1. Shodhganga@INFLIBNET
  2. Indian Institute of Technology Guwahati
  3. DEPARTMENT OF MECHANICAL ENGINEERING
Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/487211
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DC FieldValueLanguage
dc.coverage.spatialMechanical Engineering
dc.date.accessioned2023-05-30T07:19:17Z-
dc.date.available2023-05-30T07:19:17Z-
dc.identifier.urihttp://hdl.handle.net/10603/487211-
dc.description.abstractTool condition monitoring TCM is one of the most important activities in modern manufacturing activities proper implementation of TCM system not only prevents catastrophic failure of tool but also increases the productivity of the industries Drilling is one of the most common machining operations used in industries and hence monitoring of the drilling condition is of significationt importance in industries Among different causes of drilling failure gradual wear of the drilling is unavoidable
dc.format.extentNot Available
dc.languageEnglish
dc.relationNot Available
dc.rightsself
dc.titleMulti sensor based drill wear monitoring using artificial neural network
dc.title.alternativeNot available
dc.creator.researcherPanda, Sudhansu Sekhar
dc.subject.keywordEngineering
dc.subject.keywordEngineering and Technology
dc.subject.keywordEngineering Mechanical
dc.description.noteNot Available
dc.contributor.guideChakraborty, Debabrata
dc.publisher.placeGuwahati
dc.publisher.universityIndian Institute of Technology Guwahati
dc.publisher.institutionDEPARTMENT OF MECHANICAL ENGINEERING
dc.date.registered2003
dc.date.completed2007
dc.date.awarded2007
dc.format.dimensionsNot Available
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:DEPARTMENT OF MECHANICAL ENGINEERING

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04_abstract.pdf94.55 kBAdobe PDFView/Open
80_recommendation.pdf175.95 kBAdobe PDFView/Open
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