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contributor authorBayesteh, Abdolreza
contributor authorKo, Junghyuk
contributor authorJun, Martin Byung
date accessioned2017-05-09T01:32:04Z
date available2017-05-09T01:32:04Z
date issued2016
identifier issn2166-0468
identifier otherjmnm_004_02_021004.pdf
identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/162152
description abstractThere is an increasing demand for product miniaturization and parts with features as low as few microns. Micromilling is one of the promising methods to fabricate miniature parts in a wide range of sectors including biomedical, electronic, and aerospace. Due to the large edge radius relative to uncut chip thickness, plowing is a dominant cutting mechanism in micromilling for low feed rates and has adverse effects on the surface quality, and thus, for a given tool path, it is important to be able to predict the amount of plowing. This paper presents a new method to calculate plowing volume for a given tool path in micromilling. For an incremental feed rate movement of a micro end mill along a given tool path, the uncut chip thickness at a given feed rate is determined, and based on the minimum chip thickness value compared to the uncut chip thickness, the areas of plowing and shearing are calculated. The workpiece is represented by a dualDexel model, and the simulation properties are initialized with real cutting parameters. During realtime simulation, the plowed volume is calculated using the algorithm developed. The simulated chip area results are qualitatively compared with measured resultant forces for verification of the model and using the model, effects of cutting conditions such as feed rate, edge radius, and radial depth of cut on the amount of shearing and plowing are investigated.
publisherThe American Society of Mechanical Engineers (ASME)
titleMicro Flat End Milling Simulation Model With Instantaneous Plowing Area Prediction
typeJournal Paper
journal volume4
journal issue2
journal titleJournal of Micro and Nano
identifier doi10.1115/1.4032757
journal fristpage21004
journal lastpage21004
identifier eissn1932-619X
treeJournal of Micro and Nano-Manufacturing:;2016:;volume( 004 ):;issue: 002
contenttypeFulltext


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