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Technical Brief

Tool Wear in Micro-Endmilling: Material Microstructure Effects, Modeling, and Experimental Validation

[+] Author and Article Information
A. M. Abdelrahman Elkaseer

Production Engineering and
Mechanical Design Department,
Faculty of Engineering,
Port Said University,
Port Fuad, Port Said 42526, Egypt
e-mail: elkaseeram@gmail.com

S. S. Dimov

School of Mechanical Engineering,
University of Birmingham,
Birmingham B15 2TT, UK
e-mail: s.s.dimov@bham.ac.uk

K. B. Popov

School of Engineering,
University of South Wales,
Pontypridd,
Wales CF37 1DL, UK
e-mail: krastimirp@yahoo.com

R. M. Minev

Materials and Manufacturing Engineering Department,
Rouse University,
Ruse POB 7017, Bulgaria
e-mail: rus@uni-ruse.bg

1Corresponding author.

Contributed by the Manufacturing Engineering Division of ASME for publication in the JOURNAL OF MICRO- AND NANO-MANUFACTURING. Manuscript received January 4, 2013; final manuscript received July 18, 2014; published online August 13, 2014. Editor: Jian Cao.

J. Micro Nano-Manuf 2(4), 044502 (Aug 13, 2014) (10 pages) Paper No: JMNM-13-1002; doi: 10.1115/1.4028077 History: Received January 04, 2013; Revised July 18, 2014

This paper reports an investigation of material microstructure effects on tool wear in microscale machining of multiphase materials. A new generic approach is proposed to estimate the tool wear that utilizes empirical data about the effects of micromilling process on cutting edge radius. Experiments were conducted to study independently the influence of two main phases in steel, pearlite and ferrite, on tool wear under different cutting conditions. Based on this empirical data, two regression models were created to estimate the increase of cutting edge radius when machining single and multiphase steels. To validate the models they were applied to predict the tool wear when machining two different multiphase steel samples. The results showed a good agreement between the estimated and the actual tool wear.

Copyright © 2014 by ASME
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Figures

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Fig. 1

Microstructure of WCu [8]

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Fig. 2

Effect of cutting edge radius on surface roughness [12]

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Fig 3

Burr size in (a) down-milling and (b) up-milling [14]

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Fig. 4

Variations in surface roughness and forces [16]

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Fig. 5

Experimental setup

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Fig. 6

Measurement functions of the Dino-capture 2.0 software

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Fig. 7

The evaluation of gradual increase of cutting edge radius for a new tool to a worn one under severe condition; where r denotes radius, C is the circumference, and A is area

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Fig. 8

The results of five measurements carried out at three different cutting edge radii

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Fig. 9

The average increase of the cutting edge radius for pearlitic (SAE 01) workpiece

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Fig. 10

The average increase of the cutting edge radius for the ferritic (SAE 101) workpiece

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Fig. 11

Cutter radius measurements at different heights for pearlite (SAE 01)

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Fig. 12

Cutter radius measurements at different heights for ferrite (SAE 101)

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Fig. 13

Normal probability plot of the pearlite wear model

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Fig. 14

Normal probability plot of the ferrite wear model

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Fig. 15

Optical microstructure micrograph of (a) AISI 1040 and (b) AISI 8620 steels

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Fig. 16

Comparison between experimental and estimated tool wear when machining the AISI 1040 workpiece with 800 μm diameter tool and 30 μm depth of cut

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Fig. 17

Comparison between experimental and estimated tool wear when machining the AISI 8620 workpiece with 800 diameter μm tool and 30 μm depth of cut

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