Modelling of surface finish and material removal rate in rough honing

In the present work influence of different parameters of the rough honing process on surface roughness and material removal rate were studied. Specifically, second order mathematical models are presented for mean average roughness Ra (μm), maximum peak-to-valley roughness Rt (μm) and material removal rate Qm (cm min⁻¹), obtained by means of regression analysis.     

Surface roughness and material removal rate of lapping process on ceramics

Lapping is a widely used surface finishing process for ceramics. An experimental investigation is conducted into the lapping of alumina, Ni−Zn ferrite and sodium silicate glass using SiC abrasive to study the effect of process parameters, such as abrasive particle size, lapping pressure, and abrasive concentration, on the surface roughness and material removal rate during lapping. A simple model is developed based on the indentation fracture and abrasive particle distribution in the slurry to explain various aspects of the lapping process. The model provides predictions for the surface roughness,R _a andR _t , on the machined surface and rough estimation for the material removal rate during lapping. Comparison of the predictions with the experimental measurements reveals same order of magnitude accuracy.     

固着磨料加工碳化硅反射镜的材料去除率及表面粗糙度的理论研究

本文基于固着磨料加工碳化硅反射镜的微观作用原理，理论上定量分析探讨了金刚石磨料压入碳化硅工件的深度对材料去除率、光学元件表面粗糙度的影响，分别获得了材料去除率数学模型及粗糙度的仿真计算结果。通过去除率及粗糙度的实验与理论模型的对比结果来看，实验值虽与理论值有偏差，但基本稳定在同一数量级内，由此验证了理论分析的正确性。固着磨料工艺的这一易于理论预测的特性对实际的光学加工有着极为重要的意义，因此这种较为新颖的固着磨料工艺在碳化硅反射镜加工领域内有着广阔的应用前景。     

Theoretical model of brittle material removal fraction related to surface roughness and subsurface damage depth of optical glass during precision grinding

Brittle material removal fraction (BRF) is defined as the area fraction of brittle material removed on machined surface. In the present study, a novel theoretical model of BRF was proposed based on indentation profile caused by intersecting of lateral cracks. The proposed model is related to surface roughness and the subsurface damage (SSD) depth of optical glass during precision grinding. To investigate the indentation profile, indentation tests of K9 optical glass were conducted using single random-shape diamond grains. The experimental results indicate that the indentation profile is an exponent function. To verify the proposed BRF model, BRF, surface roughness and SSD depth of K9 optical glasses were investigated by a series of grinding experiments with different cutting depths. The experimental results show that BRF is dependent on surface roughness and SSD depth. The relationship between BRF, surface roughness and SSD depth is in good accordance with the proposed theoretical model. The proposed BRF model is a reasonable approach for estimating surface roughness and SSD depth during precision grinding of optical glass.     

Multi-objective optimization using Taguchi based grey relational analysis for micro-milling of Al 7075 material with ball nose end mill

This study was carried out to understand micro-milling of aluminum material with ball nose end mill and consisted of four stages: experimental work, modelling, mono and multi objective optimization. In the first stage (experimental work), micro-milling experiments were carried out using Taguchi method. The effects of spindle speed, feed per tooth and depth of cut on tool wear, force and surface roughness were investigated. Cutting tools and workpiece surfaces were also inspected via scanning electron microscope. Adhesion and abrasion wear mechanisms during micro-milling of aluminum were observed. Workpiece surfaces had the accumulations of plastically deformed workpiece material due to the high ductility of aluminum. In the second stage (modelling), all data gathered in the experimental works were utilized to formulate first-order models with interaction. These first-order models with interaction could be used to predict responses in micro-milling of aluminum with a minor error. In the third stage (mono-objective optimization), responses were used alone in optimization study as an objective function. To minimize all responses, Taguchi’s signal to noise ratio was used. The effect of control factors on responses was determined by analysis of variance. In the fourth stage (multi objective optimization), responses were optimized simultaneously using grey relational analysis.     

An analytical model of the material removal rate between elastic and elastic-plastic deformation for a polishing process

This paper develops an analytical model for the material removal rate during specimen polishing. The model is based on the micro-contact elastic mechanics, micro-contact elastic-plastic mechanics and abrasive wear theory. The micro-contact elastic mechanics between the pad-specimen surfaces used the Greenwood and Williamson elastic model. The micro-contact elastic-plastic mechanics between specimen and particle, as well as the micro-contact elastic mechanics between particle and pad, are also analyzed. The cross-sectional area of the worn groove in the specimen is considered as trapezoidal area. A close-form solution of material removal rate from the specimen surface is the function of average diameter of slurry particles, pressure, the specimen/pad sliding velocity, Equivalent Young’s modulus, RMS roughness of the pad, and volume concentration of the slurry particle.     

A review on material removal mechanism in electrochemical discharge machining (ECDM) and possibilities to enhance the material removal rate

The concept of electrochemical discharge machining (ECDM), also known as electrochemical spark machining (ECSM), was presented for the first time in 1968. Since then, this technology remains as research topic and was never explained seriously for industrial applications. The ECDM is a non-traditional machining technology used for machining of electrically non-conducting materials like glass, ceramics, quartz, etc. The literature reveals that the concept of mechanism of material removal in this machining process is not yet understood well. However, phenomena involved in the material removal needs to be investigated well in order to improve the process. In this paper, the concept of mechanism of material removal in ECDM is reviewed till date; scopes for further research have been identified. Possible future efforts to enhance the material removal rate in ECDM are also discussed.     

Modelling of surface finish,electrode wear and material removal rate in electrical discharge machining of hard-to-machine alloys

Hard-to-machine alloys are commonly used for industrial applications in the aeronautical, nuclear and automotive sectors, where the materials must have excellent resistance to corrosion and oxidation, high temperature resistance and high mechanical strength. In this present study the influence of different parameters of the electrical discharge machining process on surface roughness, electrode wear and material removal rate have been studied. Regression techniques are employed to model arithmetic mean deviation Ra (μm), peak count Pc (1/cm), material removal rate MRR (mm³/min) and electrode wear EW (%). All these parameters have been studied in terms of current intensity supplied by the generator of the electrical discharge machine I (A), pulse time t_i (μs), duty cycle η and open-circuit voltage U (V). This modelling allows us to obtain mathematical data and models to predict that the most influential factor in MRR and Ra is the current intensity and in the case of EW and Pc is the pulse time.     

Tomography of insulating biological and geological materials using focused ion beam (FIB) sectioning and low-kV BSE imaging

Tomography in a focused ion beam (FIB) scanning electron microscope (SEM) is a powerful method for the characterization of three-dimensional micro- and nanostructures. Although this technique can be routinely applied to conducting materials, FIB–SEM tomography of many insulators, including biological, geological and ceramic samples, is often more difficult because of charging effects that disturb the serial sectioning using the ion beam or the imaging using the electron beam. Here, we show that automatic tomography of biological and geological samples can be achieved by serial sectioning with a focused ion beam and block-face imaging using low-kV backscattered electrons. In addition, a new ion milling geometry is used that reduces the effects of intensity gradients that are inherent in conventional geometry used for FIB–SEM tomography.     

A study of the Taguchi optimization method for surface roughness in finish milling of mold surfaces

The objective of this paper is to develop a Taguchi optimization method for low surface roughness in terms of process parameters when milling the mold surfaces of 7075-T6 aluminum material. Considering the process parameters of feed, cutting speed, axial-radial depth of cut, and machining tolerance, a series of milling experiments were performed to measure the roughness data. A regression analysis was applied to determine the fitness of data used in the Taguchi optimization method using milling experiments based on a full factorial design. Taguchi orthogonal arrays, signal-to-noise (S/N) ratio, and analysis of variance (ANOVA) are used to find the optimal levels and the effect of the process parameters on surface roughness. A confirmation experiment with the optimal levels of process parameters was carried out in order to demonstrate the effectiveness of the Taguchi method. It can be concluded that Taguchi method is very suitable in solving the surface quality problem of mold surfaces.     

Optimization of surface roughness and tool wear in hard turning of austempered ductile iron (grade 3) using Taguchi method

In this work, the cutting parameters are optimized in hard turning of ADI using carbide inserts based on Taguchi method. The cutting insert CVD coated with AL₂O₃/MT TICN. Experiments have been carried out in dry condition using L₁₈ orthogonal array. The cutting parameters selected for machining are cutting speed, feed rate and depth of cut with each three levels, nose radius in two levels maintaining other cutting parameters constant. The ANOVA and signal to noise ratio are used to optimize the cutting parameters. The cutting speed is the most dominant factor affecting the surface roughness and tool wear. In optimum cutting condition, the confirmation tests are carried out. The optimum cutting condition results are predicted using signal to noise ratio and regression analysis. The predicted and experimental values for surface roughness and tool wear adhere closer to 9.27% and 1.05% of deviations respectively.     

Experimental investigation and analytical modelling of the effects of process parameters on material removal rate for bonnet polishing of cobalt chrome alloy

Cobalt chrome alloys are the most extensively used material in the field of total hip and total knee implants, both of which need highly accurate form and low surface roughness for longevity in vivo. In order to achieve the desired form, it is extremely important to understand how process parameters of the final finishing process affect the material removal rate. This paper reports a modified Preston equation model combining process parameters to allow prediction of the material removal rate during bonnet polishing of a medical grade cobalt chrome alloy. The model created is based on experiments which were carried out on a bonnet polishing machine to investigate the effects of process parameters, including precess angle, head speed, tool offset and tool pressure, on material removal rate. The characteristic of material removal is termed influence function and assessed in terms of width, maximal depth and material removal rate. Experimental results show that the width of the influence function increases significantly with the increase of the precess angle and the tool offset; the depth of the influence function increases with the increase of the head speed, increases first and then decrease with the increase of the tool offset; the material removal rate increases with the increase of the precess angle non-linearly, with the increase of the head speed linearly, and increases first then decreases with the increase of the tool offset because of the bonnet distortion; the tool pressure has a slight effect on the influence function. The proposed model has been verified experimentally by using different Preston coefficients from literature. The close values of the experimental data and predicted data indicate that the model is viable when applied to the prediction of the material removal rate in bonnet polishing.     

A grey-fuzzy modeling for evaluating surface roughness and material removal rate of coated end milling insert

The prime factor for selecting equipment is its performance capability and reliability without compromising on quality. Materials for aerospace application such as aluminum and its alloys have limited applications because of their complications in machining, effectively and economically. There is no further development in raising the effectiveness above the optimal level in cutting tool materials. The surface roughness influences the determination of the quality of the product. The present study focuses on finding optimal end milling process parameters by considering multiple performance characteristics using grey fuzzy approach. In this work, Aluminum Alloy 6082T6 (AA6082T6) is used as workpiece material which was end milled using Aluminum Chromo Nitride (AP3) coated milling insert. Three process performance parameters namely Centre Line Average Roughness (Ra), Root Mean Square Roughness (Rq) and Material Removal Rate (MRR) were optimized. The grey output is fuzzified into five membership functions and also with twenty-seven rules. Grey Fuzzy Reasoning Grade (GFRG) is developed and the optimal values were found out from the Grey relational grade. The result of the Analysis of Variances (ANOVA) shows that the maximum contribution in the depth cut is (31.785%) followed by feed (28.212%). Moreover, Adaptive Neuro-Fuzzy Inference System (ANFIS) model has been developed with the help of the same input values compared to the performance of the fuzzy logic model. With the help of detailed analysis, it has been found that the fuzzy logic based model gives more reasonable results when compared to ANFIS model.     

Optimisation of parameters affecting surface roughness of Co28Cr6Mo medical material during CNC lathe machining by using the Taguchi and RSM methods

This study involves modelling of experimental data of surface roughness of Co28Cr6Mo medical alloy machined on a CNC lathe based on cutting parameters (spindle rotational speed, feed rate, depth of cut and tool tip radius). In order to determine critical states of the cutting parameters variance analysis (ANOVA) was applied while optimisation of the parameters affecting the surface roughness was achieved with the Response Surface Methodology (RSM) that is based on the Taguchi orthogonal test design. The validity of the developed models necessary for estimation of the surface roughness values (Ra, Rz), was approximately 92%. It was found that for Ra 38% of the most effective parameters is on the tool tip radius, followed by 33% on the feed rate whereas for Rz tool tip radius occupied 43% with the feed being at 33% rate. To achieve the minimum surface roughness, the optimum values obtained for spindle rpm, feed rate, depth of cut and tool tip radius were respectively, 318 rpm, 0.1 mm/rev, 0.7 mm and 0.8 mm.     

Measurement and analysis of surface roughness in turning of aerospace titanium alloy (gr5)

Titanium alloys are extensively used in aerospace, biomedical applications and they are used in corrosive environments. In this study, the effect of cutting parameters on the surface roughness in turning of titanium alloy has been investigated using response surface methodology. The experimental studies were conducted under varying cutting speeds, feed and depths of cut. The chip formation and SEM analysis are discussed to enhance the supportive surface quality achieved in turning. The work material used for the present investigation is commercial aerospace titanium alloy (gr5) and the tool used is RCMT 10T300 – MT TT3500 round insert. The equation developed using response surface methodology is used for predicting the surface roughness in machining of titanium alloy. The results revealed that the feed was the most influential factor which affect the surface roughness.     

Imaging of intracellular spherical lamellar structures and tissue gross morphology by a focused ion beam/scanning electron microscope (FIB/SEM)

We report the use of a focused ion beam/scanning electron microscope (FIB/SEM) for simultaneous investigation of digestive gland epithelium gross morphology and ultrastructure of multilamellar intracellular structures. Digestive glands of a terrestrial isopod (Porcellio scaber, Isopoda, Crustacea) were examined by FIB/SEM and by transmission electron microscopy (TEM). The results obtained by FIB/SEM and by TEM are comparable and complementary. The FIB/SEM shows the same ultrastructural complexity of multilamellar intracellular structures as indicated by TEM. The term lamellar bodies was used for the multillamellar structures in the digestive glands of P. scaber due to their structural similarity to the lamellar bodies found in vertebrate lungs. Lamellar bodies in digestive glands of different animals vary in their abundance, and number as well as the thickness of concentric lamellae per lamellar body. FIB/SEM revealed a connection between digestive gland gross morphological features and the structure of lamellar bodies. Serial slicing and imaging of cells enables easy identification of the contact between a lamellar body and a lipid droplet. There are frequent reports of multilamellar intracellular structures in different vertebrate as well as invertebrate cells, but laminated cellular structures are still poorly known. The FIB/SEM can significantly contribute to the structural knowledge and is always recommended when a link between gross morphology and ultrastructure is investigated, especially when cells or cellular inclusions have a dynamic nature due to normal, stressed or pathological conditions.     

Parametric optimization for surface roughness, kerf and MRR in wire electrical discharge machining (WEDM) using Taguchi design of experiment

This paper reports the effect and optimization of eight control factors on material removal rate (MRR), surface roughness and kerf in wire electrical discharge machining (WEDM) process for tool steel D2. The experimentation is performed under different cutting conditions of wire feed velocity, dielectric pressure, pulse on-time, pulse off-time, open voltage, wire tension and servo voltage by varying the material thickness. Taguchi’s L18 orthogonal array is employed for experimental design. Analysis of variance (ANOVA) and signal-tonoise (S/N) ratio are used as statistical analyses to identify the significant control factors and to achieve optimum levels respectively. Additionally, linear regression and additive models are developed for surface roughness, kerf and material removal rate (MRR). Results of the confirmatory experiments are found to be in good agreement with those predicted. It has been found that pulse on-time is the most significant factor affecting the surface roughness, kerf and material removal rate.     

Performance studies of multilayer hard surface coatings (TiN/TiCN/Al2O3/TiN) of indexable carbide inserts in hard machining: Part-II (RSM,grey relational and techno economical approach)

This paper presents the mathematical modelling and parametric optimization on flank wear and surface roughness based on response surface methodology and grey-based Taguchi method in finish hard turning of AISI 4340 steel (HRC 47 ± 1) using multilayer coated carbide (TiN/TiCN/Al₂O₃/TiN) insert under dry environment. The economical feasibility of utilizing multilayer TiN coated carbide insert has been described. Model adequacy has been checked using correlation coefficients. From main effect, it is evident that, cutting speed is the most significant factor for flank wear followed by depth of cut and feed. Again, feed is the most significant factor for surface roughness followed by cutting speed and depth of cut. The coefficient of determination (R²) is more than 75% for RSM models developed, which shows the high correlation exist between the experimental and predicted values. The experimental vs. predicted values of flank wear and surface roughness (Ra and Rz) are also found to be very close to each other implying significance of models developed. The improvement of grey relational grade from initial parameter combination (d2–f3–v4) to the optimal parameter combination (d1–f1–v3) is found to be 0.3093 using grey relational analysis coupled with Taguchi method for simultaneous optimization of responses. Flank wear (VBc) and surface roughness parameters (Ra and Rz) are decreased 1.9, 2.32 and 1.5 times respectively considering optimal parametric combinations for multi-responses. The calculated total machining cost per part is only Rs. 3.17 due to higher tool life (47 min at their optimal level) of multilayer TiN coated carbide insert. It brings to the reduction of downtime and increases the savings.