Design of Testing Period for Reliability Assessment of Numerical Control Machine Tools Considering Working Conditions

The existing methods of determining testing period do not consider the effect of working condition covariates on reliability testing period of Numerical Control (NC) machine tools, which may lead to high-cost testing or low-precision assessment. Aiming at the problem, a new method of determining the...

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Main Authors: Li Hongzhou, Sun Lixia
Format: Article
Language:English
Published: Hindawi Limited 2018-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2018/1962064
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spelling doaj-d44289b124464480a4496ea3b20785392020-11-25T00:48:23ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472018-01-01201810.1155/2018/19620641962064Design of Testing Period for Reliability Assessment of Numerical Control Machine Tools Considering Working ConditionsLi Hongzhou0Sun Lixia1College of Mechanical Engineering, Beihua University, Jilin 132013, ChinaCollege of Mechanical Engineering, Beihua University, Jilin 132013, ChinaThe existing methods of determining testing period do not consider the effect of working condition covariates on reliability testing period of Numerical Control (NC) machine tools, which may lead to high-cost testing or low-precision assessment. Aiming at the problem, a new method of determining the testing period considering working condition covariates is proposed. The change rate of interval estimation of Mean Time between Failures (MTBF) is used as the criterion for determining the length of testing period. The reliability model of NC machine tools is established by the Cox proportional hazards model, and the two-step estimation method is used to estimate parameters of the baseline failure rate function and the coefficients of working condition covariates. The Bootstrap resamples are obtained by the Bootstrap resampling method. And then the parameters of the baseline failure rate function and the coefficients of working condition covariates are estimated simultaneously by maximum likelihood method, and thus interval estimations of MTBF under each covariate are obtained. The change rate models of MTBF interval estimation under each covariate level are established by Power function, and the testing periods under each covariate are obtained. Case study indicates that the testing periods under each covariate obtained by the proposed method are more accurate than those obtained by the others, when the same criterion and confidence level 1-α are set.http://dx.doi.org/10.1155/2018/1962064
collection DOAJ
language English
format Article
sources DOAJ
author Li Hongzhou
Sun Lixia
spellingShingle Li Hongzhou
Sun Lixia
Design of Testing Period for Reliability Assessment of Numerical Control Machine Tools Considering Working Conditions
Mathematical Problems in Engineering
author_facet Li Hongzhou
Sun Lixia
author_sort Li Hongzhou
title Design of Testing Period for Reliability Assessment of Numerical Control Machine Tools Considering Working Conditions
title_short Design of Testing Period for Reliability Assessment of Numerical Control Machine Tools Considering Working Conditions
title_full Design of Testing Period for Reliability Assessment of Numerical Control Machine Tools Considering Working Conditions
title_fullStr Design of Testing Period for Reliability Assessment of Numerical Control Machine Tools Considering Working Conditions
title_full_unstemmed Design of Testing Period for Reliability Assessment of Numerical Control Machine Tools Considering Working Conditions
title_sort design of testing period for reliability assessment of numerical control machine tools considering working conditions
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2018-01-01
description The existing methods of determining testing period do not consider the effect of working condition covariates on reliability testing period of Numerical Control (NC) machine tools, which may lead to high-cost testing or low-precision assessment. Aiming at the problem, a new method of determining the testing period considering working condition covariates is proposed. The change rate of interval estimation of Mean Time between Failures (MTBF) is used as the criterion for determining the length of testing period. The reliability model of NC machine tools is established by the Cox proportional hazards model, and the two-step estimation method is used to estimate parameters of the baseline failure rate function and the coefficients of working condition covariates. The Bootstrap resamples are obtained by the Bootstrap resampling method. And then the parameters of the baseline failure rate function and the coefficients of working condition covariates are estimated simultaneously by maximum likelihood method, and thus interval estimations of MTBF under each covariate are obtained. The change rate models of MTBF interval estimation under each covariate level are established by Power function, and the testing periods under each covariate are obtained. Case study indicates that the testing periods under each covariate obtained by the proposed method are more accurate than those obtained by the others, when the same criterion and confidence level 1-α are set.
url http://dx.doi.org/10.1155/2018/1962064
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AT sunlixia designoftestingperiodforreliabilityassessmentofnumericalcontrolmachinetoolsconsideringworkingconditions
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