LEADER 03705nam  22006015  450 
001 9910337638603321
005 20200704110309.0
010   $a3-030-12807-5
024 7 $a10.1007/978-3-030-12807-4
035   $a(CKB)4100000007598214
035   $a(DE-He213)978-3-030-12807-4
035   $a(MiAaPQ)EBC5693489
035   $a(PPN)235007315
035   $a(EXLCZ)994100000007598214
100   $a20190209d2019      u|         0
101 0 $aeng
135   $aurnn|008mamaa
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 13$aAn Intelligent Inspection Planning System for Prismatic Parts on CMMs /$fby Slavenko M. Stojadinovi?, Vidosav D. Majstorovi?
205   $a1st ed. 2019.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2019.
215   $a1 online resource (XV, 139 p.) 
311   $a3-030-12806-7 
327   $aIntroduction -- Review of CMM Inspection Planning Methods -- Ontology Knowledge Base for Integration Geometry and Tolerance of PMPs -- The Model for Inspection Planning of PMPs on CMM -- Ants Colony Optimization of The Measuring Path of PMPs on a CMM -- Concluding Remarks and Future Research.
330   $aThis book introduces a new generation of metrological systems and their application in a digital quality concept. It discusses the development of an optimal collision-free measuring path based on CAD geometry and tolerances defined in knowledge base and AI techniques such as engineering ontology, ACO and GA. This new approach, combining both geometric and metrological features, allows the following benefits: reduction of a preparation time based on the automatic generation of a measuring protocol; developed mathematical model for the distribution of measuring points and collision avoidance; the optimization of a measuring probe path; the analysis of a part placement based on the accessibility analysis and automatic configuration of measuring probes. The application of this new system is particularly useful in the inspection of complex prismatic parts with a large number of tolerances, in all of type production. The implementation is demonstrated using several case studies relating to high-tech industries and advanced, non-conventional processes.
606   $aMachinery
606   $aManufactures
606   $aArtificial intelligence
606   $aPhysical measurements
606   $aMeasurement
606   $aMachinery and Machine Elements$3https://scigraph.springernature.com/ontologies/product-market-codes/T17039
606   $aManufacturing, Machines, Tools, Processes$3https://scigraph.springernature.com/ontologies/product-market-codes/T22050
606   $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000
606   $aMeasurement Science and Instrumentation$3https://scigraph.springernature.com/ontologies/product-market-codes/P31040
615  0$aMachinery.
615  0$aManufactures.
615  0$aArtificial intelligence.
615  0$aPhysical measurements.
615  0$aMeasurement.
615 14$aMachinery and Machine Elements.
615 24$aManufacturing, Machines, Tools, Processes.
615 24$aArtificial Intelligence.
615 24$aMeasurement Science and Instrumentation.
676   $a621.8
676   $a658.4038
700   $aStojadinovi?$b Slavenko M$4aut$4http://id.loc.gov/vocabulary/relators/aut$0862561
702   $aMajstorovi?$b Vidosav D$4aut$4http://id.loc.gov/vocabulary/relators/aut
906   $aBOOK
912   $a9910337638603321
996   $aAn Intelligent Inspection Planning System for Prismatic Parts on CMMs$91925302
997   $aUNINA