Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/14116
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dc.coverage.spatialEngineeringen_US
dc.date.accessioned2013-12-18T06:32:08Z-
dc.date.available2013-12-18T06:32:08Z-
dc.date.issued2013-12-18-
dc.identifier.urihttp://hdl.handle.net/10603/14116-
dc.description.abstractPresent manufacturing industry demands more automation from design stage to manufacturing stage. The flexibility in design and production has become simpler with the use of computers. Geometric models with complete design data details are created through CAD software and are in the form of neutral file. These files can be transported for further analysis or process planning or for manufacturing floor. Automatic feature recognition is the process of extraction of design information from neutral file and identifying the features to be machined on a product without any human intervention. Automatic feature recognition is an important aspect for CAPP and it is an important task between CAD and CAPP. CAPP is the bridging gap between CAD and CAM. Present work is an attempt to develop a method for automatic feature recognition of rotational components from neutral file, STEP (AP203). A rule based search is employed to recognize manufacturing features and its attributes such as dimension (length and radius), nature of internal feature (through/ blind), type of feature (external/internal), nature of contour (concave/convex) and feature location relative to the original coordinates of the designed part(online/offline). Three dimensional rotational parts that are created using CATIA software are used in this methodology to recognize features. A generalized JAVA code has been written to extract the data and to recognize the features. The developed software consists of five major segments. First segment deals with extraction of geometrical data from neutral file and remaining four segments are used to recognize cylindrical features, curved features, cross hole features and special features respectively from extracted geometrical data. Full automation of feature recognition for rotational parts can be achieved by using the software developed. The segments have been implemented and tested on several components. The results are satisfactory and successful.en_US
dc.format.extent98p.en_US
dc.languageEnglishen_US
dc.relation-en_US
dc.rightsuniversityen_US
dc.titleAutomatic feature recognition for rotational components from step filesen_US
dc.title.alternative-en_US
dc.creator.researcherVangipurapu, Naga Malleswarien_US
dc.subject.keywordMechanical Engineeringen_US
dc.subject.keywordAutomatic feature recognitionen_US
dc.subject.keywordrotational componentsen_US
dc.subject.keywordstep filesen_US
dc.subject.keywordcylindrical feature recognitionen_US
dc.subject.keywordcurvature feature recognitionen_US
dc.subject.keywordJAVA program executionen_US
dc.description.noteBibliography p.74 -81 , Appendices p. 82-98en_US
dc.contributor.guideSarchar, M M Men_US
dc.publisher.placeVishakhapatnamen_US
dc.publisher.universityAndhra Universityen_US
dc.publisher.institutionDepartment of Mechanical Engineeringen_US
dc.date.registeredn.d.en_US
dc.date.completed2013en_US
dc.date.awardedn.d.en_US
dc.format.dimensions-en_US
dc.format.accompanyingmaterialNoneen_US
dc.type.degreePh.D.en_US
dc.source.inflibnetINFLIBNETen_US
Appears in Departments:Department of Mechanical Engineering

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01_title.pdfAttached File120.7 kBAdobe PDFView/Open
02_declaration.pdf37.68 kBAdobe PDFView/Open
03_certificate.pdf38.11 kBAdobe PDFView/Open
04_acknowledgement.pdf38.85 kBAdobe PDFView/Open
05_contents.pdf50.51 kBAdobe PDFView/Open
06_list of figures.pdf46.37 kBAdobe PDFView/Open
07_list of tables.pdf38.48 kBAdobe PDFView/Open
08_abstract.pdf37.98 kBAdobe PDFView/Open
09_chapter 1.pdf73.7 kBAdobe PDFView/Open
10_chapter 2.pdf167.24 kBAdobe PDFView/Open
11_chapter 3.pdf128.33 kBAdobe PDFView/Open
12_chapter 4.pdf229.93 kBAdobe PDFView/Open
13_chapter 5.pdf93.96 kBAdobe PDFView/Open
14_chapter 6.pdf564.8 kBAdobe PDFView/Open
15_references.pdf100.58 kBAdobe PDFView/Open
16_appendix.pdf1.22 MBAdobe PDFView/Open


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