Impact of graphite particle on milling of Al/15Al2O3 and Al/15Al2O3/5Gr composites

ABSTRACT

Hybrid Metal Matrix Composites (MMCs) are a new class of composites, formed by a combination of the metal matrix and more than one type of reinforcement having different properties. Machining of MMCs is a difficult task because of its heterogeneity and abrasive nature of reinforcement, which results in excessive tool wear and inferior surface finish. This paper investigates experimentally the addition of graphite (Gr) on cutting force, surface roughness and tool wear while milling Al/15Al₂O₃ and Al/15Al₂O₃/5Gr composites at different cutting conditions using tungsten carbide (WC) and polycrystalline diamond (PCD) insert. The result reveals that feed has a major contribution on cutting force and tool wear, whereas the machined surface roughness was found to be more sensitive to speed for both composite materials. The incorporation of graphite reduces the coefficient of friction between the tool–workpiece interfaces, thereby reducing the cutting force and tool wear for hybrid composites. The surface morphology and worn tool are analyzed using scanning electron microscope (SEM). The surface damage due to machining extends up to 200 µm for Al/15Al₂O₃/5Gr composites, which is beyond 250 µm for Al/15Al₂O₃ composites.     

Multi-attribute optimization of end milling epoxy granite composites using TOPSIS

Epoxy granite composites are identified and recognized as better materials for machine tool applications due to inherent damping properties. However, end milling of these composites has not been explored much. Milling of epoxy granite composites presents a number of problems, namely, cutting forces and surface roughness appear during machining. This research work focuses on end milling of epoxy granite composite specimens using high-speed steel end mill cutter by varying the cutting conditions such as spindle speed and feed with a uniform depth of cut and selection of optimal machining parameters. The experimental runs of 27 different trials were carried out and three different attributes such as thrust force, tangential force, and surface roughness were analyzed. This research work presents a sequential procedure for machining parameters selection. Selection of optimal machining parameters is done on the basis of Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method.     

Prediction of cutting force based on machining parameters on AL7075-T6 aluminum alloy by response surface methodology in end milling

Cutting forces modeling is the basic to understand the cutting process, which should be kept in minimum to reduce tool deflection, vibration, tool wear and optimize the process parameters in order to obtain a high quality product within minimum machining time. In this paper a statistical model has been developed to predict cutting force in terms of geometrical parameters such as rake angle, nose radius of cutting tool and machining parameters such as cutting speed, cutting feed and axial depth of cut. Response surface methodology experimental design was employed for conducting experiments. The work piece material is Aluminum (Al 7075-T6) and the tool used is high speed steel end mill cutter with different tool geometry. The cutting forces are measured using three axis milling tool dynamometer. The second order mathematical model in terms of machining parameters is developed for predicting cutting forces. The adequacy of the model is checked by employing ANOVA. The direct effect of the process parameter with cutting forces are analyzed, which helps to select process parameter in order to keep cutting forces minimum, which ensures the stability of end milling process. The study observed that feed rate has the highest statistical and physical influence on cutting force.     

Optimization of Dry Machining Parameters for High-Purity Graphite in End-Milling Process

The machining factors affecting the tool wear and surface finish produced in the end milling process are generally the cutting speed, the feed rate, the depth of cut, etc. This paper describes a study that identifies the influence of the machining parameters on the groove width and the surface roughness average for the end-milling of high-purity graphite under dry machining conditions. The experiments are based on an orthogonal arrays and grey relational analysis method is then applied to determine an optimal machining parameter setting. The dimensional accuracy of the groove width and the surface roughness average are selected as the quality targets. In this study, the feed rate is the most significant controlled factors for the machining process according to the weighted sum grade of the Δ and the R _a .     

Experimental Investigation on Rotary Ultrasonic Face Grinding of SiCp/Al Composites

SiCp/Al composites have been widely used in many fields such as aerospace, automobile, advanced weapon system, etc. But this kind of material, especially with high volume fraction, is difficult to machine due to the reinforced particles existing in matrix, which has limited its further application. Rotary ultrasonic machining (RUM) has many excellent features and it has never been used to machine SiCp/Al composites. In order to improve the machinability and application of SiCp/Al composites, the rotary ultrasonic face grinding experiments of SiCp/Al composites reinforced with 45% volume SiC particles were carried out to investigate cutting force, surface quality, tool wear, and abrasive chip shapes. The experimental results indicate that ultrasonic vibration could reduce cutting force, surface roughness, surface defects, and increase plastic removal ratio. The cutting force could be lowered by an average of 13.86% and the surface roughness could be lowered by an average of 11.53%. The examined results of tool wear patterns suggest that tool wear is mainly caused by grain breakage and grain fall-off. Grinding wheel blockage and grinding burn were not observed in machining process.     

Experimental Study of Surface Roughness and Tool Flank Wear during Hybrid Milling

Two advanced machining methods such as thermally enhanced machining and ultrasonic-assisted machining are recently considered in many studies. In this article, a new hybrid milling process is presented by gathering the characteristics of these two methods. In order to determine the axial depth of cut and engagement in the process, three-dimensional thermal finite-element analysis is applied to determine the dimensions of softened materials. Finite-element modal analysis is used to determine the dimensions and clamping state of the workpiece while cutting area has the highest vibration amplitude. Full factorial experimental design is applied to investigate the effect of hybrid machining parameters on the surface roughness and tool wear. Tool flank wear was investigated under the condition of constant cutting speed during different period of times. Hybrid milling process with an amplitude of 6 µm and a temperature of 900°C creates a surface with 42% lower roughness in comparison to conventional milling in feed 0.08 mm/tooth. In a study of tool flank wear, the results show that application of TEUAM decreases flank wear at least 16% in comparison to all other processes.     

Optimization of Machining Characteristics for Al／SiCp Composites using ANN／GA

The present work is focused on optimization of machining characteristics of Al/SiCp composites.The machining characteristics such as specific energy,tool wear and surface roughness were studied.The parameters such as volume fraction of SiC,cutting speed and feed rate were considered.Artificial neural networks(NN) was used to train and simulate the experimental data.Genetic algorithms(GA) was interfaced with ANN to optimize the machining conditions for the desired machining characteristics .Validation of optimized results was also performed by confirmation experiments.     

Effect of cutting speed on the performance of Al2O3 based ceramic tools in turning nodular cast iron

This paper presents the results of an experimental investigation on the effect of cutting speed in turning nodular cast iron with alumina (Al₂O₃) based ceramic tools. Three different alumina based ceramic cutting tools were used, namely TiN coated Al₂O₃ + TiCN mixed ceramic, SiC whisker reinforced Al₂O₃ and uncoated Al₂O₃ + TiCN mixed ceramic tool. Turning experiments were carried out at four different cutting speeds, which were 300, 450, 600 and 750 m/min. Depth of cut and feed rate were kept constant at 1 mm and 0.1 mm/rev, respectively, throughout the experiments. Tool performance was evaluated with respect to tool wear, surface finish produced and cutting forces generated during turning. Uncoated Al₂O₃ + TiCN mixed ceramic was the worst performing tool with respect to tool wear and was the best with respect to surface finish. SiC whisker reinforced Al₂O₃ exhibited the worst performance with respect to cutting forces. If tool wear, surface finish and cutting force results are considered together, among the three tools studied, TiN coated Al₂O₃ + TiCN mixed ceramic tool is the most suitable one for turning nodular cast iron, especially at high cutting speeds (V_c > 600 m/min).     

Tool condition monitoring in milling based on cutting forces by a neural network

Automated machining systems require reliable online monitoring processes. The application of a multilayered neural network for tool condition monitoring in face milling is introduced and evaluated against cutting force data. The work uses the back-propagation algorithm for training neural network of 5 2 10 2 2 architecture. An artificial neural network was used for feature selection in order to estimate flank wear ( Vb ) and surface roughness ( Ra ) during the milling operation. The relationship of cutting parameters with Vb and Ra was established. The sensor selection using statistical methods based on the experimental data helps in determining the average effect of each factor on the performance of the neural network model. This model, including cutting speed, feed rate, depth of cut and two cutting force components (feed force and vertical Z -axis force), presents a close estimation of Vb and Ra . Therefore, the neural network with parallel computation ability provides a possibility for setting up intelligent sensor systems.     

Tool wear mechanisms in axial ultrasonic vibration assisted milling in-situ TiB2/7050Al metal matrix composites

The in-situ TiB₂ particle reinforced aluminum matrix composites are materials that are difficult to machine, owing to hard ceramic particles in the matrix. In the milling process, the polycrystalline diamond (PCD) tools are used for machining these materials instead of carbide cutting tools, which significantly increase the machining cost. In this study, ultrasonic vibration method was applied for milling in-situ TiB₂/7050Al metal matrix composites using a TiAlN coated carbide end milling tool. To completely understand the tool wear mechanism in ultrasonic-vibration assisted milling (UAM), the relative motion of the cutting tool and interaction of workpiecetool-chip contact interface was analyzed in detail. Additionally, a comparative experimental study with and without ultrasonic vibration was carried out to investigate the influences of ultrasonic vibration and cutting parameters on the cutting force, tool life and tool wear mechanism. The results show that the motion of the cutting tool relative to the chip changes periodically in the helical direction and the separation of tool and chip occurs in the transverse direction in one vibration period, in ultrasonic vibration assisted cutting. Large instantaneous acceleration can be obtained in axial ultrasonic vibration milling. The cutting force in axial direction is significantly reduced by 42%-57%, 40%-57% and 44%-54%, at different cutting speeds, feed rates and cutting depths, respectively, compared with that in conventional milling. Additionally, the tool life is prolonged approximately 2-5 times when the ultrasonic vibration method is applied. The tool wear pattern microcracks are only found in UAM. These might be of great importance for future research in order to understand the cutting mechanisms in UAM of in-situ TiB₂/7050Al metal matrix composites.The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-020-00294-2     

Multiple Performance Optimization of Machining Parameters on the Machining of GFRP Composites Using Carbide (K10) Tool

The present investigation focuses on the multiple performance machining characteristics of GFRP composites produced through filament winding. Grey relational analysis was used for the optimization of the machining parameters on machining GFRP composites using carbide (K10) tool. According to the Taguchi quality concept, a L27, 3-level orthogonal array was chosen for the experiments. The machining parameters namely work piece fiber orientation, cutting speed, feed rate, depth of cut and machining time have been optimized based on the multiple performance characteristics including material removal rate, tool wear, surface roughness and specific cutting pressure. Experimental results have shown that machining performance in the composite machining process can be improved effectively by using this approach.     

Fuzzy Modeling and Analysis of Machining Parameters in Machining Titanium Alloy

Titanium alloys are utilized in many engineering fields such as chemical, industrial, marine, and aerospace due to their unique properties. Machining of these materials causes severe problems. At high temperatures, they become chemically active and tend to react with tool materials. In the present study, fuzzy logic (a tool in artificial intelligence) is used for the prediction of cutting parameters in turning titanium alloy (Ti-6Al-4V). The parameters considered in this study are cutting speed, feed, and the depth of cut. Fuzzy rule-based modeling is employed for prediction of tool flank wear, surface roughness, and specific cutting pressure in machining of titanium alloy. These models can be effectively used to predict the tool flank wear, surface roughness, and specific cutting pressure in machining of titanium alloys. Analysis of the influences of the individual important machining parameters on the responses have been carried out and presented in this study.     

Optimization for Turning of Al-6061-SiC-Gr Hybrid Nanocomposites Using Response Surface Methodologies

Metal matrix composites have cemented their applicability in industrial sector by virtue of their excellent mechanical properties. However, work has largely been done on the studies related to macro/microsize particles. This work has been aimed to evaluate the influence of input parameters in turning of Al-6061-SiC-Gr hybrid nanocomposites. This article evaluates the effect of process parameters on the cutting force and average roughness of the machined surface in turning of Al-6061-SiC-Gr nanocomposites. The experiments were designed using CCD, and cutting force and roughness were evaluated using response surface methodology. Statistical models were generated. The results of the study indicated that feed rate and depth of cut are the major influencing factors in descending order for the cutting force. The analysis of surface roughness revealed that both these factors are having identical effect. The cutting speed had little effect on cutting force and an improvement is seen in surface finish. The experiments also revealed that tool wear is negligible for nanocomposites. The software-predicted values and the experimentally obtained values of the responses were acceptably close to each other with an error percentage of less than 5%. Using response surface optimization, optimal combinations of machining parameters are also obtained.     

Optimization of Dry Machining Parameters for High-Purity Graphite in End-Milling Process

The machining factors affecting the tool wear and surface finish produced in the end milling process are generally the cutting speed, the feed rate, the depth of cut, etc. This paper describes a study that identifies the influence of the machining parameters on the groove width and the surface roughness average for the end-milling of high-purity graphite under dry machining conditions. The experiments are based on an orthogonal arrays and grey relational analysis method is then applied to determine an optimal machining parameter setting. The dimensional accuracy of the groove width and the surface roughness average are selected as the quality targets. In this study, the feed rate is the most significant controlled factors for the machining process according to the weighted sum grade of the Δ and the R_a.     

Experimental study on the meso-scale milling of tungsten carbide WC-17.5Co with PCD end mills

Tungsten carbide is a material that is very difficult to cut, mainly owing to its extreme wear resistance. Its high value of yield strength, accompanied by extreme brittleness, renders its machinability extremely poor, with most tools failing. Even when cutting with tool materials of the highest quality, its mode of cutting is mainly brittle and marred by material cracking. The ductile mode of cutting is possible only at micro levels of depth of cut and feed rate. This study aims to investigate the possibility of milling the carbide material at a meso-scale using polycrystalline diamond (PCD) end mills. A series of end milling experiments were performed to study the effects of cutting speed, feed per tooth, and axial depth of cut on performance measures such as cutting forces, surface roughness, and tool wear. To characterize the wear of PCD tools, a new approach to measuring the level of damage sustained by the faces of the cutter's teeth is presented. Analyses of the experimental data show that the effects of all the cutting parameters on the three performance measures are significant. The major damage mode of the PCD end mills is found to be the intermittent micro-chipping. The progress of tool damage saw a long, stable, and steady period sandwiched between two short, abrupt, and intermittent periods. Cutting forces and surface roughness are found to rise with increments in the three cutting parameters, although the latter shows signs of reduction during the initial increase in cutting speed only. The results of this study find that an acceptable surface quality (average roughness R_a<0.2 μm) and tool life (cutting length L>600 mm) can be obtained under the conditions of the given cutting parameters. It indicates that milling with PCD tools at a meso-scale is a suitable machining method for tungsten carbides.The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-020-00298-y     

Experimental investigations on cryogenic cooling by liquid nitrogen in the end milling of hardened steel

Milling of hardened steel generates excessive heat during the chip formation process, which increases the temperature of cutting tool and accelerates tool wear. Application of conventional cutting fluid in milling process may not effectively control the heat generation also it has inherent health and environmental problems. To minimize health hazard and environmental problems caused by using conventional cutting fluid, a cryogenic cooling set up is developed to cool tool–chip interface using liquid nitrogen (LN₂). This paper presents results on the effect of LN₂ as a coolant on machinability of hardened AISI H13 tool steel for varying cutting speed in the range of 75–125 m/min during end milling with PVD TiAlN coated carbide inserts at a constant feed rate. The results show that machining with LN₂ lowers cutting temperature, tool flank wear, surface roughness and cutting forces as compared with dry and wet machining. With LN₂ cooling, it has been found that the cutting temperature was reduced by 57–60% and 37–42%; the tool flank wear was reduced by 29–34% and 10–12%; the surface roughness was decreased by 33–40% and 25–29% compared to dry and wet machining. The cutting forces also decreased moderately compared to dry and wet machining. This can be attributed to the fact that LN₂ machining provides better cooling and lubrication through substantial reduction in the cutting zone temperature.     

Effects of Filler Concentration and Cutting Parameters on Material Properties and Machinability of SiC-Filled Epoxy Tooling Board

An experimental study was conducted to examine the material properties and machinability of a silicon carbide (SiC)-filled epoxy conductive tooling system (RP4037 CAST-IT^TM). Specifically, the effects of SiC filler concentration and machining process parameters (cutting speed and feed) on the physical and material properties, resultant cutting force, surface integrity, and tool wear were studied. Machinability evaluation was carried out using the end milling process. The study showed that an increase in filler concentration significantly increased the density, thermal conductivity, resultant machining forces, surface roughness of the machined surface, and tool wear. However, it had insignificant impact on the glass transition temperature, strength, or hardness. A decrease in material strength was observed with increasing cutting speed and feed. Increasing filler concentration was also found to degrade the machined surface morphology. Possible explanations for the observed effects are discussed.     

Single-point scratching of 6061 Al alloy reinforced by different ceramic particles

Aluminium alloys reinforced by ceramic particles have been widely used in aerospace and automotive industries for their high stiffness and wear resistance. However, the machining of such materials is difficult and would usually cause excessive tool wear. The effect of ceramic particles on the cutting mechanisms is also unclear. The purpose of this study is to investigate the cutting mechanisms and the relationship between specific energy of scratching and depth of cut (size effect). The single-point scratch test was carried out on 6061 Al and its composites reinforced by Al₂O₃ and SiC ceramic particles using a pyramid indenter. The results indicated that the scratch process was composed of rubbing, ploughing, plastic cutting and reinforcement fracture. A simple model was proposed to interpret the apparent size effect. The effect of reinforcement on the specific energy was correlated to the ratio of volume fraction to particle radius. The paper found that for machining MMCs, a larger depth of cut should be used to maintain a lower machining energy, especially for those with a larger ratio of volume fraction to particle radius.     

Parametric Optimization to Minimise the Surface Roughnesson the Machining of GFRP Composites

The present investigation focuses on the parametric influence of machining parameters on the surface finish obtained in turning of glass fiber reinforced polymer （GFRP） composites. The experiments were conducted based on Taguchi＇s experimental design technique. Response surface methodology and analysis of variance （ANOVA） were used to evaluate the composite machining process to perform the optimization. The results revealed that the feed rate was main influencing parameter on the surface roughness. The surface roughness increased with increasing the feed rate but decreased with increasing the cutting speed. Among the other parameters, depth of cut was more insensitive. The predicted values and measured values were fairly close to each other, which indicates that the developed model can be effectively used to predict the surface roughness on the machining of GFRP composites with 95% confidence intervals. Using such model could remarkablely save the time and cost.     

Design,evaluation and optimisation of cutter path strategies when high speed machining hardened mould and die materials

The use of high speed milling (HSM) for the production of moulds and dies is becoming more widespread. Critical aspects of the technology include cutting tools, machinability data, cutter path generation and technology. Much published information exists on cutting tools and related data (cutting speeds, feed rates, depths of cut, etc.). However, relatively little information has been published on the optimisation of cutter paths for this application. Most of the research work is mainly focused on cutter path generation with the main aim on reducing production time. Work with regards to cutter path evaluation and optimisation on tool wear, tool life, surface integrity and relevant workpiece machinability characteristics are scant. Therefore, a detailed knowledge on the evaluation of cutter path when high speed rough and finish milling is essential in order to improve productivity and surface quality. The paper details techniques used to reduce machining times and improve workpiece surface roughness/accuracy when HSM hardened mould and die materials. Optimisation routines are considered for the roughing and finishing of cavities. The effects of machining parameters notably feed rate adaptation techniques and cutting tools are presented.