Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/253830
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dc.coverage.spatialMetal Bending
dc.date.accessioned2019-08-22T04:49:44Z-
dc.date.available2019-08-22T04:49:44Z-
dc.identifier.urihttp://hdl.handle.net/10603/253830-
dc.description.abstractOne of the most sensitive features of the sheet metal forming is the elastic recovery during newlineunloading called springback. Sheet metals are prone to certain amount of springback depending newlineon elastic deformation. Obtaining the desired size and shape of the formed component and newlinedesign of die depends on the knowledge of the amount of this springback, therefore the accurate newlineprediction of the springback is very important. The springback is a complex phenomenon as it newlinedepends on process parameters such as die radius, tooling geometry etc. and material parameters newlinesuch as sheet thickness, strength coefficient of the material, yield strength and strain hardening newlineexponent etc. newlineIn this study we have studied the effect of sheet thickness, effect of R/t ratio, effect of newlinestrength coefficient and strain hardening exponent on springback for component with hole and newlinewithout hole in it. Also the springback with presence of holes in the component and springback newlinewithout holes in the component is studied. Further the effect location of holes in the component newlineon springback and effect of size of hole on springback is investigated. Also the springback along newlinethe length for the component with hole and without hole is studied. The FEA and experimental newlineresults are compared. It is found that the FEA and experimental results are in good agreement. It newlineis observed that with presence of hole the springback decreases adjacent to the hole and with newlineincrease in the size of the hole, reduction in springback is noted. Also the variation in the newlinespringback along the length is observed because of the presence of holes in the component. A newlineneural network model is developed and trained from the experimental and FEA data and is used newlineto predict the springback. Finally a method of forming in two steps is suggested so as to reduce newlinethe springback. newline
dc.format.extent128p
dc.language-1
dc.relation77b
dc.rightsuniversity
dc.titleStudy of Springback in Sheet Metal Bending
dc.title.alternativen.a.
dc.creator.researcherGawade Sharad Ramdas
dc.subject.keywordEngineering and Technology,Material Science,Materials Science Multidisciplinary
dc.description.noteBibliography
dc.contributor.guideNandedkar V M
dc.publisher.placeNanded
dc.publisher.universitySwami Ramanand Teerth Marathwada University
dc.publisher.institutionFaculty of Engineering
dc.date.registered11/11/2011
dc.date.completed2018
dc.date.awarded10/08/2019
dc.format.dimensions
dc.format.accompanyingmaterialDVD
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Faculty of Engineering

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01_title.pdfAttached File61.44 kBAdobe PDFView/Open
02_certificate.pdf61.14 kBAdobe PDFView/Open
03_abstract.pdf48.19 kBAdobe PDFView/Open
04_declaration.pdf61.85 kBAdobe PDFView/Open
05_acknowledgement.pdf70.97 kBAdobe PDFView/Open
06_contents.pdf70.31 kBAdobe PDFView/Open
07_list_of_tables.pdf58.84 kBAdobe PDFView/Open
08_list_of_figures.pdf59.55 kBAdobe PDFView/Open
09_abreviations.pdf48.21 kBAdobe PDFView/Open
10_chapter1.pdf128.18 kBAdobe PDFView/Open
11_chapter2.pdf165.92 kBAdobe PDFView/Open
12_chapter3.pdf447.68 kBAdobe PDFView/Open
13_chapter4.pdf2.6 MBAdobe PDFView/Open
14_chapter5.pdf74.97 kBAdobe PDFView/Open
15_bibliography.pdf109.36 kBAdobe PDFView/Open


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