Process monitoring in end milling

dc.contributor.advisor Ranga Narayanaswami Choi, Yong-hoon
dc.contributor.department Industrial and Manufacturing Systems Engineering 2018-08-24T17:51:53.000 2020-07-02T05:49:54Z 2020-07-02T05:49:54Z Wed Jan 01 00:00:00 UTC 2003 2003-01-01
dc.description.abstract <p>Monitoring cutting forces in end milling is a necessary step toward the full automation of milling. To monitor the end milling process successfully, the selection of an appropriate signal and signal processing algorithm is very important. In this research, cutting force trends and tool wear effects in ramp cut machining are experimentally observed as machining progresses.;Ramp cuts are unique in the sense that the depth of cut is continuously changing. Traditionally, a series of straight slot cuts are used to machine a deep slot. Ramp cuts in which the depth of cut is continuously changing offers an alternative. Cutting force signals, table motor currents, spindle motor currents, and tool wear in ramp cuts are experimentally observed and compared to the results of straight cuts. Trends in X, Y, and Z cutting forces for straight and ramp cuts are compared.;Tool wear and its identification and estimation are a fundamental problem in machining. With tool wear there is an increase in cutting forces, and leads to deterioration in process stability, part accuracy, and surface finish. Cutting forces using new tools are compared with cutting forces obtained from a progressively wearing tool. The wavelet transform is used for signal processing and is found to be useful for observing cutting force trends.;The Root Mean Square (RMS) value of the wavelet transformed signal and linear regression are used for tool wear estimation. Tool wear is also estimated by measuring a machined slot thickness on a coordinate measuring machine. Picture analysis of the cutting tools using a SEM and microscope are used for tool wear estimation between cutting force and tool worn area.</p>
dc.format.mimetype application/pdf
dc.identifier archive/
dc.identifier.articleid 1570
dc.identifier.contextkey 6075512
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath rtd/571
dc.language.iso en
dc.source.bitstream archive/|||Sat Jan 15 00:59:24 UTC 2022
dc.subject.disciplines Industrial Engineering
dc.subject.keywords Industrial and manufacturing systems engineering
dc.subject.keywords Industrial engineering
dc.title Process monitoring in end milling
dc.type article
dc.type.genre dissertation
dspace.entity.type Publication
relation.isOrgUnitOfPublication 51d8b1a0-5b93-4ee8-990a-a0e04d3501b1 dissertation Doctor of Philosophy
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