Scatter parameters and median life of wear are explored for various velocities as time progresses; the median life characteristics are mathematically modeled. The application of these models in accelerated wear testing is highlighted; accelerating by increasing the speed of operation provides a better extrapolation as compared to using heavier loadsIEEE1997-032020ArticlePeerReviewedinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfapplication/mswordhttps://eprints.kfupm.edu.sa/id/eprint/14673/1/14673_1.pdfhttps://eprints.kfupm.edu.sa/id/eprint/14673/2/14673_2.doc (1997) A probabilistic characterization of adhesive wear in metals. Reliability, IEEE Transactions on, 46. enenhttps://eprints.kfupm.edu.sa/id/eprint/14673/info:eu-repo/semantics/openAccessoai::146732019-11-01T14:06:54Z
spellingShingle A probabilistic characterization of adhesive wear in metals
Qureshi, F.S.
Computer
status_str publishedVersion
title A probabilistic characterization of adhesive wear in metals
title_full A probabilistic characterization of adhesive wear in metals
title_fullStr A probabilistic characterization of adhesive wear in metals
title_full_unstemmed A probabilistic characterization of adhesive wear in metals
title_short A probabilistic characterization of adhesive wear in metals
title_sort A probabilistic characterization of adhesive wear in metals
topic Computer
url https://eprints.kfupm.edu.sa/id/eprint/14673/1/14673_1.pdf
https://eprints.kfupm.edu.sa/id/eprint/14673/2/14673_2.doc