Machinery's Handbook, 31st Edition
1170
Microcutting Tools
where λ = milling factor
a = width of cut (radial depth) in milling M = number of teeth D = milling cutter diameter
Example 8, Cumulative Tool Life: Turning Test: Dry turning a metal matrix composite rod (Ø18 mm, 100 mm long) at constant 256 rpm on a manual lathe, depth of cut 0.5 mm, feed 0.07 mm/rev. Carbide tool TNPR331M-H1, tool holder MTENN2020-33. This Al-SiC composite is very abrasive and is ideal for tool life model testing since abrasive wear is the main mechanism and flank wear is clearly seen and measured on a carbide tool. In this test, a tool is turned at constant rpm until reaching 300 m m flank wear. At least two data points are required to calculate the effect of speed, or the slope n in Taylor equation. From Table 4, the speed and tool life pairs are (14.48 m/min, 3.54 min) and (9.56 m/min, 5.58 min). The slope n derived from Equation (3) for these two data points is
( V 2 ⁄ V 1 ) ( T 1 ⁄ T 2 )
log log
= log (9.56
⁄ 14.48) log (3.54 ⁄ 5.58)
0.91
n
=
=
When considering many data points, the averaged value of n is 0.94. A spreadsheet such as Table 4 is a convenient way to tabulate cumulative values of each Δ t and Δ tV 1/ n term and then use these to calculate the equivalent tool life T e with Equation (7), and the equivalent tool speed V e with Equation (8b). The plot for all experimental data at constant cutting speeds and cumulative speeds is shown in Fig. 11a . Having all data points fitting on the same line indicates the validity of cumulative tool life models. Facing Test: The same material and cutting tools are used in the facing test. Tool wear and tool life plots are shown in Fig. 11b and Fig. 11c. There is no difference in tool life when machining at low then high speed or the other way around. Table 4. Spread Sheet for Example 8 , Cumulative Tool Life in Turning Δ Length (mm) Diameter (mm) Speed (m/min) Δ t (min) Δ tV 1 / n Cumulative Flank Wear ( m m) Feed (mm/rev) Equivalent RPM Δ tV 1 / n Δ t (min) V e (m/min) T e (min)
256 26.5 256 16.0 256 21.0 179 18.5 179 21.5 179 25.0
18.0 18.0 18.0 17.0 17.0 17.0
14.48 1.48 25.39 25.39 1.48 199 0.07 14.48 0.89 15.33 40.72 2.37 242 0.07 14.48 1.17 20.12 60.84 3.54 300 0.07 9.56 1.48 16.30 16.30 1.48 160 0.07 9.56 1.72 18.95 35.25 3.19 233 0.07 9.56 2.00 22.03 57.28 5.19 289 0.07 projected 61.61 5.58 300
14.48 3.54
9.56 5.58
Workpiece Materials Micromachining is often utilized to fabricate components for miniaturized sensors, medical, optical, and electronic devices, etc. Common engineering materials for these applications include stainless steel, aluminum, titanium, copper, and tool steel for min- iature molds and dies. Workpiece materials must meet certain conditions for successful micromachining. Un like macromachining, a micromachining tool is subjected to fluctuating cutting force when it encounters each grain since microtool size is comparable to material grain size. A microtool is more vulnerable to fatigue fracture and the resulting surface—if the tool survives—would be rough due to different spring-back protrusion from each grain due to different crystallographic orientations of the grains, and direction-dependent properties of the material. Homogenous workpiece materials with very fine and uniform grain sizes should be chosen for micromachining. Inclusions and large precipitates should be mini mized to avoid damage to a fragile tool edge.
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