An Ordering Decision-Making Approach on Spare Parts for Civil Aircraft Based on a One-Sample Prediction
Ordering decision-making on spare parts is crucial in maximizing aircraft utilization and minimizing operating costs. This paper develops an approach of ordering decision-making for civil aircraft spare parts based on a one-sample prediction. Engineering background for line replace units, failure/re...
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Veröffentlicht in: | IEEE access 2018-01, Vol.6, p.27790-27795 |
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description | Ordering decision-making on spare parts is crucial in maximizing aircraft utilization and minimizing operating costs. This paper develops an approach of ordering decision-making for civil aircraft spare parts based on a one-sample prediction. Engineering background for line replace units, failure/replace processes, and spare parts requirements are represented. The model for future failure time is proposed based on the conditional probability density function of the failure time. A Weibull process with failure truncated and time truncated is employed to establish the prediction model. The point estimates and prediction bounds for future failure time are provided. Moreover, a prediction procedure for spare parts is investigated by identifying the ordering time and ordering quantity. Finally, a case study illustrates the developed method by predicting the spare parts as well as future failure time for engine-driven pumps. The predicted results are compared with the reality to demonstrate the effectiveness of the developed method. |
doi_str_mv | 10.1109/ACCESS.2018.2818404 |
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This paper develops an approach of ordering decision-making for civil aircraft spare parts based on a one-sample prediction. Engineering background for line replace units, failure/replace processes, and spare parts requirements are represented. The model for future failure time is proposed based on the conditional probability density function of the failure time. A Weibull process with failure truncated and time truncated is employed to establish the prediction model. The point estimates and prediction bounds for future failure time are provided. Moreover, a prediction procedure for spare parts is investigated by identifying the ordering time and ordering quantity. Finally, a case study illustrates the developed method by predicting the spare parts as well as future failure time for engine-driven pumps. 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(IEEE) 2018</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c408t-700b62730468bcd59be4dd930047dc1612f608e6d484d1edb8eaf7b9cfc1cd5d3</citedby><cites>FETCH-LOGICAL-c408t-700b62730468bcd59be4dd930047dc1612f608e6d484d1edb8eaf7b9cfc1cd5d3</cites><orcidid>0000-0001-7045-4022</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/8323189$$EHTML$$P50$$Gieee$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,864,2102,27633,27924,27925,54933</link.rule.ids></links><search><creatorcontrib>Sun, Yongquan</creatorcontrib><creatorcontrib>Hao, Xueling</creatorcontrib><creatorcontrib>Su, Zimei</creatorcontrib><creatorcontrib>Ren, He</creatorcontrib><title>An Ordering Decision-Making Approach on Spare Parts for Civil Aircraft Based on a One-Sample Prediction</title><title>IEEE access</title><addtitle>Access</addtitle><description>Ordering decision-making on spare parts is crucial in maximizing aircraft utilization and minimizing operating costs. This paper develops an approach of ordering decision-making for civil aircraft spare parts based on a one-sample prediction. Engineering background for line replace units, failure/replace processes, and spare parts requirements are represented. The model for future failure time is proposed based on the conditional probability density function of the failure time. A Weibull process with failure truncated and time truncated is employed to establish the prediction model. The point estimates and prediction bounds for future failure time are provided. Moreover, a prediction procedure for spare parts is investigated by identifying the ordering time and ordering quantity. Finally, a case study illustrates the developed method by predicting the spare parts as well as future failure time for engine-driven pumps. The predicted results are compared with the reality to demonstrate the effectiveness of the developed method.</description><subject>Aircraft</subject><subject>Aircraft propulsion</subject><subject>civil aircraft</subject><subject>conditional distribution</subject><subject>Conditional probability</subject><subject>Decision making</subject><subject>Failure times</subject><subject>Maintenance engineering</subject><subject>one-sample prediction</subject><subject>Order decision-making</subject><subject>Prediction models</subject><subject>Predictive models</subject><subject>Probability density function</subject><subject>Probability density functions</subject><subject>Spare parts</subject><subject>Stochastic processes</subject><issn>2169-3536</issn><issn>2169-3536</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>ESBDL</sourceid><sourceid>RIE</sourceid><sourceid>DOA</sourceid><recordid>eNpNkUtv3CAUha2olRql-QXZIHXtKZiHYem6aRMp1VSado14XCZMJ8YFp1L-fZg6isIGuDrn415O01wRvCEEq8_DOF7vdpsOE7npJJEMs7PmvCNCtZRT8e7N-UNzWcoB1yVriffnzX6Y0DZ7yHHao6_gYolpan-YP6f7MM85GXeP0oR2s8mAfpq8FBRSRmP8F49oiNllExb0xRTwJ51B2wnanXmYj1WewUe3VOTH5n0wxwKXL_tF8_vb9a_xpr3bfr8dh7vWMSyXtsfYiq6nmAlpnefKAvNeUYxZ7x0RpAsCSxCeSeYJeCvBhN4qFxypck8vmtuV65M56DnHB5OfdDJR_y-kvNd1hOiOoG3fE25DqGTDFJeWC-6wxdZRYgRxlfVpZdVf-PsIZdGH9Jin2r7uGOdSMaq6qqKryuVUSobw-irB-hSQXgPSp4D0S0DVdbW6IgC8OiTtKJGKPgP9IIuL</recordid><startdate>20180101</startdate><enddate>20180101</enddate><creator>Sun, Yongquan</creator><creator>Hao, Xueling</creator><creator>Su, Zimei</creator><creator>Ren, He</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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This paper develops an approach of ordering decision-making for civil aircraft spare parts based on a one-sample prediction. Engineering background for line replace units, failure/replace processes, and spare parts requirements are represented. The model for future failure time is proposed based on the conditional probability density function of the failure time. A Weibull process with failure truncated and time truncated is employed to establish the prediction model. The point estimates and prediction bounds for future failure time are provided. Moreover, a prediction procedure for spare parts is investigated by identifying the ordering time and ordering quantity. Finally, a case study illustrates the developed method by predicting the spare parts as well as future failure time for engine-driven pumps. The predicted results are compared with the reality to demonstrate the effectiveness of the developed method.</abstract><cop>Piscataway</cop><pub>IEEE</pub><doi>10.1109/ACCESS.2018.2818404</doi><tpages>6</tpages><orcidid>https://orcid.org/0000-0001-7045-4022</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Aircraft Aircraft propulsion civil aircraft conditional distribution Conditional probability Decision making Failure times Maintenance engineering one-sample prediction Order decision-making Prediction models Predictive models Probability density function Probability density functions Spare parts Stochastic processes |
title | An Ordering Decision-Making Approach on Spare Parts for Civil Aircraft Based on a One-Sample Prediction |
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