CIRP Journal of Manufacturing Science and Technology 7 (2014) 5570

Contents lists available at ScienceDirect

CIRP Journal of Manufacturing Science and TechnologyReview

Interaction of the cutting tools and the ceramic-reinforced metalmatrix composites during micro-machining: A review

Jian Liu a, Juan Li a, Chengying Xu b,*aDepartment of Mechanical and Aerospace Engineering, University of Central Florida, Orlando, FL 32816, USAbDepartment of Mechanical Engineering, Florida State University, Tallahassee, FL 32310, USA

Contents

1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

2. Ceramic-reinforced metal matrix composites. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

2.1. Mechanical properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

2.2. Fracture mechanism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58

2.3. Machinability study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59

3. Cutting process mechanism. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60

3.1. Materials micro-structural effect. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60

3.1.1. Effect of crystalline grain size on micro-machining (crystallographic effect) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60

3.1.2. Effect of reinforcements on micro-machining . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60

3.2. Strengthening effect . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61

3.3. Size effect . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62

3.4. Minimum chip thickness effect . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62

4. Cutting process modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63

4.1. Chip formation modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63

4.2. Cutting force modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64

4.3. Dynamics modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65

4.4. Other aspects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66

A R T I C L E I N F O

Article history:

Available online 5 March 2014

Keywords:

Micro-machining

Heterogeneous materials

Ceramic particle reinforcement

Metal matrix composites

Size effect

Minimum chip thickness

Toolworkpiece interaction

Strengthening mechanism

Materials microstructural effect

Materials mechanical property

Fracture mechanism

Machining dynamics

Surface generation

A B S T R A C T

High performance ceramic-reinforced metal matrix composites (MMCs) are becoming widely popular in

industry and the mechanical machining method is one of the most suitable manufacturing techniques

for near net shape MMC components. This paper provides a comprehensive literature review to enhance

the fundamental understanding of the toolworkpiece interactions in micro-scale during cutting process

on engineered-heterogeneous materials. The paper focuses on mechanical properties, fracture

mechanism and machinability of ceramic-reinforced MMCs, with signicant emphasis on the chip

formation mechanism considering different dominant effects, such as materials strengthening

mechanisms, micro-structural effect, size effect and minimum chip thickness effect. It also includes

some work that, while not directly focused on micro-scale cutting ceramic-reinforced MMCs, but

provided important insight to the eld of cutting engineered-heterogeneous materials (non-eutectic).

Furthermore, process modeling studies for micro-scale cutting are also surveyed, including the cutting

force modeling, dynamics modeling and surface generation modeling. The comments on future needs

and directions are provided at the end.

2014 CIRP.

* Corresponding author. Tel.: +1 8504106588.

E-mail address: cxu@fsu.edu (C. Xu).

jou r nal h o mep age: w ww.els evier . co m/lo c ate /c i rp j

1755-5817/$ see front matter . 2014 CIRP.http://dx.doi.org/10.1016/j.cirpj.2014.01.003

. .

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J. Liu et al. / CIRP Journal of Manufacturing Science and Technology 7 (2014) 557056components can be manufactured more efciently with lower costand higher quality.

However, the remarkably enhanced mechanical propertiesof MMCs, in terms of yield strength, fracture strength,wear resistance and shear modulus, bring great challenges formechanical micro-machining. Comparing with micro-machining

2. Ceramic-reinforced metal matrix composites

2.1. Mechanical properties

Ceramic-reinforced metal matrix composites (MMCs) havepotential to replace conventional light-weight metallic materials,5. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1. Introduction

Metal matrix composite materials (MMCs) have been applied innumerous elds that include energy, defense, aerospace, bio-technology, optics and automobile, because of their reinforced highperformance mechanical properties and reduced weight. In recentdecades, substantial progress has been achieved in the developmentof MMCs. This enables the advanced heterogeneous materials to beconsidered in more applications, specically, avionics packaging,micro-uidic channels for fuel cells, micro-scale holes for ber optics,micro-nozzle array for multiplexed electrospray systems, microsensors and actuators [16]. These applications require outstandingmechanical properties, including light weight, high strength, highcreep resistance, long fatigue life, high corrosion/oxidation resis-tance, low thermal expansion and good wear resistance.

On the other side, emerging miniaturization technologies areperceived as key technologies of the future in a broad spectrum ofapplications [2,3]. Due to the high surface-to-volume ratio,miniature components can provide lower power consumption,higher heat transfer, and are more exible and efcient. Usingminiature components under appropriate circumstances canfurther improve energy efciency.

In aforementioned applications, both the small size andoutstanding mechanical properties are required. Ceramic parti-cle-reinforced metal matrix composites, such as aluminum-basedMMCs (Al-MMCs) or magnesium-based MMCs (Mg-MMCs), withlight weight and high toughness, are excellent candidates formaking components for such applications. Thanks to the hardceramic particles reinforcement, the mechanical properties areimproved signicantly. It was found that these composites exhibitmuch better mechanical properties, such as higher strength andsuperior wear resistance than pure Mg/Al and their alloys [79].

There exist a number of different fabrication methods to makeminiaturized components, made of ceramic-reinforced MMCs.Since components made of advanced MMC materials usuallycontain complex 3-Dimensional (3-D) features, the traditionalsilicone-based fabrication methods for micro-electro-mechanicalsystems (MEMS) are not adequate. Several micro-manufacturingmethods have been reported in the literature for SiC reinforcedMMCs. Muller et al. [10] studied the capability of manufacturingSiC particle-reinforced aluminum matrix composites using EDMmethod. The results showed that the removal rate was low due tothe poor electrical conductivity of SiC particles. In addition,electrode wear was severe and thus inevitably increased themanufacturing cost. Laser machining is another alternativemethod and is capable of making small diameter holes and cuttingmetal matrix composites. However, the surface quality wasrelatively poor and the microstructure of materials was changedunder the effect of laser heating [11].

Compared to the above methods, the mechanical micro-machining process is promising to mass produce MMCs parts.This approach is cost-effective, exible, and controllable, precise(relative accuracy as 103 to 105), and capable to make arbitrary3D pattern [2,10,11]. Using micro-machining technique, small . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68

homogeneous metals, cutting forces when machining MMCs aremuch larger due to the existence of the ceramic particlereinforcement. Tool wear is more severe and tool life is shortened.Due to the elevated cutting force amplitude, tool vibration and tooldeection are more signicant. As a result, both dimensionalaccuracy and surface quality are adversely affected. In order toachieve good machining efciency and quality, it is important tofully understand the strengthening mechanism and the inuenceof reinforcement particles on the entire micro-cutting process,especially the chip formation process.

Fig. 1 illustrates the relationships among material properties,strengthening mechanisms and cutting mechanisms in differentscales during mechanical micro-machining.

In the micro-scale level, the fundamental microstructure andstrengthening mechanisms of the MMCs establish the foundationfor cutting mechanics and dynamics. Core research topics involvemechanical properties and fracture mechanisms of the material.

In the meso-scale level, fundamental chip formation mechanismis different from traditional machining and micro-machining ofhomogeneous materials, due to the effect of heterogeneity, sizeeffect and the minimum chip thickness effect, etc. The inuenceof materials microstructure and strengthening mechanism onchip formation is the key. The fundamental material removalmechanism for heterogeneous materials further establishes thetheoretical foundation, which differentiates cutting regimes inmacro-scale level. The chip formation modeling involvesmaterial strengthening effect, tool edge radius effect, size effect,minimum chip thickness effect; it is built to further predictdynamic cutting force during machining.

In the macro-scale level, the research should focus on modelingthe process states, including cutting forces and tool vibration, aswell as the nal machined surface integrity, in terms ofdimensional accuracy and surface roughness.

Thorough understanding the tool-workpiece interaction mecha-nism and the chip formation physics will facilitate the modelingwork of the entire micro-cutting process. With this purpose, thisreview paper specically focuses on the interaction of the cuttingtools and the ceramic-reinforced MMCs. Based on the processmodels, the productivity, machined surface integrity, and tool lifecan all be improved through optimizing the cutting conditions forspecic ceramic-reinforced MMCs composite materials. The re-mainder of this paper is organized as follows. Section 2 reviews theproperties of the ceramic-reinforced MMCs, including mechanicalproperties, fracture mechanisms and micro-machinability. Section 3examines the chip formation process with emphasis on micro-structural effect, strengthening effect, size effect and minimum chipthickness effect, as well as their inuences on the cuttingmechanism. In Section 4, the process modeling work is summarizedfor the micro-cutting process. Cutting force modeling, dynamicsmodeling and surface generation modeling are also covered. Section5 concludes and provides future directions.

J. Liu et al. / CIRP Journal of Manufacturing Science and Technology 7 (2014) 5570 57such as magnesium, aluminum, titanium and their alloys, due tothe reinforced high mechanical performance, including higheryield strength, fracture strength, toughness, lower thermalexpansion, higher creep resistance and wear resistance. Incomparison to pure metal materials, the engineered compositesdisplay higher stiffness, strain hardening, and strength, with lowerstrain to fracture [1].

Previous studies primarily focused on the use of micro-sizedreinforcements, mostly in aluminum matrix [1]. Researchers haveinvestigated the effect of micro-sized reinforcement particles on themechanical properties of the MMCs [1,8,12]. Lim et al. [8] studied thewear behavior of the Mg-MMCs reinforced by SiC particles with anominal size of 14 mm. Charles et al. [12] investigated the mechanicalbehavior of SiC reinforced Al-MMCs at cryogenic temperatures basedon Design of Experiments (DOE) method. It was found that themechanical properties of the MMCs in terms of hardness, wearresistance, and tensile property are high for cryo-treated specimensand decrease with increase in temperature. The mechanical proper-ties also increase with the increase of reinforcements.

As novel nanoparticle-reinforced MMCs show improved me-chanical performances, such as higher yield strength and creepresistance, comparing to their micro-composite counterparts,researchers began to move their interests further to nano-particulateMMCs. Different matrix materials were studied including magne-sium [1316], aluminum [17] and copper [18]. The investigated

Fig. 1. Schematic of the interrelationship amongreinforcement nanoparticles include SiC [13], alumina [15,18], MgO/MgO2 [19] and even Ti2AlC [16]. Tjong summarized and reviewed theprocessing methods, micro-structures and mechanical properties ofMMCs reinforced with nano-sized ceramic particles [20]. Thesestudies revealed that the composites reinforced with nano-sizedparticles exhibit better properties than those reinforced with micro-sized reinforcements. Nano-reinforcements can remarkably increasethe mechanical strength by effectively promoting particle hardeningmechanisms. A ne and uniform dispersion of nano-particlesprovides a good balance between the non-deforming ceramicreinforcement particles and their inter-particle spacing to maximizeyield strength and creep resistance, while retaining good ductility[2123]. Above studies primarily focused on the use of low volumefractions (

in research. Reddy et al. [13] rst reported Mg-MMCs using SiCparticulates in sub-micron length scale. In this study, the micro-structural, physical and mechanical properties of pure magnesiumreinforced by different volume fractions of 0.6 mm SiC particleswere studied. The Mg-MMCs were synthesized using disintegratedmelt technique. The characterization results are shown in Table 1.The microscopic views showing the distribution of the particles inmatrix materials are displayed in Fig. 2.

Cao et al. [14] investigated the mechanical properties andmicrostructure of MgSiC nanocomposites fabricated by ultrasoniccavitation to disperse SiC nanoparticles in Mg melts. The averagesize of SiC particles used in this study is 50 nm. The mechanical

fabricated Mg-MMCs are shown in Fig. 3. It indicates that most ofthe SiC nanoparticles were dispersed well locally, with extinct SiCmicro-clusters. Table 3 shows result for Mg-MMCs with highercontent of SiC nanoparticles [13], where the percentage value inthe rst column represents the weight ratio of SiC nanoparticles inthe matrix of Mg-MMCs nanocomposites.

According to the literature, the volume fraction of the Mg-MMCs using SiC as reinforcement is limited approximately around10 vol.%. There is very little literature regarding higher volumefraction MMCs with nano-reinforcements, especially for Mg-basednanocomposites [25]. The main reason is because it is very difcultto mix more SiC nano-particles into the matrix metal uniformly.Different mechanical property aspects, such as elasticity, plasticityand fracture strength, exhibit different trends as volume fractionvaries. Also, MMCs reinforced by various sizes of nano particlesbehave differently in mechanical properties. Therefore, the studyon the effect of particle size and volume fraction on the materialproperties is important and explicit models are needed.

2.2. Fracture mechanism

In order to understand the cutting mechanism of ceramic-

Table 1Results of acid dissolution, density, porosity and grain size measurements [13].

Material Reinforcement Density (g/cm3) Porosity (vol.%) Characteristics of grains Characteristics of SiC particulates

wt.% vol.% Size (mm) Aspect ratio Size (mm) Aspect ratio

Mg 1.7380 0.0020 0.12 21 6 1.8 0.41 Mg/SiC 4.8 2.7 1.7698 0.0236 0.53 18 6 1.9 0.40 0.57 0.04 1.2 0.1Mg/SiC 10.2 5.8 1.7931 0.0019 1.75 17 7 1.8 0.21 0.58 0.02 1.1 0.1Mg/SiC 15.4 9.0 1.8349 0.0163 1.98 12 4 1.4 0.11 0.58 0.02 1.1 0.1

Table 2Average mechanical properties [14].

Materials Yield strength

(MPa)

Ultimate tensile

strength (MPa)

Ductility/

Elong. (%)

Pure Mg 20.0 89.6 14.0

Mg/0.5% SiC 28.3 120.7 15.5

Mg/1.0% SiC 30.3 124.1 14.2

Mg/2.0% SiC 35.9 131.0 12.6

Mg/4.0% SiC 47.6 106.9 5.5

J. Liu et al. / CIRP Journal of Manufacturing Science and Technology 7 (2014) 557058properties are shown in Table 2. The microstructures of theFig. 3. SEM images of Mg/2 wt% SiC nanocomposite: (a) lo

Fig. 2. SEM micrographs showing the distribution of reinforcement in: reinforced MMCs, it is critical to understand the materials fracture

(a) Mg/4.8 wt% SiC; (b) Mg/10.2 wt% SiC; (c) Mg/15.4 wt% SiC [13].wer magnication and (b) higher magnication [14].

mechanism. From the perspectives of fracture mechanics andcomputational mechanics, researchers have dedicated effort inmodeling the fracture behavior, crack damage evaluation andinterface damage for MMCs.

For particle-reinforced MMCs, classical plasticity theory cannot

Experimentally, Xia et al. [31] studied the fracture behavior ofMMCs reinforced with micro-sized (1530 mm) ceramic particles.Different volume fractions (520%), reinforcements (alumina andSiC) and matrix materials (2618, 6061 and 7075 Al) were examinedunder three point bending tests. Results revealed that the energyabsorption level during the crack propagation depended on bothmatrix strength and ductility. The latter property related to thevolume fraction, composition and heat treatment conditions. Similarexperimental study was also performed by Rabiei et al. [32], whoevaluated the fracture toughness of Al-MMCs with various particlereinforcements. Hahn Roseneld model was used to estimatetheoretical fracture toughness. Since the Hahn Roseneld model isonly valid for predicting the fracture toughness of MMCs with 510 mm particle reinforcements, a modication to this model wasdeveloped for estimating the fracture toughness of the MMCs with

Table 3Mechanical properties measured at ambient room temperature [13].

Material Youngs

Modulus E

(GPa)

0.2% Yield

stress (MPa)

UTS (MPa) Ductility (%)

Mg 39.82 153 8 207 4 9.2 1.4Mg/4.8%SiC 45.60 182 2 219 2 2.1 0.9Mg/10.2%SiC 47.22 171 3 221 14 1.5 0.2Mg/15.4%SiC 48.24 155 1 207 9 1.4 0.1

J. Liu et al. / CIRP Journal of Manufacturing Science and Technology 7 (2014) 5570 59be directly applied, because the composites exhibit a tension-compression yield asymmetry due to the variation of damageevolution with loading modes [26]. Zhang et al. [26] proposed aviscoplastic multi-axial constitutive model for plastic deformationof MMCs using the Mises-Schleicher yield criterion, which iscapable of describing the multi-axial yield and ow behavior ofMMCs, by using asymmetric tensile and compressive stressstrainresponses as input. Biner and Hu [27] proposed a phase-eld modelto describe the damage evaluation in particle reinforced MMCs dueto particle cracking. In this model, the metal matrix deformation isdescribed by using elasticplastic constitutive law including linearhardening behavior. Comparing to conventional models, such asconstitutive models of void growth and cohesive zone models, theexperimentally validated phase-eld model that they proposedhas the advantage to describe the microstructure and topologicalchanges related to damage evaluation.

Aiming at assessing micro-scale stress rates of MMCs under highplastic strain conditions, which are typical for high-temperatureforming process, Ilie et al. [28] introduced a multi-scale niteelement (FE) modeling approach and two model types to analyze theextrusion of SiC/Al MMCs. The micro-scale model explicitlyembraced the heterogeneous micro-structures of the material,while the macro-scale model was used to simulate the extrusionprocess of the MMCs, which was modeled as homogeneous conti-nuum at this level. Using the proposed multi-scale model, thepredicted macro-scale plastic strain distributions and pressures canbe used to evaluate the risk of damage in the materials duringforming process. Aghdam et al. [29] developed a three-dimensionalmicromechanical FE model to study the interface damage of unidi-rectional SiC/Ti MMCs under hybrid thermal and axial shear loading.By introducing a suitable failure criterion for interface damage, thepredicted stressstrain curve demonstrated better agreement withexperimental data than predictions based on perfectly bonded andfully de-bonded interface. The interface damage study was alsoconducted for off-axis loading in their later work [30].Fig. 4. Nature of line defects in the two different matrix materials: (a) Alarger sizes of particle reinforcements (up to 20 mm).According to the above modeling and experimental studies, the

stressstrain behavior, interface damage or fracture responses canbe predicted; however, the investigated loading conditions inliterature were far from reality of true material removal formachining processes.

2.3. Machinability study

The aim of manufacturing is to achieve near net shapecomponents with required strength and functions. Even thoughMMCs are generally processed near net shape, further machiningoperations are usually inevitable to ensure the correct function forapplication. In this section, a number of experimental studies onMMCs machinability are reviewed. The inuences of machiningconditions, e.g., cutting speed, feed speed and depth of cut, on variousaspects of the machinability are evaluated. Important factors ofmachinability include cutting forces, chip formation, built-up edges(BUEs), surface integrity, shear/friction angles and residual stress.

Different cutting tools, including tungsten carbide (WC) inserts[33] and PCD inserts [34], were used to conduct experimentalinvestigations on the machinability of SiC particulate Al-MMCs inturning operations. Another experimental study for Al-MMCs [35]focused on evaluating the chip compression ratio, chip formation,friction angle, shear angle, normal and shear stress under differentcutting conditions.

Kannan et al. [36] carried out research to understand the role ofductile matrix on the machining performance by estimating linedefects (Fig. 4), resulting from turning operation for aluminareinforced Al-MMCs. The ceramic particle size was in micro-level.

Pramanik et al. [37] experimentally studied the effects ofreinforcement particles on the machining performance of Al-MMCs. The SiC particles average size is 618 mm. The experimentswere carried out using a bar turning process under dry condition.The effect of ceramic particles on cutting forces, surface roughness,

l-7075/10% alumina MMC and (b) Al-6061/10% alumina MMC [36].

ctu

J. Liu et al. / CIRP Journal of Manufacturing Science and Technology 7 (2014) 557060residual stress, chip shape, shear angles and friction angles wereexamined. From the results, complex variation of force proles forthe Al-MMCs and the Al alloy was observed and possible reasonswere summarized to be: (a) different work hardening properties,(b) fracture at the shear plane and tool chip interface for MMCs, (c)different thermal softening behaviors, (d) tool-particle interactionfor MMCs, and (e) different effects of strain and strain rate on forcesof these materials. They [38] also proposed a mechanistic model forpredicting the average cutting forces in turning MMCs reinforcedwith SiC or Al2O3 particles. The forces were categorized into threeaspects, including the chip formation force, the ploughing forceand the particle fracture force.

Since the cutting mechanisms are not well understood yet forMMCs, the experimental study to reveal the nature of MMCscutting behavior demands a large number of cutting tests. In orderto improve the efciency of the experimental study and extractmore information from the experimental results analysis, Design ofExperiments (DOE) methods have been widely applied to study themachinability of MMCs. A Taguchi method-based experimentationstudy using L27 (3

13) orthogonal array was carried out to analyzethe chip formation mechanism in machining Al-MMCs [39,40]. Asimilar Taguchi method was also applied to study the drilling ofhybrid MMCs [41]. Besides, response surface methodology (RSM)was effective to study the effects of cutting conditions on cuttingforces [42] and surface roughness [43].

Machinability studies on micro-reinforced MMCs have beenexperimentally developed to a mature stage, especially onconventional turning operation for Al-MMCs. Currently, there area number of companies who are commercializing the Al-MMCs, suchas Aerospace Metal Composites Ltd. (AMC, UK) Talon Composites-RAC Corporation (US), and TISICS Ltd. (UK). However, there is littleliterature on the machinability of nano-reinforced MMCs. Therefore,

Fig. 5. (a) Actual and (b) simulated microstructures of pearlitic (left); (a) athe micro-machinability study on the Mg-MMCs reinforced bynano-sized ceramic particles is greatly needed in this eld.

3. Cutting process mechanism

3.1. Materials micro-structural effect

3.1.1. Effect of crystalline grain size on micro-machining

(crystallographic effect)

During micro-milling, the micro-structural nature of theworkpiece materials must be considered in order to achieve highsurface quality. The crystalline grain size of the most commonlyused engineering materials suitable for micro-machining isbetween 100 nm and 100 mm [44]. These crystalized materials,such as aluminum, copper, steel and titanium, have broadengineering applications. The order of magnitude overlaps withthe feature size in micro-machining. Moreover, the tool edgeradius (roundness) and preferred feed per tooth value are oftendesigned from several hundreds of nanometers to several micrometers, which is also comparable to the crystalline grain size.Therefore, the effect of crystallographic properties on overallcutting performances plays an important role in micro-machining.

Vogler et al. [45] proposed a micro-structural mapping basedon nite element (FE) simulation (Fig. 5) and studied the effect ofmetallurgical phases on cutting forces. Comprehensive literaturestudies regarding the grain size effect of traditional polycrystallinematerials, such as steel, aluminum, etc., were conducted in [3,44].Chuzhoy et al. [4648] proposed a FE model for the orthogonalcutting of ductile iron. In this study, the different phases of the iron,including ferrite and pearlite, were explicitly modeled withdifferent constitutive models. The proposed model was capableto compute stress, strain, temperature and damage distributions aswell as the size of fracture and decohesion zones. Fig. 6 shows theaccumulated damage during the FE simulation. The grain size inthis study is around tens of micrometers.

3.1.2. Effect of reinforcements on micro-machining

During micro-machining processes, reinforcements in MMCsplay a signicant role in machining performance. Due to the micro-structural inuence of particles or bers in the matrix material,material removal and chip formation mechanism are differentfrom when machining homogeneous material, where only grainsize effect is considered.

In Ref. [49], the matrix deformation and tool-particle inter-actions during orthogonal cutting operation were investigatedusing FE method (Fig. 7). Three regions were dened to explainthe interactions between the tool and micro-sized reinforcementparticles: particle along the cutting path, particle above thecutting path, and particle below the cutting path, where the

al and (b) simulated microstructures of ferritic ductile iron (right) [45].micro-sized particles along the cutting path have both fracture

Fig. 6. Machining damage accumulated during machining ductile iron [47].

and displacement. The evolution of stress and strain elds as wellas some typical physical phenomena, including tool wear, particledebonding, and heterogeneous deformation of matrix, wereinvestigated. We did theoretical and experimental study on SiCnano-particle reinforced MMCs, where the particles along the

understand the micro-machinability of nano- and micro-sizedreinforced MMCs.

3.2. Strengthening effect

Material removal process in cutting operations is essentially aprocess where materials are continuously/intermittently fracturedand then removed under comprehensive fracture criteria. Theenhanced mechanical properties of MMCs, including the yieldstrength and toughness, inuence the materials fracture behaviorssignicantly. Researchers tried to predict the reinforced yield strengthby considering different strengthening mechanisms [5456]. Thethree main strengthening mechanisms include Orowan strengthen-ing mechanism, enhanced dislocation density strengthening mecha-nism and the strengthening mechanism of load-bearing effect.

As widely acknowledged, Orowan strengthening is caused bythe resistance of hard reinforcement particles to the passing ofdislocations. This effect is not a major factor in micro-sizeparticulate-reinforced MMCs, especially for melt-processed MMCswith particles size as 5 mm or larger [57]. However, for nano-sizedparticles, typically in sub-micron level, Orowan strengtheningeffect becomes more prominent [54]. Zhang and Chen proposed amodel to predict the yield strength of nano-reinforced MMCs and

Fig. 7. Workpiece and tool for MMC machining simulation [49].

J. Liu et al. / CIRP Journal of Manufacturing Science and Technology 7 (2014) 5570 61cutting path are prone to displace instead of fracture [50].Similar FE-based techniques can also be applied to machining of

carbon nanotube (CNT) reinforced polymer composite materials.Dikshit et al. proposed a continuum-based microstructuralmaterial model [51] to simulate machining of CNT reinforcedcomposites using a micro-level FE model [52]. In this model, theGearing and Anand failure model calibrated at different tempera-tures were implemented. On average, the model can predictcutting forces with an error of 8% and thrust forces with an error of13.4%. The chip formation mechanism (Fig. 8) was studied usingthis model and a detailed failure mechanism study was furtherconducted in Ref. [53].

According to above literature, the cutting mechanism forceramic-particle reinforced MMCs is not fully understood,especially for nano-reinforced MMCs. Further investigations arerequired to reveal the fundamentals of micro-cutting suchmaterials, in terms of stressstrain distribution, failure mode,chip formation, tool wear, and particle behaviors, etc. Theoreticaland experimental studies should be conducted in order to betterFig. 8. Comparison of experimental anshowed that the strengthened yield strength is governed by thesize and the volume fraction of nanoparticles, the difference in thecoefcients of thermal expansion between the two phases, and thetemperature change after processing [54]. Also, it indicates that forMMCs with particle size smaller than 50 nm, the yield strengthincreases dramatically as the particle size decreases (Fig. 9).

The following equation was proposed to predict the enhancedyield strength:

syc sym1 f load-bearing1 f Orowan1 f dislocatin (1)

where sym is the yield strength of the matrix material; fload-bearingand fOrowan and fdislocation represent the three aforementionedstrengthening mechanisms. The prediction showed good agree-ment with experimental data. However, in reality, materialremoval process is more complicated due to the complex micro-structural effects, and thus cannot be described by yield strengthalone. In this case, the fracture mechanism studies [29,32,58] ofMMCs become highly important and will benet the fundamentals

d simulated chip formation [52].

calculated via dividing the RMS cutting force by the feed pertooth ft and depth of cut da. Three cutting regions were formed withdifferent dominant cutting mechanisms [108,110]. The cuttingenergy in Region I and III changes linearly with the nominal feedper tooth. Region I is the elastic recovery zone and Region IIIdenotes the traditional shearing zone. In Region II, ploughing playsthe most important role, with a small portion of elastic recoveryphenomenon.

By comparing Figs. 10 and 11, it can be seen that:

Due to particle strengthening effect, much more energy is neededto cut the Mg-MMCs with volume fraction of 10 vol.% than cutpure Mg. The peak value when cutting the 10 vol.% Mg-MMCs inthe elastic zone is around 70 GPa; while the value is around10 GPa when cutting pure Mg.

Both the elastic zone and the ploughing zone are wider whencutting the 10 vol.% Mg-MMCs than cutting pure Mg.

J. Liu et al. / CIRP Journal of Manufacturing Science and Technology 7 (2014) 557062of chip formation studies for cutting processes [49,59]. It waspointed out that the relative contribution of load-bearing effect isvery small in nano-reinforced MMCs [55].

3.3. Size effect

In micro-machining process, the ratio of the uncut chipthickness to the effective tool edge radius becomes a signicantfactor inuencing the cutting performance. As this ratio decreases,the specic cutting energy in machining increases nonlinearly [6063]. This phenomenon occurs due to several factors, includingmaterial strengthening effect, nite tool edge radius, and materialseparation effects [60]. We observed similar phenomena whenmicro-milling nano-ceramic particle-reinforced Mg-MMCs, wherethe size effect plays an important role [50].

In our study, the ratio of particle size to uncut chip thickness,and the volume fraction, signicantly affects the micro-millingperformance of MMCs. Therefore, heterogeneous materials expressdifferent phenomena from homogeneous materials. Figs. 10 and11 compare the specic cutting energy trends from experimentsfor pure Mg and 10 vol.% Mg-MMCs (with nano-reinforcements),respectively. The horizontal axis represents the nominal feed pertooth (uncut chip thickness). The vertical axis represents thespecic cutting energy. The Root Mean Square (RMS) values of in-

plane cutting force F F2 F2

q were calculated for 18

Fig. 9. Yield strength as a function of nanoparticle size for different volume fractionsin nano-Al2O3 particulate-reinforced Mg-MMCs [54].in plane x y

different cutting conditions. The specic cutting energy is

Fig. 10. Specic cutting energy vs. nominal feed per tooth for pure Mg [50].3.4. Minimum chip thickness effect

The role of the minimum chip thickness has been studied bymany researchers in the past twenty years both theoretically andexperimentally [45,64,65]. In micro-milling conditions, Weule etal. rstly proposed the existence of minimum chip thickness andits signicant inuence on machined surface quality [66]. Theauthors pointed out that the minimum chip thickness was stronglydependent on material properties. In another theoretical study, Liuet al. proposed an analytical model for the prediction of minimumchip thickness [67]. The model considers comprehensive aspects ofmaterials properties as well as cutting conditions. It accounts forthe effects of thermal softening, strain hardening, cutting velocityand tool edge radius. The minimum chip thickness value can bepredicted from the workpieces and tools thermal-mechanicalproperties.

In our previous study, a comprehensive instantaneous chipthickness model is developed for micro-machining MMCs [50]. Theheterogeneity of materials properties is taken into consideration.

When the uncut chip thickness is smaller than elastic recoverythreshold, only elastic deformation occurs and the deformedmaterial will fully recover to its original position. The SiCnanoparticles comply with the same elastic deformation as theMg matrix and will fully recover to the original positions aftercutting.

As the uncut chip thickness increases beyond the elastic recoverythreshold, the elasticplastic deformation becomes dominant. In

Fig. 11. Specic cutting energy vs. nominal feed per tooth for 10 vol.% Mg-MMCs[50].

this region, it is assumed that a constant percentage of theworkpiece material undergoes elastic deformation. The remain-ing material undergoes plastic deformation. In this case, the SiCparticles cannot recover to their original positions. Since theplastic deformation occurs in this region, the matrix-particleinterface will be damaged, and then leads to mainly particledisplacements.

When the uncut chip thickness increases to the minimum chipthickness, the shearing mechanism plays a major role and

simulation and have become popular in academia, such as Abaqusand LS-Dyna. Complex cutting geometries and material models canbe embedded into the cutting process model conveniently by usingsuch FE platforms.

In recent decades, tool edge radius effect has gained adequateattention from cutting mechanism researchers [7679]. In thesestudies, a 2-Dimentional (2D) orthogonal cutting model wasconstructed to represent the toolworkpiece interaction, wherematerials were treated as homogeneous (Table 4). Nasr et al. [77]

chn

e-me

e-me

e-me

J. Liu et al. / CIRP Journal of Manufacturing Science and Technology 7 (2014) 5570 63continuous chips form. In this situation, the elastic recovery ratedrops to zero. The reinforcement particles in the chips and theuncut material can mostly retain their original relative positionslocally. Although the particles in the separation zones still havefractures and displacements, this effect is negligible comparingto shearing effect.

4. Cutting process modeling

4.1. Chip formation modeling

As seen in Fig. 1, in macro-scale, the chip formation processduring micro-machining can be understood by applying the theoryof minimum chip thickness to the instantaneous chip thicknessmodel. This belongs to the mechanistic process modelingtechnique, which relates the process inputs and the outputs bycombining a comprehensive characterization of the cuttinggeometries. However, due to the complex physics, which governsthe toolworkpiece interactions during micro-machining process,in micro-scale, chip formation cannot be explicitly predicted interms of accurate chip thickness and how the chip deforms as thecutting tool proceeds. Except for the mechanistic process modelingmethod, there are other approaches aiming at a better under-standing of the chip formation. These methods include moleculardynamics (MD) simulation [6870], the Finite Element (FE)analysis simulation, and multi-scale simulation [71,72]. MDsimulation performs analysis in nano-size with resolution to theatomic level, thus is best suitable for nano-metric analysis. FEmethod is capable of predicting cutting forces, temperatures,stresses, strains and machined surface integrity, since theunderlying theory in FE is macro/meso/micro scale continuummechanics. Therefore, by using FE technique, the chip formationcan be modeled and predicted with reasonable accuracy.

In the early stage of computational study of metal cutting, theFE method was used only to obtain intermediate values for semi-mechanistic or empirical models. Ueda et al. [73] presented such amethod to analyze the material removal mechanism in micro-machining ceramics. This method largely depended on fracturemechanism for cutting process. FE was used only to calculate the J-integral around a crack in front of the cutting edge, in order todifferentiate various cutting modes. Later on, rigid-plastic FE beganto prevail in modeling chip formation [74,75], which is used tofurther understand the localized adiabatic deformation forhomogeneous metals, such as copper.

With the development of modern computer technology,FE simulation can be carried out on more advanced solvers.Some commercially available FE solvers are suitable for cutting

Table 4Comparison of FE modeling studies on micro-cutting homogeneous metals.

No. Research purpose Constitutive model Meshing te

1 s, T J-C model A.L.E. 2 Size effect Taylor-based non-local plasticity Adaptive r

3 s, e, T, force Internal state variable plasticity Adaptive r4 Size effect Taylor-based non-local plasticity Adaptive r

5 Grain renement Dislocation density-based model A.L.E. presented an ArbitraryLagrangianEulerian (A.L.E.) FE model tosimulate the effects of tool edge radius on residual stresses whendry turning AISI 316L stainless steel. The JohnsonCook (JC)plasticity was used for material modeling. The analysis wasachieved in two steps. The rst step simulated the cutting process,and the second one did the stress-relaxation process. Coupledthermal-mechanical analysis was carried out in both steps. Theusage of Eulerian formulation avoids the necessity to dene thefailure criterion for chip formation. Ozel et al. [78] applied thesimilar modeling technique to simulate high speed machining ofAISI 4340 steel, in order to extract the stress and temperaturedistributions. In the study conducted by Liu and Melkote [79], theinuence of tool edge radius on size effect was investigated byusing a strain gradient plasticity-based FE model. Orthogonalmicro-cutting simulation was achieved for Al5083-H116. Chipseparation criterion was also ignored via an adaptive re-meshingtechnique. Except for the tool edge radius effect, other researchersput emphasis on either advanced hard-to-machine materials[80,81] or material strengthening mechanisms [60].

Based on the FE modeling approach, the mechanistic models ofmicro-cutting can be further improved by using the parameterscalibrated by FE models. The FE-based chip formation studies forhomogeneous materials are summarized in Table 4. Tool edgeradius has been considered as a dominant factor in micro-cutting.For different materials, different constitutive modeling approacheswere applied. Even though good results can be achieved and matchthe experimental data, the use of the Arbitrary Lagrangian Eulerian(A.L.E.) or adaptive re-meshing technique makes it possible toignore the actual chip separation criterion. According to Atkins[82], this is implausible and implies that plastic ow cannot be thephenomenon explaining the separation of chips from themachined surface.

Three important factors in the FE cutting simulations have beensystematically studied by previous researchers, including thematerial constitutive model, the friction model and the fracturecriterion. Shi and Liu [83] compared four different materialconstitutive models which incorporate strain rate and temperatureeffects. The material models applied in FEA modeling of orthogonalmachining on HY-100 steel include LitonskiBatra [84,85], powerlaw [86], JohnsonCook [87], and Bodner-Partom [88]. Ozel [89]investigated several friction modeling techniques by developingconstant and variable friction coefcient based models. It wasfound that the most accurate one for FEA simulation is the one withvariable friction coefcient. When pure Lagrangian formulation isapplied without adequate re-meshing, a chip separation criterioncannot be avoided. In our previous work [90], the effect of fracturemodel on FEA cutting simulations was systematically studied. The

ique Fracture model Tool edge radius Materials Ref. #

NO YES AISI steel [77,78]

shing NO YES Al5083-H116 [79]

shing NO Sharp Mg-Ca alloy [80]

shing NO Sharp Al5083-H116 [60]

NO YES CP Ti [81]

models include constant fracture strain [9193], JohnsonCook[94], JohnsonCook coupling criterion [95], Wilkins [96,97],modied CockcroftLatham [98], and Bao-Wierzbicki fracturecriterion [99,100]. Based on our result, it is found that damage

mechanical behaviors in a uniaxial manner. Due to the nature ofcutting, the loads applying on the material should be multi-axial.Therefore, materials constitutive model should be reformulated inhigher order.

Table 5Comparison of FE modeling studies on micro-cutting heterogeneous metals.

No. Constitutive model Meshing technique 2D/3D Matrix Reinforcement Particle size Ref. #

1 Internal state variable model [101] Adaptive re-meshing 2D Ferritic and

pearlitic grains

Graphite (10%) mm-sized [4648]

2 Mulliken and Boyce model [102] Adaptive re-meshing 2D Polymer CNT nm-sized [5153]

3 JohnsonCook model NO adaptivity 2D Al6061 Alumina particles

(15 mm)mm-sized [103,104]

4 Equivalent homogeneous material

(EHM) model [105,106]

Adaptive re-meshing 3D A359 SiC particles (20%) mm-sized [107]

5 CowperSymonds model NO adaptivity 2D Aluminum SiC particles (30%) mm-sized [49]

J. Liu et al. / CIRP Journal of Manufacturing Science and Technology 7 (2014) 557064evolution should be considered in cutting process FE simulation.Moreover, the B-W fracture model with consideration of ratedependency, temperature effect and damage evolution gives thebest prediction of chip removal behavior of ductile metals.

These factors are also critical when FE method is applied toheterogeneous materials. However, the FE based chip formationmodeling on heterogeneous materials is still in the early stage.Most of the available research literature on this topic wasconducted in the last decade. In the chip formation modeling forheterogeneous materials, such as ductile iron (crystallographicheterogeneous), polymer-based CNT composites and particulate-reinforced MMCs, the fracture mechanisms of the materials havebeen considered (listed in Table 5). Dikshit et al. [52,53]implemented the Gearing and Anand failure model in order tocapture the difference between ductile and brittle failure modes inthe polymer matrix. For the CNT reinforcement phase, a simplestrain-to-failure criterion was used. Chuzhoy et al. [46,48] alsoconsidered the material damage model by continuously removingthe damaged element during simulation. The experimentalresults of the chip formation are shown in Fig. 12.

Zhu and Kishawy [104] utilized a shear failure model bycomparing effective plastic strain with the damage plastic strainvalue for each element. Similar approach was also applied in thework conducted by Pramanik et al. [49]. However, the failuremodes during micro-cutting particulate reinforced MMCs are farmore complex than the existing models proposed by previousresearchers. More research effort toward the fracture behavior ofthe particulate MMCs is needed both theoretically and experi-mentally. The understanding of failure modes potentially requiresthe application of cohesive zone models so that it is possible tocapture the details of particles effect on micro-cutting. Materialsconstitutive modeling is another aspect requiring more research.Currently, most of the material models take account of theFig. 12. Photomicrographs of machined chips of (aAs it can be seen in Table 5, most of research on micro-cuttingMMCs focus on micro-sized particulate MMCs. There are very fewpublications on the machining of nano-sized particulate MMCs.The research on particle size effect and the micro-cutting of nano-reinforced MMCs will lead to a new area for metal cutting theory.As computing power gets further improved, molecular dynamicssimulation and multi-scale modeling techniques can be essentialanalysis tools in the future.

4.2. Cutting force modeling

Cutting MMCs is considerably difcult due to the extremelyabrasive nature of the reinforcements that causes rapid tool wearand high machining cost [36]. Thus, it is crucial to fully understandthe effect of ceramic particles on the machining process. Based onthe process model, machining quality and cost can be improvedthrough optimizing the cutting conditions for specic compositematerials. As a step toward this goal, cutting force modeling is verycritical.

During the last decade, process models have been developed topredict cutting force at the micro-milling scale [45,108,109]. Jun etal. [110] studied the geometric chip formation mechanism inmicro-milling and proposed a new algorithm to compute theinstantaneous chip thickness by incorporating the minimum chipthickness effect. In their later work [108], the mechanistic model ofmicro-milling forces was proposed. This model considered theeffects of ploughing, elastic recovery, tool run-out and dynamics;and it focused on homogeneous materials. Vogler et al. [45,109]proposed a mechanistic model that explicitly accounts for differentphases when machining heterogeneous materials. The modelpredicted the higher frequency components of cutting forces byconsidering the multiple phases (in micro-scale grain size) in thematerial model. However, as the size of the reinforcement particles) pearlite, (b) ferrite, and (c) ductile iron [46].

decreases to nano-scale, this model is not suitable to predictcutting forces since SiC nanoparticles will not be directly cut bytool edge. Kishawy et al. [111] proposed an energy-basedanalytical force model for orthogonally cutting Al-MMCs. In thismodel, the total specic energy for deformation had beenestimated for the debonding of ceramic particles from thealuminum matrix as a function of volume fraction and materialproperties. The model was validated and applicable for micro-sizedceramic reinforced MMCs in turning conguration. Nano-sizedreinforcements are more prone to escape the cutting than themicro-scale particles during machining because they are smallerthan the tool edge radius. Thus, the cutting mechanism of nano-reinforced heterogeneous materials is seen to be different from themicro-reinforced heterogeneous materials. So far, there is very fewliterature on the explicit modeling of cutting forces for nano-reinforced heterogeneous materials. Therefore, being able topredict cutting forces for nano-reinforced heterogeneous materials

material properties. With the cutting conditions (tool geometrycutting speed, etc.) properly set up in the FE models, the cuttingprocess variables including cutting forces could be predicted.Verication using experimental data is needed in order to ensurereliable force prediction. Another way to utilize the FE method is touse the simulated cutting forces to calibrate mechanistic cuttingforce models. The cutting force coefcients of the mechanistic forcemodel are calibrated using FE simulation data. Then cutting forcecan be predicted using the calibrated empirical mechanistic forcemodel. However, this method also needs the FE model to beproperly veried before using for mechanistic model calibration.For example, in a micro-scale machining application, Afazov et al.[126] proposed a new approach for predicting micro-millingcutting forces using the FE methods. A set of FE analyses wereperformed rstly at different chip loads and cutting speeds, andthen the relationship between cutting forces, chip load and cuttingvelocities could be nonlinearly tted and used in micro-milling

5000

J. Liu et al. / CIRP Journal of Manufacturing Science and Technology 7 (2014) 5570 65become necessary.As for calibration of cutting force coefcients, some previous

researchers expressed the simultaneous force coefcients as anonlinear exponential function [112114]. Wan et al. [114]proposed a genetic procedure to calibrate the force coefcientsusing instantaneous cutting force. An exponent-like function wasproposed to describe the relationship between force coefcientsand uncut chip thickness. The force was predicted using calibratedinstantaneous force coefcients [114118]. This method wasexperimentally validated under conventional milling conditions.Additionally, the method uses the instantaneous cutting forcesignals [115,116]. The accuracy of the force coefcients heavilydepends on where the data is truncated and the length of the data.Other models were developed based on constant cutting forcecoefcients [45,108,119121]. The coefcients in mechanicalmicro-machining were calibrated according to different cuttingmechanisms, such as shearing and ploughing [108,120]. Theminimum chip thickness plays an important role in differentiatingthe cutting mechanisms. Liu et al. [67] developed an analyticalmodel to predict the minimum chip thickness by consideringvarious material properties and cutting conditions. Finite elementmodels can also be used to calibrate cutting force coefcients.However, accurate material models are required and computa-tional load can be high for high quality meshing [61].

However, instead of the above methods, 2-D FE models built fororthogonal cutting can be efciently used to acquire cuttingcoefcients which are essential for cutting force modeling.Researchers used the FE simulation methods to predict cuttingforces for conventional turning [122,123], high speed milling[124], and single point diamond turning [125]. In general, the FEcutting process models were developed with accurately calibrated

Fig. 13. Cutting forces at different cutting conditions on AISI 4340: (a) spindle speed force calculation. The full relation between these variables isexpressed in Eq. (2), where h is uncut chip thickness, v is thetangential cutting velocity and p1p6 are the constants. Thepredicted and experimental cutting force results are shown inFig. 13.

Fc;t p1v p21 exp p3h p4v p51 exp p6h (2)

Altintas and Jin [127] further improved the mechanicsunderstanding of micro-milling by incorporating the effect of tooledge radius. The authors proposed a micro-milling force analyticalmodel from materials constitutive model and friction coefcient.The chip formation process is predicted with a slip-line eld model[76]. The predicted cutting forces are displayed in Fig. 14.

As for heterogeneous materials, Park et al. [128] introduced amethod for mechanistic cutting force model calibration usingmicrostructural FE model for ferrous materials. This methodrequires detailed modeling for the materials microstructures inorder to achieve accurate calibration. In our previous work [50], weproposed another cutting force structures and correspondingcalibration technique by considering the behaviors of reinforce-ment ceramic particles for Mg-MMCs. The simulated cutting forcesare shown in Fig. 15.

4.3. Dynamics modeling

The dynamics modeling of micro-cutting requires fullyunderstanding the behaviors of material-tool-holder system andthe machine tool structures. Prior to these aspects, the fundamen-tal cutting mechanisms are the foundation of dynamic analysis ofmicro-cutting MMCs, because the existence of reinforcements in

rpm, feed speed 2 mm/s; (b) spindle speed 50,000 rpm, feed speed 0.5 mm/s [126].

di

m

J. Liu et al. / CIRP Journal of Manufacturing Science and Technology 7 (2014) 557066Fig. 14. Slot micro-milling with 50 mm axial depth of cut on Brass 260 using 200 mm 20,000 rpm, feed rate: 3 mm/tooth and (b) spindle speed: 40,000 rpm, feed rate: 5 m

0

100

200

For

ce (m

N)

(a) Cutting Forces (X Direction)

ExperimentSimulationthe matrix affects the overall dynamic behaviors [37,45], especiallyfor micro-milling processes.

Filiz and Ozdoganlar [129] presented an analytical model of thetransverse vibration of rotating micro-end mills in the presence oftool alignment errors and tool manufacturing errors. The modelcan be used for micro-tools design and stability analysis of micro-milling processes. The tool tip motion modes are shown in Fig. 16.A more sophisticated dynamics model for micro-milling wasconstructed by Jun et al. [110,130], considering the complex chipformation nature. The stability characteristics due to the regener-ative effect were also studied. A comparison of typical stability lobecontours for micro-milling process is displayed in Fig. 17. Thestability lobes are shown for different combinations of tool lengthand shank projection length.

It was found that there was signicant increase in vibration dueto the unbalance arising from process faults [110,130]. Thus, theestimation of effective process errors/faults [131] and its analysisare essential to mitigate unbalance-induced vibration. It was notedthat the minimum chip thickness effect causes instability whenfeed rate is around the minimum chip thickness.

Based on our extensive literature survey, there is little relevantresearch on how the materials microstructures affect systemdynamics, which is crucial for particulate MMCs machining. Forexample, in micro-milling process, measurements of tool vibrationand tool deection is a challenging task, because the vibrationmeasurement at the shank of the cutting tool can be misleading[130]. During micro-milling, the tool tip is buried into theworkpiece material. Current measurement techniques are able

200 400 600 800 1000 1200 1400

-100

Rotation Angle (deg)

Cutti

ng

Fig. 15. Cutting forces on 10 vol.% SiC nanoparticle reinforced Mg-MMCs at cutting condicut is 20 mm using 1 mm diameter end mill [50].a. cutting tool (with two 308 helical utes) at cutting conditions: (a) spindle speed:/tooth [127].

0

100

200 F

orce

(mN)

(b) Cutting Forces (Y Direction)

ExperimentSimulationto detect the displacement at the cutting tool shank which isdifferent than the actual tool tip deection and vibration.Therefore, the effect of reinforcement particles on the micro-cutting dynamics, tool vibration, tool deection [132], chatterprediction and suppression [133135] will need to be studied forMMC micro-machining.

4.4. Other aspects

Surface measurement and modeling is also difcult since thenature of machined surface generation is complicated anddetermined by numerous factors, as we observed in our previouswork [136]. Vogler et al. [137] built the surface generation modelsfor surface roughness in micro-end milling of single phase andmultiple phase materials based on minimum chip thicknesstheory. The model was able to accurately predict the surfaceroughness for single phase materials. For multi-phase materials,the authors pointed out that surface roughness is affected by threeindependent effects, including: geometric effect, minimum chipthickness effect and the effect of burr formation at the grainboundaries. The effect of reinforcement particles in particulateMMCs still remains unstudied by previous researchers. Cuttingtemperature distribution for micro-cutting is usually capturedand analyzed by infrared (IR) camera [138,139]. Along with thecutting temperature, machined surface residual stress, tool wear,and tool life prediction under the effects of reinforcementparticles are still unclear for particulate MMCs during micro-cutting operations.

200 400 600 800 1000 1200 1400

-200

-100

Rotation Angle (deg)

Cutti

ng

tion: spindle speed is 4000 rpm, feed speed is 0.4 mm/s (ft = 3.0 mm/t) and depth of

Fig. 16. Orbital vibrations for the steady-state harmonic response. The size of each square is 6 mm 6 mm. The static runout is plotted as dashed circles. Dynamic runout isplotted as solid circles [129].

Fig. 17. contour maps of the X direction shank and tool tip vibrations for case (a) shank projection length Ls = 17 mm and tool length Lt = 1.5 mm; and case (b) Ls = 10 mm andLt = 2.5 mm [130].

J. Liu et al. / CIRP Journal of Manufacturing Science and Technology 7 (2014) 5570 67

J. Liu et al. / CIRP Journal of Manufacturing Science and Technology 7 (2014) 5570685. Conclusion

This paper provides a literature review on micro-cuttingceramic-reinforced metal matrix composites (MMCs). Someobservations regarding past work and future directions aresummarized:

1. The cutting mechanism of the nano/micro-sized ceramicparticle reinforced MMCs is not fully understood for micro-machining operations, in terms of stressstrain distribution,failure mode, chip formation, tool wear, and particle fracture/debonding/dislocation.

2. Although there exist a number of studies and theories onmachining micro-reinforced particulate MMCs over the last 25years, further machinability study is still needed. Because theexisting literatures mostly focus on conventional-scaled turn-ing, the theoretical and experimental study in micro-scaledmachining is needed.

3. Multiphase materials performance in micro-cutting has beenstudied by using ductile iron as samples. The material phasesof eutectic heterogeneous materials are different from eachother in crystalline structures; however they have similarmaterial properties in terms of elasticity, plasticity andfracture. The ceramic reinforced MMCs contain multiplematerial phases whose material properties are very different.The eutectic heterogeneous materials behave differently fromengineering-designed MMCs during the cutting process dueto the aforementioned differences including the reinforce-ment particle fracture mechanism. The cutting mechanismsfor MMCs should be redened beyond the understanding ofmultiphase materials, such as ductile irons and CNT reinforcepolymers.

4. Since cutting performance is strongly affected by the cuttingmechanisms in three scales: macro, meso and micro, a thoroughunderstanding of the cutting mechanisms in different scales isrequired.

5. In particulate MMCs, the effects of particle shapes (aspect ratio),particle size and volume fraction have great inuences on themicro-cutting performance. The effects of these factors oncutting mechanisms should bring more attention in order tobetter understand MMCs micro-machining process.

6. As the particle size decreases to nanometer level, thecontinuum mechanics laws can be fundamentally different.FE approach based on continuum assumption will remain asone of the suitable candidates to conduct chip formationsimulation. How to simulate nano-particle reinforced MMCsis challenging until some explicit modeling technique isestablished.

7. The fracture mechanics and criterions for MMCs should becarefully considered to achieve accurate simulation of particlefracture and chip separation. The currently popular techniqueusing A.L.E. or adaptive re-meshing skills in FE is not suitable forheterogeneous material cutting simulation. Homogenizedmaterial properties, including elasticity, plasticity and failuremodes, are good enough to initiate research work on cuttingmechanisms.

8. Process models, including chip formation model, cuttingforce model, tool deection model and surface generationmodel, should be constructed to better understand the micro-machinability of nano- and micro-size reinforced Mg-MMCs.

9. The explicit process models connecting the controllable inputcutting conditions with output variables (e.g., cutting forces,tool deections and generated surface roughness) for advancedheterogeneous MMCs during machining process will benet theindustrial needs for MMCs processing.Acknowledgements

The authors greatly appreciate the funding support from TheNational Science Foundation CMMI (award no. 0927441) and theU.S. Department of Energy (grant no. DE-FOA-0000059).

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