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dc.contributor.authorChelishchev, Petr
dc.contributor.authorSørby, Knut
dc.date.accessioned2020-05-18T07:50:42Z
dc.date.available2020-05-18T07:50:42Z
dc.date.created2020-01-20T15:13:10Z
dc.date.issued2020
dc.identifier.isbn978-981-15-2341-0
dc.identifier.urihttps://hdl.handle.net/11250/2654716
dc.description.abstractThis paper proposes the algorithm for analyses of sample strategies. The back propagation artificial neural network approach is employed to approximate CMM measurements of the circular features of the aluminum workpieces machined with milling process. The discrete data is transformed into continuous nondeterministic profiles. The profiles are used for simulation to estimate the maximum possible error in different sample strategies for various diameters.en_US
dc.language.isoengen_US
dc.publisherSpringeren_US
dc.relation.ispartofAdvanced Manufacturing and Automation IX Conference proceedings IWAMA 2019
dc.titleSimulation Algorithm of Sample Strategy for CMM Based on Neural Network Approachen_US
dc.typeChapteren_US
dc.description.versionacceptedVersionen_US
dc.source.pagenumber434-441en_US
dc.identifier.doi10.1007/978-981-15-2341-0_54
dc.identifier.cristin1778126
dc.description.localcode"This is a post-peer-review, pre-copyedit version of an article. Locked until 3.1.2021 due to copyright restrictions. The final authenticated version is available online at: http://dx.doi.org/10.1007/978-981-15-2341-0_54en_US
cristin.unitcode194,64,92,0
cristin.unitnameInstitutt for maskinteknikk og produksjon
cristin.ispublishedtrue
cristin.fulltextpreprint
cristin.qualitycode1


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