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doi:10.1016/j.ijm

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International Journal of Machine Tools & Manufacture 48 (2008) 878–886

www.elsevier.com/locate/ijmactool

A comprehensive tool-wear/tool-life performance model in theevaluation of NDM (near dry machining) for sustainable manufacturing

P.W. Marksberrya,�, I.S. Jawahirb,1

aCenter for Manufacturing, College of Engineering, University of Kentucky, UK Center for Manufacturing, 414G Robotics Building (Office 414L),

Lexington, KY 40506-0108, USAbDepartment of Mechanical Engineering, College of Engineering, University of Kentucky, 414C Center for Robotics and Manufacturing Systems 0108,

414C Robotics Building (Office 414C), Lexington, KY 40506-0108, USA

Received 23 January 2007; received in revised form 14 November 2007; accepted 19 November 2007

Available online 31 January 2008

Abstract

Traditionally, metal working fluids (MWF) are known to improve machining performance despite poor ecological and health side

effects. A new sustainable process that has minimized the use and application of MWFs is NDM (near dry machining). Although there is

much controversy on the effectiveness of NDM, it is agreed that a lack of science-based modeling prevents its widespread use. This paper

presents a new method to predict tool-wear/tool-life performance in NDM by extending a Taylor speed-based dry machining equation.

Experimental work and validation of the model was performed in an automotive production environment in the machining of steel wheel

rims. Machining experiments and validation of the new equation reveal that tool-wear can be predicted within 10% when the effect of

NDM is statistically different than dry machining. Tool-wear measurements obtained during the validation of the model showed that

NDM can improve tool-wear/tool-life over four times compared to dry machining which underlines the need to develop sustainable

models to match current practices.

r 2007 Elsevier Ltd. All rights reserved.

Keywords: NDM (near dry machining); Automotive; Sustainable manufacturing; Tool-wear/tool-life; Predictive modeling

1. Industry background and relevance

The US utilization of metal working fluids (MWFs) isestimated at 100 million gallons annually and the currentworldwide consumption is 640 million gallons. It is estimatedthat 52% is used for machining purposes and 31% is appliedto stamping processes [1]. In machining operations, MWFsreduce friction between the cutting tool and the workpiece,prevent galling, protect surface characteristics, reduce sur-face adhesion or welding, balance heat generation effects andflush away swarfs, chips, fines and residue [2].

However, there are serious drawbacks with the use ofMWFs: cost and negative health effects. The costs for

e front matter r 2007 Elsevier Ltd. All rights reserved.

achtools.2007.11.006

ing author. Tel.: +1859 257 6262x409.

resses: marksberry@mfg.uky.edu (P.W. Marksberry),

ky.edu (I.S. Jawahir).

/www.engr.uky.edu (P.W. Marksberry).

257 6262x207

purchase, care and disposal of MWF are two times higherthan machining cost and can represent up to 17% per partin the manufacturing of automotive components [1]. It isestimated that 1.2 million workers are potentially exposedto the hazardous/chronic toxicology affects of MWFs [3].MWF impact on health is significant in five main areas:known occupational health effects, suspect occupationalhealth effects, occupational health trend, global environ-mental performance and machining economics [4–9]. Thus,operations concerned with sustainability need to look foralternatives.Near dry machining (NDM) is a sustainable manufac-

turing technique that is safe for the environment [10–12],the worker [13] and is cost effective [14]. The minimizationof MWFs is a direct indicator of sustainable manufactur-ing. The goal of NDM is to machine parts using a minimalamount of MWF so that the workpiece, chips andenvironment remain dry after cutting. In NDM, newMWF is applied to the cutting zone in a precise and

ARTICLE IN PRESSP.W. Marksberry, I.S. Jawahir / International Journal of Machine Tools & Manufacture 48 (2008) 878–886 879

controlled manner in a flow of compressed air thatis completely vaporized by the heat generated in thecutting process. MWF can be reduced up to 10,000 timescompared to traditional flood cooling providing asignificant environmental and occupationally impact.Unfortunately, the application of NDM is very difficultdue to several factors. First, NDM can be appliedin a variety of applications and offers a broad operat-ing range. Users of NDM have the option to select awide range of pressures, volumetric flow rates, nozzleconfigurations and MWF types. Depending on theparameter selection, various results (positive and ne-gative) have been reported which is summarized inTable 1. In all cases, the range of operation in NDMhas a tremendous effect on the application and offersa much smaller process window than traditional floodcooling.

Table 1

Literature review in NDM detailing varying results associated with operating

Area Description of previous work

Health and

safety

Brinksmeier and Brockhoff [10] observed in oscillating

grinding that NDM should only be used with an air suction

due to aerosol concentration levels.

The work of Gressel [15] reinforced earlier findings

quantitatively by completing experiments while turning and

drilling steel. His work demonstrated that concentrations

exceeded NOISH REL (recommended exposure limits)

limits.

Marksberry [13] indicated that air pressure, MWF

volumetric flow rates and MWF type have a profound

effect on concentrations. MWF volumetric flow rates

should stay below 200ml/h with pressures below 0.034MPa

(5 psi) to prevent total mass particulate from reaching the

5mg/m3 REL when using oil-based MWFs. Water soluble

MWFs can employ a larger process window at double to

triple the MWF rates and pressures.

Process Heisel et al. [11] stated that nozzle location in NDM has less

importance on tool-life/tool-wear when machining steel.

Wakabayashi et al. [12] concluded that NDM provided

almost equivalent advantages compared to flood cooling

when machining steel using dual nozzles at the rank face

and flank face.

Marksberry [14] indicated that nozzle position has a direct

effect on the process and greatly depends on the chip flow

path and the nozzle to cutting tool to workpiece

relationship.

Machining

performance

Scandiffio [16] observed that NDM did not offer any

improvement over conventional flood cooling when turning

steel at high cutting speeds.

Rahman et al. [17] demonstrated that NDM could provide

comparable results to flood when milling at low feed rates,

low speeds and depths of cut.

Chen et al. [18] observed that tool-wear could be reduced

over dry machining in turning stainless.

Marksberry [14] completed work that shows that tool-wear/

tool-life can be greatly improved by the use of NDM up to

four times compared to dry machining when machining

steel when directed at the dominate tool-wear pattern.

Second, models to predict machining performancethrough parameter selection do not exist for NDM. Thewide spread use and application of NDM has been slowedmainly due to three unanswered delivery parameterquestions:

1.

ran

Pro

Pre

MW

Pre

rat

Pre

MW

No

chi

No

No

chi

Pro

Pro

Pro

Pro

How much MWF should be applied?

2. Where and how do I apply the MWF? 3. What type of MWF should I apply?

Thus, there is a need to develop a scientific approach inselecting the optimal delivery parameters and cuttingconditions for machining performance that considers boththe cutting mechanics and the mist spray delivery. It is thegoal of this work to develop, validate and apply aperformance-based model in NDM that answers thosedelivery questions. The use of a model will also serve to

ge

cess range Comment

ssure: 0.6MPa (87 psi),

F rate: 30ml/h

Need air suction due to aerosol

concentration levels when using NDM.

ssure: not cited, MWF

e: 660ml/h

NDM exceeded NOISH REL limits.

ssure: 0.034MPa (5 psi),

F rate: 200ml/h

NDM is safe if pressures are low and

MWF rates are low.

zzle position: flank, rank,

p

Nozzle position is not a sensitive control

variable.

zzle position: flank, rank Multiple nozzle positions aimed at the

rank and flank face provide benefit.

zzle position: flank, rank,

p

Obstructions from the workpiece, chip

flow path and cutting geometry greatly

affect NDM effectiveness.

cess: turning steel Tool-wear did not improved compared

to flood cooling using NDM.

cess: milling steel Tool-wear did not improved compared

to flood cooling using NDM.

cess: turning stainless Tool-wear improved over dry machining

using NDM.

cess: turning steel Tool-wear improvement greatly depends

on the cutting geometry and machining

application.

ARTICLE IN PRESSP.W. Marksberry, I.S. Jawahir / International Journal of Machine Tools & Manufacture 48 (2008) 878–886880

reduce machining cost associated in NDM and lesson theenvironmental impact of manufacturing operations.

2. Machining modeling background

Several attempts have been made to develop methods[19–23] for accurately predicting the effects of machiningoperations over the past several decades. A commonapproach for assessing machining performance is tool-wear/tool-life. Tool-wear/tool-life is one of the mostsignificant and necessary parameters required for processplanning and total machining economics. A review ofnumerous theoretical and experimental techniques forpredictive assessment of tool-wear and tool-life revealsthat eight different types of tool-wear/tool-life relation-ships are commonly being used for dry machining, asshown in Table 2.

The trend in tool-wear/tool-wife modeling has been toextend Taylor’s basic equation. This is mainly due to thedirect relationship between cutting speed and tool-wear/

Table 2

Summary of tool-wear and tool-life models for dry machining

No. Tool-life/tool-wear equation Dete

cons

1 Taylor’s basic equation: VTn ¼ C C an

expe

and

from

sour

2 Taylor’s reference-speed based equation: V=VR ¼ ðTR=TÞn n is

deter

avail

refer

3 Taylor’s extended equation: T ¼ C2=ðVPf qdr

Þ All c

r) ar

deter

4 Temperature-based tool-life equation: yTn ¼ C3 n is

and

expe

5 Taylor’s extended equation including cutting conditions and

tool geometry: C / ½ðcot b� tan aÞnF ða;bÞ1=���1The

can

deter

cont

cons

6 Taylor’s extended equation including cutting conditions and

workpiece hardness: T ¼ C4Vnf mdPrqstiujx

Requ

life t

cons

u an

7 Taylor’s extended equation including cutting conditions and

workpiece hardness: V ¼ C5=ðTmf ydx

ðBHN=200ÞnÞAll c

and

deter

8 Taylor’s extended equation including chip groove effect factor

and a tool coating effect factor:

T ¼ TRW gðVR=V ÞW cð1=nÞ; where W c ¼ n=nc and W g ¼ km=f n1dn2Constants (

operation effect factor (with m ¼ 1 considered for turning)Extends the Taylor

chip-groove effect factor. Equation also includes the effects of feed, depth of

tool-life. This relationship holds true for all machiningoperations and is considered as a basis for more advancedmodels. Currently, a model does not exist for NDM and noattempts have been made to extend dry machining tool-wear/tool-life models. It is the author’s goal in this work toselect the most appropriate dry machining model andextend it for NDM.The appropriate selection of a dry machining model for

extension to NDM depends on various factors. First, it isimportant that the model be robust to accommodate a widerange of machining parameters and applications. Themodel should be easily modified and practical for industryapplications where complete machining data is not avail-able. Lastly, the model should be accurate, repeatable andsuited for industrial use where experimental constants canbe generated without using sophisticated equipment; suchas tool dynameters to calculate forces, high-speed film tounderstand complicated chip flow paths and electronmicroscopes to determine residual stress patterns andmaterial structure.

rmination of

tants

Comment Ref.

d n are

rimentally determined

currently available

many reference

ces

Most widely used

equation; however, C and

n apply to a particular

tool–workpiece

combinations

Mills and Redford

[24], Schey [25]

experimentally

mined and currently

able from many

ence sources

n applies only to

particular tool–workpiece

combinations

Mills and Redford

[24]

onstants (C2, p, q and

e experimentally

mined

Gives better accuracy

than Taylor’s basic

equation, but more tool-

life tests are required

Niebel et al. [26],

Hoffman [27]

found between 0.01

0.1 and C3 is

rimentally determined

Although the equation is

set only on an empirical

basis, it is not convenient

for practical use in the

shop floor environment

Quinto [28], Oxley

[29]

influence of a and bbe theoretically

mined as partial

ribution to Taylor’s

tant C

A complicated

relationship between tool-

life and rake/clearance

angles

Lau et al. [22]

ires excessive tool-

esting to determine all

tants (C4, n, m, p, q, t,

d x)

It is claimed that the data

for setting up the

equation are generated

from both laboratory and

industrial sources

Venkatesh [21]

onstants (C5, m, y, x

n) are experimentally

mined

It is claimed to be a good

approximation for tool-

life ranges of 10–60min

Wang and Wysk

[30], Hoffman [27]

k, n1, n2 and nc) are experimentally determined; m is the machining

-type equation to include two new factors: tool coating effect factor and

cut and cutting speed.Jawahir et al. [31], Li et al. [32]

ARTICLE IN PRESSP.W. Marksberry, I.S. Jawahir / International Journal of Machine Tools & Manufacture 48 (2008) 878–886 881

3. The new tool-wear/tool-life relationship for NDM

A recent advance in tool-wear/tool-life modeling fordry machining is the work of Jawahir et al. [31] and Liet al. [32]:

T ¼ TRkm

f n1dn2

VR

V

� �ð1=ncÞ

, (1)

where T is tool-life or tool-wear, TR is the referencetool-life or tool-wear for 1min, V is the cutting speed,VR is the reference cutting speed for 1min of tool-lifeor tool-wear, nc is the coating effect factor and Wg isthe chip-groove effect factor, represented as km=f n1dn2 . Wg

is a function of feed (f), depth of cut (d), tool nose radius,chip breaker configurations and the type of machiningoperation (m) with m ¼ 1 for turning. n1, n2 and k areempirical constants. Outputs and constants of this modelcan be easily generated using a series of machining trials(o10) while varying depth of cut, feed, and cutting speedwhile achieving accuracies on the order of �90%.Modifications to the tool-coating effect factor, nc, ispossible by including NDM parameters to the series oftrial experiments.

Extension to the dry machining model is shownbelow:

T ¼ TRkm

f n1dn2

VR

V

� �ð1=ncÞð1=NNDMÞ

, (2)

where NNDM is the NDM effect factor and is expressed as

NNDM ¼nmist

nc, (3)

Table 3

G function explanation

Mapping

function

(subscript)

Definition Comment

F Ideal MWF function MWFs are often classified as

‘‘coolants’’ or ‘‘lubricants’’

W Dominant tool-wear

pattern

Tool-wear pattern responsible

catastrophic failure or end of

N Nozzle(s) position MWF source direction and

distance to cutting zone

MZX MWF rate effect factor Linearization of tool-wear an

MWF vol. flow rate data

MZY MWF type effect factor Linearization of tool-wear an

tapping torque data from MW

where nmist is the modified coating factor for NDM mistspray. nmist can be defined as the following:

nmist ¼logV 1 � logV2

logðGF ;W ;N ;MZX ;MZYÞ � logT1

, (4)

where GF ;W ;N ;MZX ;NZYis the new modified tool-wear/tool-life

value in NDM, empirically derived while varying MWF type,MWF volumetric flow rate and nozzle(s) position. Subscriptsof the G function: F, W, N, MZX and MZY each represent amodified tool-wear value that is empirically derived. Table 3explains each mapping function and how it is derived.

3.1. Derivations of the MZX and MZY effect factors

MZX and MZY effect factors can be solved by lineariza-tion of actual tool-wear/tool-life results as shown in Fig. 1.MWF rate (denoted Xrate in units ml/h along the X-axis)represents the actual volumetric flow rate of the MWF. Theperformance and linkage of MWF type can be accom-plished by using a standard MWF evaluation method. Inthis work, a standard tapping torque test method was used(denoted as Ytyp in units N cm along the Y-axis). Variationsof the standard method were also developed to characterizecooling and lubrication behaviors of MWFs.Having obtained MZX and MZY, GF ;W ;N ;MZX ;MZY

can besolved using Eq. (5):

GF ;W ;N ;MZX ;MZY¼ TNDM � ½ðMZX ÞðX rate � bminÞ

þ ðY type � aminÞðMZY Þ þ Z1�, ð5Þ

where GF ;W ;N ;MZX ;MZY40, TNDM is the predominate tool-

life of the cutting tool, Z1 is the intercept of the effect

Categories Method to calculate

GC, cooling (water

miscible); GL, lubrication

(non-water miscible)

Collect torque test data (Nm) for

each MWF using the ASTM D 5619

tapping torque test standard with

reamed holes at 5.48 and 5.55mm.

for

life

WBL, length of groove

backwall wear

Measurements using new method for

assessing tool-wear.

Single nozzle: R, rake

face; F, flank face; C, chip

Vector representation of nozzle to

cutting zone (include three

dimensional angle and distance to

cutting zone from nozzle tip)

d MZX Calculate slope of axis:

1. Tool-wear

2. MWF volume flow rate

d

F

MZY Calculate slope of axis:

1. Tool-wear

2. Tapping torque results from

MWF

ARTICLE IN PRESSP.W. Marksberry, I.S. Jawahir / International Journal of Machine Tools & Manufacture 48 (2008) 878–886882

factors, bmin is the minimum MWF volumetric flow rateused in the construction of the data set, and amin isthe minimum MWF tapping test torque value used in theconstruction of the data set.

Z-Axis

Y-A

xis

X-Axis

MWF

Rate (ml/hr)

MWF

Type (N-cm)

Ytype

Tool-Wear

WBL or WBW

MWF Rate

Effect Factor

(Slope) MZX

MWF Type

Effect Factor

(Slope) MZY

Z1

Xrate

Fig. 1. Linearization of MWF rate and type effect factors.

NW2N

NL2 BL

NW1

NL1

A

[1] VB = Flank Wear Land

[2] BW = Width of Groove Backwall Wear

[3] BL = Length of Groove Backwall Wear

[4] KT = Crater Depth Wear

[5] SW = Width of Secondary Face Wear

[6] SD = Depth of Secondary Face Wear

[7] n = Nose Wear

[8] NL1 = Notch Wear Width on Main Cutting Edge

[9] NW1 = Notch Wear Width on Main Cutting Edge

[10] NL2 = Notch Wear Length on Secondary Cutting

[11] NW2 = Notch Wear Width on Secondary Cutting

Fig. 2. New approach to measuring combined

4. Experiment set-up

Experimental work was carried out on a CNC turningcenter in a high volume automated environment for themachining of steel wheel rims. The approach for assessingtool-wear is shown in Fig. 2 [31] and is a comprehensivemethod for evaluating grooved tools that goes beyond theoutdated ANSI/ASME B 94.55M and ISO 3685 standard.The predominant tool-wear pattern was determined to

be WBL (length of groove backwall wear). An example ofexperimental set-up can be seen in Fig. 3, detailing thenozzle to workpiece to cutting tool orientation.A standard CNMG 432 ESA AC2000 tool holder was

used in the experimental work. The workpiece material wasHSLA (high strength low alloy) steel; SAE 070 Yequivalent. Fixed machining and mist spray deliveryparameters can be seen in Table 4.

4.1. Experimental procedure

Over 400 experiments have been conducted to establishthe machining constants and to validate the new tool-wear/tool-life predictive model for NDM. The factors understudy can be seen in Table 5 and were deliberately changedin a controlled manner. Because there is skepticism aboutthe delivery of NDM for optimal tool-wear/tool-lifeperformance, a complete balance factorial experimentalpattern was performed.

A

A- A

BW5W

SD

KT VB

Edge

Edge

tool-wear patterns for grooved tools [31].

ARTICLE IN PRESS

80˚

16°

4

-Z (k)

+X (i)

~50-mm3

5

2

5

1

2

3

4

1

+Y (j)-Y (j)

+X (i)

[1] Removable Hardened Steel Nozzle Holder

[2] Stainless Steel Adjustable Nozzle

[3] Tool Holder

[4] Indexable Cutting Tool Insert

[5] Tool Holder Carousel (4 qty)

Nozzle to Cutting Tool Relationship (vector notation)

i, j, k (+X, +Y, +Z) Vectors (+/- 2-mm)

i. = -48-mm j. = -8-mm k. = -14-mm

Fig. 3. Nozzle to cutting tool to workpiece orientation.

Table 4

Fixed machining and mist spray delivery parameters

Parameter Description

Cutting tool

material

Al2O3, aluminum oxide (supplier: Kennametal CNMG

432 ESA AC2000)

Cutting tool

geometry

� Type: grooved chip breaker

� Relief angle: 01 (side), 01 (end)

� Cutting edge angle: 51 (side), 51 (end)

� Tool nose radius: 0.8mm

Cutting

parameters

� Depth of cut: 3.2mm

� Cutting speed: 4m/s

� Feed: 0.3mm/rev

� Metal removal rate: 11,520mm3/s

MWF type � Straight oil, Cooluble 2210

� Soluble—water miscible, Cimperial 1011

� Semi-synthetic—water miscible, TRIM SC235

� Synthetic—water miscible, Hocut 763

Atomization

system

� Atomization type: co-axial air blast atomization

� Machine: MSK-G 100—MicroJet

� Air pressure: 5 psi

� Nozzle: stainless steel

Table 5

Design of experiments

Control factors Levels Description of levels

MWF volumetric flow rate (ml/h) 4 (1) 20

(2) 40

(3) 80

(4) 160

MWF type 4 (1) Straight oil

(2) Soluble oil

(3) Semi-synthetic

(4) Synthetic oil

Nozzle position 3 (1) Rake face

(2) Flank face

(3) Chip

P.W. Marksberry, I.S. Jawahir / International Journal of Machine Tools & Manufacture 48 (2008) 878–886 883

The 95% confidence interval was determined at 0.85 and1.00-mm for the dominant tool-wear pattern (WBL) for drycutting using a sample size of 20.

Modifications to the ASTM tapping torque procedurewere carried out to distinguish the primary MWF functionsusing two different reamed hole diameters 5.55 and5.48mm to characterize cooling and lubricity, respectively.Fig. 4 shows the ASTM tapping torque results for each of

the MWFs used in this work while varying the reamed holediameter. Test results were collected from a MicrotapMegatap 2, Labtop II G8 machine using standard 1018steel test bar. A forming tap type was used in the test at asize of M6� 1 pitch. Tapping speed was held constant at1000 rpm or 18.8m/min.

5. Results

A comprehensive study has been conducted tovalidate the new tool-life/tool-wear relationship forNDM. A summary of the study is presented inTables 6–8 and Fig. 5.

ARTICLE IN PRESS

250

300

350

400

450

500

550

AS

TM

D 5

61

9 T

ap

pin

g T

orq

ue

(N

-cm

) 5.55-mm Reamed Hole

(Lubricity)

5.48-mm Reamed Hole

(Cooling)

Straight Oil Soluble Oil

MWF Type

Semisynthetic

Oil

Synthetic Oil

Fig. 4. ASTM tapping torque results varying MWF type and reamed

holes.

Table 6

MWF rate and type effect factors for MWFs primary used for lubrication

Dominant tool

wear pattern

Nozzle position MWF rate

effect factor

(� 10�4) MZX

MWF type

effect factor

(� 10�4) MZY

WBL R (rake face) 25.6 �2.7

F (flank face) �1.3 �6.2

C (chip) 5.1 18.9

Table 7

MWF rate and type effect factors for MWFs primary used for cooling

Dominant tool

wear pattern

Nozzle position MWF rate

effect factor

(� 10�4), MZX

MWF type

effect factor

(� 10�4), MZY

WBL R (rake face) 23.4 �10.4

F (flank face) �6.6 7.5

C (chip) �5.7 �8.3

Table 8

MWF rate and type effect factors for MWFs primary used for cooling

MWF

type

New tool coating for mist

factor (nmist)

NDM total effect factor

(NDM)

Predicted t

WBL (mm)

Straight 0.078 0.140 0.88

Soluble 0.060 0.135 0.77

Semi-

synthetic

0.055 0.126 0.55

Synthetic 0.065 0.138 0.22

Dominant tool-wear pattern: WBL; nozzle position: rake face; MWF volumetric

factor (nc): �0.56; empirical constants: k ¼ 0.32, m ¼ 1 for turning, n1 ¼ 0.23

P.W. Marksberry, I.S. Jawahir / International Journal of Machine Tools & Manufacture 48 (2008) 878–886884

6. Discussion

Tool-life/tool-wear modeling using mist spray applica-tions can be successfully and more accurately predictedthan using dry machining equations for NDM. Fig. 5shows that predicted tool-wear values mostly fall withinactual 95% machining confidence intervals for actualresults while varying MWF type and rate. Table 6 indicatesthat significant improvements in tool-wear (over 400%)can be achieved using NDM compared to dry machining.This study emphasis that models developed for drymachining conditions cannot accurately predict NDMperformance. Equation accuracy over a broad range ofMWFs, nozzle position(s) and MWF volumetric flow rateswas observed to be less than 10% on the average.Linearization of MWF rate and type effect factorssimplified model calculations, yet provided to be fairlyaccurate for shop-floor use. Modification of the toolcoating effect factor allowed the Taylor equation to beextended without deteriorating chip groove or tool coatingfactor accuracy.

7. Conclusion

It has been observed that the selection of ‘‘mist spray’’delivery parameters represents an essential element inminimizing tool-wear/tool-life. The following is a summaryof findings from the present work:

�

ool

flo

0, n

A new tool-wear/tool-life relationship has been devel-oped for NDM with coated grooved tools by extend-ing the Taylor-type equation to include mist spraydelivery parameters by modifying the tool coating effectfactor.

� More accurate and consistent estimates of tool-wear are

made by using the new predictive model for NDMcompared to dry machining models.

� The G mapping function allows users of the empirical-

based model to customize the equation to consider awide variety of mist-spray delivery parameters, includ-ing nozzle position, MWF volumetric flow rate andMWF type.

-wear Actual test tool-wear

WBL (mm)

Error

%

Improvement % over dry

machining

0.91 �3.30 102

0.74 4.05 125

0.59 �6.78 157

0.23 �4.35 402

w rate: 180ml/h; chip-groove effect factor (Wg): 0.89; tool coating effect

2 ¼ �0.642.

ARTICLE IN PRESS

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

0 50 100 200

Wid

th o

f G

roo

ve B

ackw

all W

ear

(mm

)

Tool-wear Repeatability

Results Shown with

95% confidence interval

Predicted Tool-wear

Value using

New NDM Equation

Synthetic MWF

Semi-Syn. MWF

Soluble MWF

Straight MWF

Predicted Tool-wear

Value using Dry Equation

MWF Volumetric Flow Rate (ml/hr)

150

Fig. 5. Tool-wear varying MWF type for rake face nozzle position.

P.W. Marksberry, I.S. Jawahir / International Journal of Machine Tools & Manufacture 48 (2008) 878–886 885

�

Modification of the ASTM Tapping Torque Test can beused as a technique to characterize cooling and lubricitybehaviors in MWFs while altering the reamed hole size. � The new approach in assessing tool-wear/tool-life

remains useful for characterizing tool-wear patterns inNDM that cannot be described by traditional standards.

� It is proposed to validate the new tool-wear/tool-life

equation for a wider range of conditions includingatomization type, chip form/flow interference with spraymist field, cutting geometry and work materials.

Acknowledgments

The author would like to thank the two anonymousreviewers for their comments. Very special thanks to BobGregory for suggestions for improving the draft. I wouldalso like to thank the participants of the spring 2006,Sustainability Seminar Series (coordinated by Dr. I.S.Jawahir at the University of Kentucky, College ofMechanical Engineering) for their comments.

References

[1] T. Brockhoff, A. Walter, Fluid minimization in cutting and grinding,

abrasives, Journal for the Abrasive Engineering Society, Butler, PA,

October–November 1998.

[2] E.S. Nachtman, S. Kalpakjian, Lubricants and Lubrication in

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