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Pyrolytic carbon (PyC) is extremely biocompatible with high directional strength and unique directional thermal conductivity. PyC is used in biomedical devices like cardiovascular implants and finger prosthesis. Microfeatures on PyC have been proven as performance-driving agents in many cases. This work is focused on micro-electric discharge machining (micro-EDM) characterization of PyC to understand the effect of material/thermal anisotropy on the process response. An L9 Taguchi design of experiments has been performed to analyze the effect of gap voltage, capacitance, and frequency on the MRR, surface quality, and dimensional accuracy. MRR increases by 16% with vibration in AB plane machining. In C plane, the effect of vibration on MRR is not favorable. MRR reduces by 56% if the machining plane changes from AB to C due to the lower thermal conductivity along C. Surface roughness decreases by an order of magnitude if machining plane changes from AB to C; surface roughness of 65nm has been achieved in C plane under certain conditions. The error in dimensional accuracy in C plane is 46% lower than AB plane. EDS shows noncontaminated machined surface. Finally, micro-EDM process has been used to create microfeatures in PyC, which could potentially improve/alter the desired surface quality. [ABSTRACT FROM AUTHOR]

Reverse microelectrical discharge machining (R-MEDM) process is a recent variant of microelectrical discharge machining process capable of fabricating high aspect ratio arrayed microfeatures and textured surfaces. Efficient flushing of the debris particles from the interelectrode gap is essential for process stability, but extremely small interelectrode gaps ( $\sim 5~\mu $ m) make the dispelling of debris difficult, rendering the R-MEDM process infeasible for machining difficult-to-erode materials and creation of engineered/textured surfaces. It has been experimentally observed that the electrode vibrations facilitate the flushing of debris particles and improve the erosion rate, surface morphology, and dimensional accuracy of the machined features. Despite the obvious advantages, the vibration-assisted R-MEDM process, specifically the debris motion and dielectric flow under the effect of vibration, is not very well understood. Consequently, this paper is focused on computational modeling of the debris motion and its interaction with the dielectric fluid under low-amplitude vibrations imparted via a magnetorestrictive actuator. The effects of frequency and amplitude of the electrode vibration on the debris motion have been quantified. The higher local debris velocities and oscillatory motion due to flow reversal potentially reduce the debris agglomeration. As a result, the normal discharge duration, which is responsible for the material erosion, is increased and fabrication of arrayed features on difficult-to-erode materials and creation of surface texture over large areas become feasible. [2013-0394] [ABSTRACT FROM AUTHOR]

Highlights: [•] Finite element modeling of orthogonal micromachining of pyrolytic carbon has been done via damaged plasticity and cohesive zone models. [•] Captures brittle failure and peeling effect during micromachining of layered brittle materials. [•] The force prediction errors in the model lie between 9% and 27%. It also qualitatively captures the chip morphology. [ABSTRACT FROM AUTHOR]

Problem: The prediction of cutting forces is very important in designing mechanical micromachining to ensure geometrical accuracy of the machined feature and avoid tool breakage. These predictions can be done either via analytical models or finite-element models. The finite-element models are precise but usually time consuming to run. Analytical models, on the other hand, are less accurate but computationally much cheaper. The problem here is to integrate these two types of physics-based models and obtain an easy-to-evaluate statistical model that can approximate the machining forces. Approach: We propose performing a sensitivity analysis using the computationally cheap analytical models prior to conducting the computationally intensive finite-element simulations. With the elicited prior knowledge from the sensitivity analysis, a two-stage strategy is presented for designing the finite-element simulations in which customized number of levels can be assigned for each input factor. The finite-element simulation data can then be integrated with the analytical models in developing the final metamodel. Results: We show that the initial sensitivity analysis can reveal critical information about the underlying system and guide us to more efficiently extract information from the finite-element models. The proposed design for the finite-element simulations is comprised of two subarrays and overall can achieve desirable orthogonality and space-filling properties. Compared with using n different levels for all input factors, as in the traditional space-filling design, the new design is more capable for estimating factor interactions while still maintaining the ability to capture necessary nonlinear effects. By using fewer levels, it can also improve the efficiency of estimating the effects when the simulation is subject to stochastic noise. In model validation, our numerical results indicate that the fitted integrated metamodel can more precisely approximate the machining forces than either using the analytical models or the traditional metamodel based on the finite-element simulations alone. [ABSTRACT FROM AUTHOR]

Abstract: Engineered features on pyrolytic carbon (PyC) have been reported to improve the functional performance of the cardiovascular implants. PyC also finds application in thermonuclear components due to its unique directional thermal properties. Note that PyC comprises of stacked layers of brittle graphite-like material and its machining characteristics differ from plastically deformable isotropic materials due to brittle damage and interlaminar decohesion. Consequently, this study is aimed at understanding the mechanics of material removal in the plane of transverse isotropy (horizontally stacked laminae) of PyC via a finite element model. A damaged plasticity material model has been used to capture the effect of material degradation of a brittle material under machining. Uniaxial tension/compression tests have been carried out to calibrate the damaged plasticity model. A surface based cohesive bonding has been used between the layers to simulate the interlaminar decohesion which results in peeling, slipping and delamination during machining. The model predicts the cutting force and thrust forces under different process conditions. The cutting force predictions from the finite element model have been validated against the experimental data for different cutting conditions. In addition, the model also predicts the chip morphology for different machining conditions. The prediction error in the model lies between 2% and 23%. Parametric studies have also been performed to understand the effect of the machining parameters, such as rake angle, uncut chip thickness on the process response. It is found that use of the positive rake angle decreases the cutting forces up to 72%. [Copyright &y& Elsevier]

The objective of this study is to optimize a laser-assisted micro-grooving process designed for micromachining of difficult-to-machine materials such as hard mold/die steels and ceramics. The process uses a relatively low power continuous wave laser beam focused directly in front of a micro-grooving tool to thermally soften the material thereby lowering the cutting forces and associated machine and tool deflections. However, the use of laser heating can produce a detrimental heat-affected zone (HAZ) in the workpiece surface layers. Consequently, the laser and micro-grooving parameters need to be optimized in order to achieve the desired thermal softening effect while minimizing the formation of a HAZ in the material. Although thermal and force models for the hybrid process have been developed for possible use in process optimization, they are computationally intensive and are not accurate enough to produce reliable results. We overcome these deficiencies using a statistical approach. First, easy-to-evaluate metamodels are developed to approximate the complex engineering models. Then, the metamodels are statistically adjusted using real data from the process to make more accurate predictions. The optimization is then carried out on this statistically adjusted metamodels. The optimization strategy is experimentally verified and shown to yield good results. [ABSTRACT FROM AUTHOR]

Laser assisted mechanical micromachining is a process that utilizes highly localized thermal softening of the material by continuous wave laser irradiation applied simultaneously and directly in front of a miniature cutting tool in order to produce micron scale three-dimensional features in difficult-to-machine materials. The hybrid process is characterized by lower cutting forces and deflections, fewer tool failures, and potentially higher material removal rates. The desktop-sized machine used to implement this process has a finite stiffness and deflects under the influence of the cutting forces. The deflections can be of the same order of magnitude as the depth of cut in some cases, thereby having a negative effect on the dimensional accuracy of the micromachined feature. As a result, selection of the laser and cutting parameters that yield the desired reduction in cutting forces and deflection, and consequently an improvement in dimensional accuracy, requires a reliable cutting force model. This paper describes a cutting force model for the laser-assisted microgrooving process. The model accounts for the effect of elastic deflection of the machine X-Y stages on the forces and accuracy of the micromachined feature. The model combines an existing slip-line field based force model with a finite element based thermal model of laser heating and a constitutive material flow stress model to account for thermal softening. Experiments are carried out on H-13 steel (42 HRC (hardness measured on the Rockwell 'C' scale)) to validate the force model. The effects of process parameters, such as laser power and cutting speed, on the forces are also analyzed. The model captures the effect of thermal softening and indicates a 66% reduction in the shear flow stress at 35 W laser power. The cutting force and depth of cut prediction errors are less than 20% and 10%, respectively, for most of the cases examined. [ABSTRACT FROM AUTHOR]

Abstract: Laser-assisted mechanical micromachining (LAMM) is a micro-cutting method that employs highly localized thermal softening of the material by continuous wave laser irradiation focused in front of a miniature cutting tool. However, since it is a heat-assisted process, it can induce a detrimental heat-affected zone (HAZ) in the part. This paper focuses on characterization and prediction of the HAZ produced in a LAMM-based micro-grooving process. The heat-affected zone generated by laser heating of H-13 mold steel (42 HRC) at different laser scanning speeds is analyzed for changes in microstructure and microhardness. A 3-D transient finite element model for a moving Gaussian laser heat source is developed to predict the temperature distribution in the workpiece material. The model prediction error is found to be in the 5–15% range with most values falling within 10% of the measured temperatures. The predicted temperature distribution is correlated with the HAZ and a critical temperature range (840–890°C) corresponding to the maximum depth of the HAZ is identified using a combination of metallography, hardness testing, and thermal modeling. [Copyright &y& Elsevier]

Abstract: Mechanical micro-cutting is emerging as a viable alternative to lithography based micromachining techniques for applications in optics, semiconductors and micro-mold/dies. However, certain factors limit the types of workpiece materials that can be processed using mechanical micromachining methods. For difficult-to-machine materials such as mold and die steels or ceramics, limited cutting tool/machine stiffness and strength are major impediments to the efficient use of mechanical micromachining methods. In addition, at micron length scales of cutting, the effect of tool/machine deflection on the dimensional accuracy of the machined feature can be significant. This paper presents experimental characterization of a novel hybrid laser assisted mechanical micromachining (LAMM) process designed for 3D micro-grooving that involves highly localized thermal softening of the hard material by focusing a solid-state continuous wave laser beam in front of a miniature cutting tool. Micro-scale grooving experiments are conducted on H-13 mold steel (42 HRc) in order to understand the influence of laser variables and cutting parameters on the cutting forces, groove depth and surface finish. The results show that the laser variables significantly influence the process response. Specifically, the mean thrust force is found to decrease by 17% and the 3D average surface roughness increases by 36% when the laser power is increased from 0 to 10W. The groove depths are found to be influenced by the machine (stage) deflection and tool thermal expansion, which affect the actual depth of cut, in the presence of laser heating. In particular, it is found that the accuracy of groove depth improves with laser heating. Explanations for the observed trends are given. [Copyright &y& Elsevier]

This study investigates the influence of the micro-turning operation on the subsurface deformation-induced transformation. The variations in nanohardness, shear transformation zone (STZ) volume, and free volume in the machined subsurface of the Zr-based bulk metallic glass (BMG) have been characterized. Nanoindentation studies reveal that the machined subsurface is strain hardened, a unique phenomenon that has not been reported in Zr-based BMG machining. The work-hardened zone extends until a depth of ∼20 μm from the surface. The quantitative evaluation of the deformation-induced hardening has been done experimentally by nanoindentation followed by the free volume characterization via Differential Scanning Calorimetry (DSC). The Shear Transformation Zone (STZ) volume approach has been used to understand the changes in the machined subsurface induced due to microturning. The STZ volume in the machined region is lower than that in the undeformed zone for all the machining conditions investigated in this work. The enthalpy change obtained using DSC analysis for estimating the change in free volume content of the machined regions correlates with the STZ volume. • Microturning of the Bulk metallic glass induces work hardening on the machined sub-surface. • Nanoindentation can be used as a valuable tool to characterize the work hardening behavior of the machined surface. • Reduced modulus and the serrated flow behavior due to nanoindentation depends on the extent of work-hardening. • Change in the free volume influences the shear transformation zone volume and the hardening observed during nanoindentation. [ABSTRACT FROM AUTHOR]

An increase in the demand for miniaturized components has resulted in the development of mechanical micromachining processes, such as micromilling. However, scaling down the process for micromilling operations require micro-tools, whose stiffness values are orders of magnitude lower than the conventional tools. The limited stiffness of the micro-end mills is a big impediment in machining difficult-to-cut materials, such as hardened steels and Ti-alloys. To address this issue, the cutting forces and hence the chip loads need to be reduced by using very high spindle rotational speeds. However, at lower chip loads ploughing may occur instead of cutting resulting in cutting force variation and high spindle speeds can excite higher order modes. Consequently, high spindle speeds and low chip loads in a tool with limited stiffness can lead to chatter induced dynamic instability which deteriorates the part quality, surface finish and tool life. Hence, identification of stable cutting parameters is necessary to avoid the chatter in high speed micromilling. Since the dynamic stability depends on the speed and the chip load (feed/flute), mechanistic force model with a constant cutting coefficient will yield inaccurate results. In this paper, the mechanistic force model based on velocity and chip load dependent cutting coefficient has been incorporated into the analytical stability model to predict the cutting forces and the stability lobe diagrams for high-speed micromilling of Ti6Al4V. The force predictions from the mechanistic model using velocity and chip load dependent cutting coefficient are in better agreement with experimentally measured forces as compared to constant cutting coefficients. Up to a spindle speed of 70,000 rpm, the maximum prediction errors in stability boundary for a 500 µm diameter end-mill using constant and velocity–chip load dependent cutting coefficients are ~33% and ~11%, respectively. [ABSTRACT FROM AUTHOR]

Abstract: Mechanical micromachining is increasingly finding applications in fabrication of components in various fields, such as, biomedical devices, optics, electronics, medicine, communications and avionics. In order to ensure adequate functionality, there are stringent requirements for form and finish in case of biomedical devices like cochlear implants and metallic optics. This necessitates that the post machined surface must be burr free. To address these issues in micromachining, this paper presents results of an experimental study to investigate the influence of main process parameters i.e. speed, feed rate, depth of cut, tool diameter and number of flutes on the formation of the various types of burrs i.e. exit burrs and top burrs produced during micro-end milling operation. The experiments performed using Taguchi method shows that three types of burr formation mechanisms prevail during micro-end milling operations; these are: lateral deformation of material, bending and tearing of the chip. Also, three types of burrs were observed include: Poisson burr, rollover burr in down milling and tear burr in up milling. Further, it is observed that the depth of cut and the tool diameter are the main parameters, which influence the burr height and thickness significantly. However, the speed and the feed rate have small to negligible effect on the burr thickness and height. Besides the experimental analysis, the paper presents an analytical model to predict the burr height for exit burr. The model is built on the geometry of burr formation and the principle of continuity of work at the transition from chip formation to burr formation. Note that prediction of burr height in micro-end milling is extremely challenging due to the complex geometry of material removal and microstructural effects encountered during cutting at that length scales. The model fares well and the prediction errors range between 0.65 and 25%. [Copyright &y& Elsevier]

This article is focused on the finite element modeling of burr formation in high speed micromilling of Ti6Al4V. Studies show that the burr produced at the up milling side at the exit of the micromilling tool is the biggest among burrs at other locations. Therefore, side exit burr at the up milling side has been modeled through finite element modeling. Johnson cook material constitutive model has been implemented in the formulation of burr formation. Experimental work has been performed to validate the developed model. It is found that the burr height and width obtained from the simulation has been validated experimentally with a maximum error of 15%. It was found from the literature review that the cutting speed is the factor, which influences the burr formation. Therefore, the model has been further extended to study the effect of cutting speed on the burr size. A maximum tool rotation of 200,000 rpm was considered with a tool diameter of 500 μm. It is predicted from the simulation that, the burr size was reduced by 96% (both height and width) if cutting tool speed was increased from 10,000 to 200,000 rpm. Therefore, it is concluded that the cutting speed is the major factor to reduce the burr size in micromilling of Ti6Al4 V. This study shows that the high speed micromachining center can be helpful in producing the micro parts with less or no burrs. It is expected that further extension of the burr formation model can minimize the burr size to zero/near zero size. [ABSTRACT FROM AUTHOR]

In this study, the orthogonal micromachining of a Zr-based bulk metallic glass (BMG) was carried out at different cutting speeds and undeformed chip thicknesses. The work softening behavior of the micromachined sub-surface was characterized via nanoindentation. It was observed that the serrated flow in the load-displacement curves during nanoindentation depends on the previous machining conditions. The softening in the machined subsurface was studied up to a depth of 300 µm and the minimum and the maximum reductions in nanohardness with respect to unmachined region were 13% and 37%, respectively. Furthermore, the shear transformation zone volume of the machined surface was determined and its correlation with the cutting force coefficients K c and K t was observed. Differential scanning calorimetry (DSC) reveals an increase in the free volume due to micromachining of BMG. This work presents a nanoindentation-based framework and insight into the changes occurring in the sub-surface due to severe plastic deformation in BMG. [ABSTRACT FROM AUTHOR]