Multi sensor based drill wear monitoring using artificial neural network

dc.contributor.guide	Chakraborty, Debabrata
dc.coverage.spatial	Mechanical Engineering
dc.creator.researcher	Panda, Sudhansu Sekhar
dc.date.accessioned	2023-05-30T07:19:17Z
dc.date.available	2023-05-30T07:19:17Z
dc.date.awarded	2007
dc.date.completed	2007
dc.date.registered	2003
dc.description.abstract	Tool 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.description.note	Not Available
dc.format.accompanyingmaterial	None
dc.format.dimensions	Not Available
dc.format.extent	Not Available
dc.identifier.uri	http://hdl.handle.net/10603/487211
dc.language	English
dc.publisher.institution	DEPARTMENT OF MECHANICAL ENGINEERING
dc.publisher.place	Guwahati
dc.publisher.university	Indian Institute of Technology Guwahati
dc.relation	Not Available
dc.rights	self
dc.source.university	University
dc.subject.keyword	Engineering
dc.subject.keyword	Engineering and Technology
dc.subject.keyword	Engineering Mechanical
dc.title	Multi sensor based drill wear monitoring using artificial neural network
dc.title.alternative	Not available
dc.type.degree	Ph.D.