Search

Manufacturing processes in industry applications are often controlled by the evaluation of surface topography. Topography, in its overall performance, includes form, waviness, and roughness. Methods of measurement of surface roughness can be roughly divided into tactile and contactless techniques. The latter ones are much faster but sensitive to external disturbances from the environment. One type of external source error, while the measurement of surface topography occurs, is a high-frequency noise. This noise originates from the vibration of the measuring system. In this study, the methods for reducing high-frequency errors from the results of contactless roughness measurements of turned surfaces were supported by machine learning methods. This research delves into optimizing filtration methods for surface topography measurements through the application of machine learning models, focusing on enhancing the accuracy of surface roughness assessments. By examining turned surfaces under specific machining conditions and employing a variety of digital filters, the study identifies the Gaussian regression filter and spline filter as the most effective methods at a 22.5 µm cut-off. Utilizing neural networks, support vector machines, and decision trees, the research demonstrates the superior performance of SVMs, achieving remarkable accuracy and sensitivity in predicting optimal filtration methods. [ABSTRACT FROM AUTHOR]

As copper is a rather difficult material to machine due to its ductility compared to aluminium, this study presents the approach of oxidizing the surface to improve the results of the grinding process. Therefore, batch manufactured flexible micro-grinding tools are used for grinding of copper and oxidized copper surfaces to machine microstructure or local areas of functional Abstract surfaces. Besides, we show a comparison of the performance of an abrasive layer made of silicon carbide (SiC) and cubic boron nitride (cBN). The tools are made of a polyimide-based abrasive layer and silicon as substrate and are fabricated by photolithography and deep reactive ion etching. The oxidation of copper surfaces is done by electrochemical processes and are directly machined with grinding tools. The surface quality is evaluated concerning the surface roughness by optical measurements with confocal microscopy. Lower roughness values are achieved on both, the pure copper and the oxidized copper by using SiC grinding tools. On pure copper this is reflected in a reduction of the arithmetical mean roughness value Ra to 0.04 µm. The unprocessed reference surface shows an Ra of 0.24 µm. In addition, the machined oxidized surfaces show a reduction of the mean roughness depth Rz from 7,60 µm to 1.10 µm, which is an optimization of factor 2 compared to the machined non-oxidized copper surfaces (2.32 µm). The machining of copper with cBN micro-grinding tools also shows improved roughness values, but in comparison to the SiC tools these are 50 % higher for machined copper surfaces and similar for machined oxidized copper surfaces. While the oxidation of the copper surface has a positive effect on the surface quality, no effect on tool wear can be observed. [ABSTRACT FROM AUTHOR]

In the paper, a three-dimensional (3D) micromechanical numerical cutting model with three phases was developed to study the surface integrity in cutting of Carbon fiber-reinforced polymer (CFRP) composites. The surface roughness and the depth of subsurface damage were predicted by using the numerical model, which were used to characterize the surface integrity. The machined surface observations and surface roughness measurements of CFRP composites at different fiber orientations were also performed for model validation. It is indicated that the 3D micromechanical cutting model is capable of precisely predicting the surface integrity of CFRP composites. To investigate the complex coupling influences of multiple machining parameters on the surface integrity, the factor analysis of multiple machining parameters was performed, and then the effects of these machining parameters on the surface roughness and subsurface damage depth were obtained quantitatively. It was found that the coupling effect of fiber orientation and cutting speed are the most significant factors to affect the surface roughness with the contribution rate of 4.8%, and the interaction between fiber orientation and edge radius has the most important effect on the subsurface damage depth with the rate of 5%. The results also reveal that coupling effects of cutting speed and rake angle should be considered for improving the surface integrity of CFRP composites. [ABSTRACT FROM AUTHOR]

This study examines surface roughness measurements via piezo acoustic disks and appropriate signal processing. Surface roughness is one characteristic of surface texture that can have various irregularities inherent to manufacturing methods. The surface roughness parameters and corresponding surface profiles are acquired by a stylus profilometer. Simultaneously, elastic waves propagated along metal surfaces caused by the friction of a diamond tip are obtained in the form of raw sound via piezo acoustic disks. Frequency spectrum analysis showed apparent correlations between the traditionally obtained measurement parameters and the piezo acoustic measurement data. Thus, it is concluded that acoustic friction measurement shows promising results as a novel measurement method for the surface roughness states of certain materials. [ABSTRACT FROM AUTHOR]

The article presents selected issues related to material quality manufactured by selective laser sintering of AlSi10Mg alloy powder after milling. The workpiece was prepared and machined by down-milling and up-milling with tools made of high-speed steel. Breaches, pores and failure-like cracks on the machined surface were found, which negatively influenced the values of 3D surface roughness parameters. The occurring phenomena were analyzed and proposals for their explanation were made. The results of this research describe the effect of cutting parameters (the feed rate of f = 0.013–0.05 mm/tooth) on the values of parameters describing the surface quality and benchmarks. Topography measurements and 3D surface roughness parameters are presented, as well as the results of microscopic surface analysis. It was found that for aluminum alloy produced by the direct metal laser sintering (DMLS) method, the recommended machining method is down-milling. [ABSTRACT FROM AUTHOR]

This empirical study was investigated to determine correlation between surface roughness and cutting parameters for turning and milling processes. The specimens were operated with the machining techniques as turning and milling. The 3D measurements of surface roughness were obtained with Nano-Focus confocal microscope. The variables were utilized Rz as dependent variable and cutting parameters as control factors; respectively, cutting speed, cutting depth, cutter radius and feeding. Multi-linear regression model was used for determination of relation between variable of roughness and cutting parameters. In terms of detection the magnitude and direction of relations, partial correlation was conducted on MATLAB 2021. Mathematical regression models were constituted for turning and milling processes separately. [ABSTRACT FROM AUTHOR]

The article deals with the surface roughness examination of three selected hard materials, that is, K100, 100CrMnMo7, and 16MnCr5, all with a defined hardness of HRC 60. The individual materials were machined using sintered carbide and cermet cutting materials with TiCN and TiN + TiCN + Al2O3 coatings. The research resided in the realization of three experiments. These experiments were carried out by three alternatives differing in the setting of basic cutting parameters. The experimental procedure was realized by the simulation method and direct contact measurement method of surface roughness. From the overall technical evaluation described in the practical part of the article, for the primarily observed parameter, the surface roughness, the least suitable values were obtained in the evaluation of the material from experiment No. 1-K100 with hardness HRC60. The experiments realized and the results achieved show that the machining of tool steels and other superhard materials requires special cutting tools, machines, and the use of progressive technologies, to ensure the production of a dimensionally and qualitatively shaped functional component. [ABSTRACT FROM AUTHOR]

Smart sensing of the surface roughness values is of great importance for intelligent manufacturing when online surface roughness measurements are essential in optimizing the machining processes. In this article, the magnetic flux leakage (MFL) method is applied to assess the roughness of triangle array surfaces, which may result from milling, turning, and planing. The leakage magnetic field (LMF) distribution is obtained by the magnetic dipole theory. The Fourier transform (FT) method is adopted to obtain the spatial spectrum functions of the LMF. Surface topography parameters are characterized from the first pulsed position and the correlation coefficient in the spatial spectrum domain. A magnetic recording head is designed for experimental verification. The results show that the relative errors of the surface roughness values are less than 13%. In addition, a portable probe used for roughness measurements is developed for a machining tool with an electromagnetic fixture. Fourier transform (FT), electromagnetic fixture, magnetic flux leakage (MFL), spatial spectrum, surface roughness. [ABSTRACT FROM AUTHOR]

High quality surfaces with transparency are required for manufacturing of plastic products. In cutting of polymer materials, surface quality is sometimes deteriorated by tarnish and/or unequal spaces of area on a surface. The cutting parameters should be determined through understanding of surface finish characteristics. This paper presents an optimization approach in milling of polycarbonate with polycrystal diamond tools in terms of the surface finish. Surfaces are finished with changing the feed rate and the clearance angle of the tool. The surface finishes, then, were observed to classify the deterioration type into welding, adhesion, and the unequal space of cutter marks with measurement of the surface profiles. The measured surface roughnesses are decomposed into the theoretical/geometrical term and the irregular term induced by the thermal and the dynamic effects. A map is presented to characterize the irregular term for the feed rates and the clearance angles. Because the surface roughnesses are measured at discrete sets of the cutting parameters in the actual cutting tests, the process design cannot be conducted to optimize the operation parameters. Therefore, a neural network is applied to associate the cutting parameters with the irregular term in the map. An approach is presented to determine the number of hidden nodes/units in the design of the neural network. Three prominent areas of welding, adhesion, and unequal spaces of the cutter marks, appear in the map of irregular roughness. The map of the surface roughness is made to optimize the cutting process. The applicable feed rates and clearance angles are determined for the tolerable surface roughnesses. The gradient information in the map is used to evaluate the stability/robustness of the surface quality for changing the parameters. The optimum parameters were determined to minimize the gradient information in the applicable feed rates and clearance angles. [ABSTRACT FROM AUTHOR]

Surface roughness assessment would help in predicting a component's functionality. This clearly shows the significance of measuring the surface roughness of machined components. Thus, each machined component, depending upon its intended function, requires a certain surface finish. To predict the surface roughness of a machined component, a detailed understanding of the machining parameters is essential. This is because, surface roughness generated on a component, depends upon machining parameters speed, feed, and depth of cut. A stable manufacturing process gives a consistent surface finish on all the manufactured components. Thus, only by having a stable process, consistent quality of manufactured products is possible. The capability of the machine is defined as the capability of the machine to carry out the set process efficiently and effectively to produce parts as per the specification limits. Machining parameters, tools, coolant flow rate, etc. An effort has been made in this research work, to show how by measuring surface roughness of machined components process capability can be assessed. Thus, the method is a novel technique of assessing the process capability of a given process. A capable process would help a manufacturing company in meeting customer expectations. The proposed method is of non-contact type, quick, and industry-friendly. [ABSTRACT FROM AUTHOR]

The aim of this study is to determine the optimal combination of process parameters when machining commercially pure titanium grade 2. The unification of Multi objective optimization based on ratio analysis (MOORA) and fuzzy approach has applied to optimize the process parameters. Three process parameters i.e. cutting speed, tool overhang, and microhardness have been varied at three levels each and a total of twenty seven experiments have been conducted based on Taguchi’s L27 design of experiment technique. Cutting force, tool flank wear, and average surface roughness have been considered a machinability indicators to measure the process performance. Feed rate and depth of cut have been kept constant. Successful optimization is done and results show that machining titanium at higher cutting speed (140 m/min) and higher tool overhang length (65 mm) with medium hardness (1934 HV) results in lower cutting force, tool flank wear, and surface roughness. Outcomes of the present work reveal that the hybrid fuzzy-MOORA method is convincing enough to obtain the best process parameter combination for the best machinability while machining titanium type difficult-to-machine materials. [ABSTRACT FROM AUTHOR]

A new hybrid cutting-abrasive machining tool (turn-grind) is detailed for high-quality machining of fibre reinforced polymer (FRP) composites, comprising single point carbide inserts electroplated with multi-layers of diamond abrasives 120 μm grain size, to form an abrasive region adjacent to an abrasive-free cutting edge. Experimental data are presented for turning tubes of CFRP and GFRP. The surface quality of workpieces after machining was evaluated through surface roughness measurements and SEM imaging. Cutting-only caused more defects such as delamination and fibre to pull out. Compared with cutting-only, contact and non-contact measurement of surface roughness (Ra) in both axial and radial directions showed an increase for CFRP and GFRP with roundness error reduced to 50%. No significant increase in cutting force was observed. [ABSTRACT FROM AUTHOR]

Machinery is one of the major fields that impact the growth of the country. Computer numerical control (CNC) plays a vital role in manufacturing machining parts. Each product manufactured from CNC has its performance index requirements based on its usage. The performance indexes, such as surface roughness and geometric tolerances, are important for any CNC machined product. The performance index values are affected by several controllable and uncontrollable parameters, among which the controllable parameters can be tuned to get the desired performance index values. Hence, in this article, we proposed an intelligent prediction model to predict the performance index values, such as surface roughness and geometric tolerances, considering the controllable machining parameters as the input for the model. The experimental results show that the performance index can be predicted effectively with various CNC machining parameters. Therefore, the model can be useful for the manufacturers for achieving the desired performance index values. [ABSTRACT FROM AUTHOR]

Through numerical calculations, it could be found that when the blade surface quality reaches a certain level, the surface quality of the blade was continuously improved, and the guarantee effect on its performance would be weakened. Under this circumstance, continuing to improve the surface quality of the blade had no positive effect on the performance of the blade. Studies had shown that when the blade surface equivalent grit roughness Ks reaches 4.96 (about R a = 0.8 µm), the blade performance was close to the smooth surface of the blade, and no further processing was required to improve the surface roughness. When the surface equivalent grit Ks was greater than 4.96 µm, the surface roughness had a great influence on the blade performance. When Ks was larger than 40 µm, the negative effect is significantly increased. For the different characteristics of the blade and different processing conditions, four kinds of robot-based blade surface grinding schemes were proposed, of which the core content was the robot layout. Based on the robot group's fitting to the spatial surface and the path planning, the experimental verification was carried out. [ABSTRACT FROM AUTHOR]

In this research, the effect of machining parameters on the various surface roughness characteristics (arithmetic average roughness (Ra), root mean square average roughness (Rq) and average maximum height of the profile (Rz)) in the milling of AISI 4140 steel were experimentally investigated. Depth of cut, feed rate, cutting speed and the number of insert were considered as control factors; Ra, Rz and Rq were considered as response factors. Experiments were designed considering Taguchi L9 orthogonal array. Multi signal-to-noise ratio was calculated for the response variables simultaneously. Analysis of variance was conducted to detect the significance of control factors on responses. Moreover, the percent contributions of the control factors on the surface roughness were obtained to be the number of insert (71.89 %), feed (19.74 %), cutting speed (5.08%) and depth of cut (3.29 %). Minimum surface roughness values for Ra, Rz and Rq were obtained at 325 m/min cutting speed, 0.08 mm/rev feed rate, 1 number of insert and 1 mm depth of cut by using multi-objective Taguchi technique. [ABSTRACT FROM AUTHOR]

Inconel 718 is a superalloy, considered one of the least machinable materials. Tools must withstand a high level of temperatures and pressures in a very localized area, the abrasiveness of the hard carbides contained in the Inconel 718 microstructure and the adhesion tendency during its machining. Mechanical properties along with the low thermal conductivity become an important issue for the tool wear. The finishing operations for Inconel 718 are usually performed after solution heat treatment and age hardening of the material to give the superalloy a higher level of hardness. Carbide tools, cutting fluid (at normal or high pressures) and low cutting speed are the main recommendations for finish turning of Inconel 718. However, dry machining is preferable to the use of cutting fluids, because of its lower environmental impact and cost. Previous research has concluded that the elimination of cutting fluid in these processes is feasible when using hard carbide tools. Recent development of new kPCBN (Polycrystalline Cubic Boron Nitride) grades for cutting tools with higher tenacity has allowed the application of these tool grades in the finishing operations of Inconel 718. This work studies the performance of commercial PCBN tools from four different tool manufacturers as well as an additional grade with equivalent performance during finish turning of Inconel 718 under dry conditions. Wear tests were carried out with different cutting conditions, determining the evolution of machining forces, surface roughness and tool wear. It is concluded that it is not industrially viable the high-speed finishing of Inconel 718 in a dry environment. [ABSTRACT FROM AUTHOR]

The effect of electric discharge machining (EDM) on surface quality and consequently on the fatigue performance of Al 2024 T6 is investigated. Five levels of discharge current are analyzed, while all other electrical and nonelectrical parameters are kept constant. At each discharge current level, dog-bone specimens are machined by generating a peripheral notch at the center. The fatigue tests are performed on four-point rotating bending machine at room temperature. For comparison purposes, fatigue tests are also performed on the conventionally machined specimens. Linearized SN curves for 95% failure probability and with four different confidence levels (75, 90, 95 and 99%) are plotted for each discharge current level as well as for conventionally machined specimens. These plots show that the electric discharge machined (EDMed) specimens give inferior fatigue behavior as compared to conventionally machined specimen. Moreover, discharge current inversely affects the fatigue life, and this influence is highly pronounced at lower stresses. The EDMed surfaces are characterized by surface properties that could be responsible for change in fatigue life such as surface morphology, surface roughness, white layer thickness, microhardness and residual stresses. It is found that all these surface properties are affected by changing discharge current level. However, change in fatigue life by discharge current could not be associated independently to any single surface property. [ABSTRACT FROM AUTHOR]

All engineering materials can be machined by one or combination of processes in such a way that the material's potential is fully exploited. Electrochemical machining is found to be a most promising process that produces various components from the hard-to-machine materials for the various applications. Electrolyte concentration is playing a positive role by improving the electrolyte conductivity, but negatively forming the passivation layer on the cut surfaces. In order to improve the surface finish and removal of generated residual materials from the cut surfaces, abrasive particles were fed along with electrolyte into the machining zone. This present paper investigates the sodium chloride (NaCl) electrolyte with varied concentration (10-30%) in association with SiC abrasive particles on the material removal rate, surface roughness, and radial overcut while machining of aluminum 6061-boron carbide (5-15 wt%) composites. This study conclusively derived that electrolyte concentration up to 20% exhibited a positive role in the material removal rate for the machining of composites because the rate of dissolution was of higher magnitude. Externally supplied abrasive particles along with electrolyte reduced the surface roughness and radial over cut to an extent. Conversely, at higher electrolyte concentration, the externally supplied abrasive particles have a little effect on the removal of the formed passivation layer as confirmed by SEM analysis. [ABSTRACT FROM AUTHOR]

The present study focuses on the development of predictive models of average surface roughness, chip-tool interface temperature, chip reduction coefficient, and average tool flank wear in turning of Ti-6Al-4V alloy. The cutting speed, feed rate, cutting conditions (dry and high-pressure coolant), and turning forces (cutting force and feed force) were the input variables in modeling the first three quality parameters, while in modeling tool wear, the machining time was the only variable. Notably, the machining environment influences the machining performance; yet, very few models exist wherein this variable was considered as input. Herein, soft computing-based modeling techniques such as artificial neural network (ANN) and support vector machines (SVM) were explored for roughness, temperature, and chip coefficient. The prediction capability of the formulated models was compared based on the lowest mean absolute percentage error. For surface roughness and cutting temperature, the ANN and, for chip reduction coefficient, the SVM revealed the lowest error, hence recommended. In addition, empirical models were constructed by using the experimental data of tool wear. The adequacy and good fit of tool wear models were justified by a coefficient of determination value greater than 0.99. [ABSTRACT FROM AUTHOR]

Precision and micro rotational parts are widely used in various industries, such as micro probes for medical instruments, contact pins for micro assembly applications, micro electrodes for micro Electrical discharge machining (μ-EDM) or micro Electro-chemical discharge machining (μ-ECDM). In this research, a uniform annular area layer by layer feeding strategy was proposed to fabricate high aspect ratio, small radii rotational components on a conventional Wire electrical discharge machining (WEDM) machine equipped with an auxiliary spindle. The uniform annular area layer by layer feeding strategy consisted of the roughing and finishing stages. First, the theoretical Material removal rate (MRR) and radial infeed rate for each layer were determined for the roughing stage, and the theoretical surface roughness, Rz in the finishing stage was researched. Then, a series of optimization experiments were conducted to investigate the influence of the parameters on MRR and the machined surface roughness. A group of pin electrodes were machined by applying this feed strategy with the optimized parameters, and the minimum diameter of the pin electrodes was 40 μm with an aspect-ratio of 60. Finally, micro electrodes for an injection nozzle were achieved with this novel process and a qualified injection nozzle for powder metallurgy was fabricated with the machined micro electrodes. [ABSTRACT FROM AUTHOR]

The aim of this study was to obtain targeted surface roughness values in drilling by determining drilling parameters using Artificial Neural Networks (ANN). In realizing this, two Artificial Neural Network (ANN) models were developed for the drilling process. The first model is employed for predicting the surface roughness of holes, depending on the drilling parameters (spindle speed and feed rate). The second model is involved with the experimental data and used to determine the drilling parameters to obtain targeted surface roughness. The drilling experiments were performed by changing the spindle speed and feed rate, while the other parameters were kept constant. While the surface roughness of drilled holes was predicted successfully by the first ANN Model, the optimal drilling parameters to obtain targeted surface roughness were determined by the second model. By this approach, enhanced surface roughness (Ra) values reaching up to the 0.17 μm were obtained during the drilling of AISI 2080 steel. [ABSTRACT FROM AUTHOR]

Circular saw blades are fundamental and necessary cutting tools used for sawing, slicing, and related machining processes. In this paper, an innovative and economical design of a circular saw blade with self-clamped cutting inserts used for general purpose steel cutting is presented. The designed circular saw blade consists of a plurality of cutting inserts assembled to a circular saw plate through an elastic deformation-based self-clamping mechanism. Prototypes of the designed circular saw blade were actually fabricated. Slicing tests of workpieces made of JIS S45C carbon steel and JIS SCM440 alloy steel were conducted, and the induced cutting forces and surface roughness were also measured and then evaluated through established response surface models. The resultant cutting forces obtained from all slicing tests were less than 560 N, which indicates that a moderate level of cutting forces would be induced. The values of arithmetical mean roughness obtained from all slicing tests significantly ranged from 1 to 4 μm, which indicates that well surface quality of the machined surface could be achieved. Therefore, the presented circular saw blade was feasible for applications of general purpose steel cutting. [ABSTRACT FROM AUTHOR]

This paper investigates the effect of cutting parameters (cutting speed, feed rate and approach angle) on roughness in turning of Al 7075 hard ceramic composite (10 wt.% SiC) and Al 7075 hybrid composite (7 wt.% SiC and 3 wt.% graphite) using polycrystalline diamond tool (PCD). The dry turning is conducted to examine the trend of roughness by using a SJ301 MITUTOYO roughness tester for both composites at cutting speed (80–170 m/min), feed rate (0.05–0.2 mm/rev) and approach angle (45–90°). It is inferred that surface roughness of the hybrid composite (7 wt.% SiC and 3 wt.% graphite) is lower than that of the hard ceramic composite (10 wt.% SiC) in all combinations of experiments. To recognize the mixing of reinforcement is examined using scanning electron microscope (SEM) and X-ray diffraction (XRD). Response surface methodology (RSM) and artificial neural networking (ANN) are applied to validate the results obtained during experimentation and to predict the behavior of the system under any condition within the operating range. It is apparent from the analysis that feed rate has significant contribution for both materials than speed and approach angle. [ABSTRACT FROM AUTHOR]

The article focuses on monitoring the machined surface after it has been machined with different milling strategies. Different milling strategies refer to milling whilst changing the tool axis relative to the surface after finishing the free form milling. The research focuses mainly on the geometric characteristics of the finished surface profile and residual stresses in the surface layer. The goal of the experimental work is to find an effective position of the tool axis, or an effective interval of the tool axis, in relation to the machined surface normal. Practical applications of the results are focused on finishing milling of complicated shape surfaces especially in the production of moulds and dies for the automotive and aerospace industries. The technology is based on the substitution of three-axis milling for multi-axis milling, i.e. mainly 5-axis simultaneous milling. [ABSTRACT FROM AUTHOR]

AISI4340 hardened steel has vast functionality in industries. Hard machining of this steel has several benefits such as, higher productivity, lower production cost and improved workpiece properties. In machining operation, ultimate surface roughness is the most important characteristic of machined surface and plays an important role in workpiece life. One of the effective factors on surface integrity is cutting fluid used in machining operation which, in spite of its positive effects has health and environmental problems. As a result, using minimum quantity lubrication is considered as an alternative method. In the present study, relations between milling parameters and final surface quality in milling of AISI4340 hardened steel, in the presence of lubrication systems including; dry, wet and minimum quantity lubrication have been investigated. Cutting speed, feed rate, axial and radial depth of cut have been considered as main parameters of milling operation. Totally, 90 experiments have been done using response surface method to analyze the effects of process parameters on surface roughness. Results revealed that feed rate and cutting speed have the most influence on surface roughness. Also, higher values of cutting speed and lower values of feed rate are necessary to reduce surface roughness. In addition, compared to other lubrication methods, minimum quantity lubrication has the best performance in surface quality, especially in high cutting speed and depth of cut. [ABSTRACT FROM AUTHOR]

This paper focuses on the mechanical behavior in quasi-static tests (compression and inter-laminar shear) of two composite materials machined by different processes. First, the impact of the variation of average surface roughness (Ra) and the machining process is studied for both materials and for each stress. The results of compression and inter laminar shear tests show that the mechanical behavior is greatly affected by the surface roughness and the machining temperatures. Secondly the effect of machining processes is detailed. The experimental results show the major dependence of the mechanical behavior on the machining process. The results obtained on the two materials being different, this work sheds light on the influence of the composition of composite materials on the surface defects and the mechanical behavior of such materials. [ABSTRACT FROM AUTHOR]

In order to explore the effect of process parameters on surface roughness in high-speed milling, the multifactorial orthogonal experiments of die steel S50C are conducted, and the surface roughness is measured under different parameters such as spindle speed, feed rate, axial depth, radial width and pose angle. The artificial neural network and genetic algorithm are used to establish a prediction model of surface roughness and an optimization model of process parameters. In addition, the validity of two models is verified. Results show that the approach may be used for the prediction of surface roughness and optimization of the process parameters before machining. Moreover, this research also provides a valid means to study the process parameters of other materials. [ABSTRACT FROM AUTHOR]

This paper presents the state of surface integrity produced on hardened-high strength 41Cr4 steel after hard machining and finish ball burnishing. Surfaces machined by sequential machining processes were characterized using 2D and 3D surface roughness parameters. Moreover, detailed functionality of the generated surfaces was performed using a set of 3D functional roughness parameters. Among the characteristics of the surface layer, its microstructure, the distribution of microhardness and the residual stresses were determined. This investigation confirms that ball burnishing allows producing surfaces with lower surface roughness and better service properties than those generated by cubic boron nitride (CBN) finish hard turning operations. [ABSTRACT FROM AUTHOR]

It is difficult to have high accuracy and low surface roughness in processing of metal matrix composites (MMCs). Micro-wire electrical discharge machining (micro-WEDM) has no obvious cutting force in processing because there is no direct action between tool electrode and workpiece, which makes micro-WEDM complete the machining of MMCs with high hardness and high strength. However, the recast layer can be formed with damages on machining surface in micro-WEDM process. Therefore, to resolve these problems, this paper highlights analysis of the surface characteristics of SiC/Al particulate MMC in micro-WEDM process. In addition, the characteristics of recast layer with different discharge energy are analyzed. And the removal process of ceramic particles in the composite is thermal spalling process, which is proved using surface morphology of SiCp/Al MMC by micro-WEDM. Finally, to reduce the thickness of recast layer and improve surface integrity of SiCp/Al2024 MMC by micro-WEDM, a multicutting experimental is performed and the machined surface with 0.774 µm in surface roughness and 3 µm in recast layer thickness are obtained. [ABSTRACT FROM PUBLISHER]

In this study, turning of super alloy Monel K500 has been investigated with ceramic tools and with the help of ordinary and Wiper inserts under dry and near dry machining. First, preparation of process on lathe and a mechanism to provide near dry lubrication was done. The used tools are ordinary ceramic inserts from type of DNGA 12 04 08 T01020-650 and Wiper inserts from type of DNGA 12 04 08 T01020WG-650 manufactured by Sandvik company. During the experiments, parameters such as cutting force, surface roughness, and cutting region temperature were evaluated. All of the mentioned parameters were measured in both dry and near dry lubrication. The obtained results prove that under near dry machining not only surface roughness enhances, but also cutting force and temperature decrease. [ABSTRACT FROM PUBLISHER]

Highlights: [•] Increasing the number of flutes (cutting edges) improved the surface quality. [•] The recommended tool had 4 flute and the estimated surface roughness was 1.6586μm. [•] Minimum surface roughness was 1.626μm with a 4 flute end mill. [•] Optimal cutting parameters were obtained 113m/min, 0.04mm/rev, and 3mm. [ABSTRACT FROM AUTHOR]

Elman Networks is a one of the dynamic recurrent neural networks. In this research it is used for the prediction of surface roughness in Electrical Discharge Machining (EDM). Training of the models was performed with data from series of EDM experiments on SKD 11 (AISI D2) Tool steel; in the development of predictive models, machining parameters of discharge current, pulse duration and duty cycle were considered as model variables with a constant voltage 50 volt. For this reason, extensive experiments were carried out in order to collect surface roughness dataset. The developed model is validated with a new set of experimental data, and predictive behavior of models is analyzed. The reported results indicate that the proposed model can satisfactorily predict the surface roughness in EDM. And can be considered as valuable tools for the process planning for EDMachining. [ABSTRACT FROM AUTHOR]

This study investigated the microstructure and machining characteristics of a Zr38.5Ti16.5Cu15.25Ni9.75Be20 bulk metallic glass (Zr-BMG) alloy machined using electro-discharge machining (EDM). After EDM, the hardening effect near the outer surface of the electro-discharge machined (EDMed) Zr-BMG alloy originated from the surface carbides of the recast layer, ZrC and TiC. The thickness of the recast layer, crater size, and the surface roughness increased with greater pulse energy. Furthermore, the EDM can generate a porous recast layer and convert the Zr-BMG alloy surface into a carbide surface, which is a potential method to fabricate biomaterials. Experimental results also show that the material removal rate of this alloy in the EDM process was significantly related to the pulse current IP and pulse duration τP. Many electro-discharge craters and recast materials were observed on the surface of the EDMed Zr-BMG alloy. The surface roughness of the EDMed Zr-BMG alloy was found to obey the empirical equation of Ra = β(IP × τP)α. [ABSTRACT FROM PUBLISHER]

In this study, the machining characteristics of AISI 202 stainless steel have been investigated in thermal erosion process. Taguchi method based experiments have been conducted with conventional and modified pulse generators using electric discharge machining. Material removal rate (MRR) and surface roughness were taken to evaluate performance of process. Gap voltage, discharge current, and duty factor have been chosen as input parameters to access the machinability. The efficacy of pulse generators in thermal erosion process is determined by high material removing property and better surface finish. Since this machining process has stochastic nature, conventional RC relaxation pulse generator and transistor pulse train generator could not satisfy both the two requirements. It is proved that modified ISO current pulse generator could produce better surface finish with high MRR than conventional pulse generators in thermal erosion process. [ABSTRACT FROM PUBLISHER]

The machining response of metallurgically and mechanically modified materials when processed by employing the microwire electrical discharge machining (μWEDM) technology is reported in this paper. In particular, the effects of the material microstructure on resulting surface integrity of Al5000 series aluminium alloys after μWEDM processing is studied. The machining response of an ‘as received’ aluminium alloy was compared against the results obtained on samples processed through extrusion strain hardening and severe plastic deformation. Especially, the process–material effects on the resulting microhardness, phase content changes, heat-affected zone, surface roughness, microcracks, recast layer, material removal rate, and element spectrum after both rough and finishing μWEDM cuts were investigated. This study shows that an ultrafine grained (UFG) Al5083 exhibits not only superior mechanical properties but also the machining response to μWEDM is favourable. A reduction of the recast layer after μWEDM was observed when compared with ‘as received’ and ‘conventionally’ processed Al5083. [ABSTRACT FROM PUBLISHER]

Abstract: Surface roughness of the workpiece is an important parameter in machining technology. Wiper inserts have emerged as a significantly class of cutting tools, which are increasingly being utilized in last years. This study considers the influence of the wiper inserts when compared with conventional inserts on the surface roughness obtained in turning. Experimental studies were carried out for the carbon steel AISI 1045 because of its great application in manufacturing industry. Surface roughness is represented by different amplitude parameters (R a, R zD, R 3z, R q, R t, R a/R q, R q/R t, R a/R t). With wiper inserts and high feed rate it is possible to obtain machined surfaces with R a <0.8μm (micron). Consequently it is possible to get surface quality in workpiece of mechanics precision without cylindrical grinding operations. [Copyright &y& Elsevier]

This paper presents the formulation and solution of optimization of various process parameters for the selection of the best control settings on a microwire electrical discharge machining process. A factorial design model is used to predict the measures of performance as a function of various control settings. Analysis of variance is used to indicate the significant factors. Regression models relating the machining performance are established. The performance measures taken for the model are material removal rate (MRR), overcut, and surface roughness. At discharge energy of 2,645 μJ, maximum MRR of 0.0428 mm/min and an overcut value of 69 μm are observed. With the value of discharge energy changing from 32 to 4,500 μJ, the Ra value of slot surface varied from 1.17 to 4.25 μm. The analysis gave the average erosion efficiency around of 27%, which showed high sensitivity to the selected discharge energy levels. [ABSTRACT FROM AUTHOR]

In rough machining of parts with sculptured surfaces, two main objectives are usually considered: machining time and overall removed material at the end of the roughing phase. The outcome of that phase is critical for the subsequent finishing phase. This paper proposes a method for measuring roughed part quality through calculation of the local difference between the roughed part geometry and the ideally finished part geometry. The method calculates the height from a point lying on the roughed surface to its projection on the ideally finished part surface. Using the API of a CAD system for this purpose proves computationally inefficient. Therefore, a mean distance between a triangle of the roughed surface triangular mesh and the ideally finished part surface region lying in a suitable envelope is calculated instead. The calculation is repeated not for all triangles of the mesh, but for a sample as low as 3%, which, according to the Levene statistical test suffices, thereby, reducing computational cost by orders of magnitude. The method ultimately yields a single figure, i.e. the standard deviation of local differences between the roughed and finished part, normalized by the mean difference. The concept was tested on sculptured surface parts of various mechanical and operational properties and was proven efficient in all test cases. [ABSTRACT FROM AUTHOR]

In this paper an attempt has been made to find optimal process parameters of abrasive mixed electrical discharge machining (AEDM). Taguchi methodology has been adopted for planning and analysing the experiments for optimising the multiple performance characteristics. The process input parameters, viz, concentration of silicon in dielectric fluid, current, pulse-on time, duty factor were chosen to study process performance in terms of material removal rate (MRR) and surface roughness (SR). The investigations result show that with addition of silicon abrasive powder (2 g 1-1) in kerosene dielectric fluid, material removal rate improves by 23% and surface roughness is reduced by 35 %. The optimum process conditions as suggested by the present study are verified by conducting confirmation experiments. [ABSTRACT FROM AUTHOR]

Milling is one of the common machining methods that cannot be abandoned especially for machining of metallic materials. The cutters with appropriate cutting parameters remove material from the workpiece. Surface roughness has the major influence on both obtaining dimensional accuracy and quality of the product. A number of cutter path strategies are employed to obtain the required surface quality. Zigzag machining is one of the mostly appealing cutting processes. Modeling of surface roughness with traditional methods often results in inadequate solutions and can be very costly in terms of the efforts and the time spent. In this research Genetic Programming (GP) has employed to predict a surface roughness model based on the experimental data. The model has produced an accuracy of 86.43%. In order to compare GP performance, Artificial Neural Network (ANN) and Adaptive Neuro Fuzzy Inference System (ANFIS) techniques were utilized. It was seen that the surface roughness model produced by GP not only outperforms but also enables to produce more explicit models than of the other techniques. The effective parameters can easily be investigated based on the appearances in the model and they can be used in prediction of surface roughness in zigzag machining process. [ABSTRACT FROM AUTHOR]

The literature reports many scientific works on the use of artificial intelligence techniques such as neural networks or fuzzy logic to predict surface roughness. This article aims at introducing Bayesian network-based classifiers to predict surface roughness (Ra) in high-speed machining. These models are appropriate as prediction techniques because the non-linearity of the machining process demands robust and reliable algorithms to deal with all the invisible trends present when a work piece is machining. The experimental test obtained from a high-speed milling contouring process analysed the indicator of goodness using the Naive Bayes and the Tree-Augmented Network algorithms. Up to 81.2% accuracy was achieved in the Ra classification results. Therefore, we envisage that Bayesian network-based classifiers may become a powerful and flexible tool in high-speed machining. [ABSTRACT FROM AUTHOR]

Principal features of aluminium matrix composites are put forward. Emphasis is put on temperatures of melting and coefficients of heat conduction of matrix and reinforcement. The paper presents results of electrical discharge machining of aluminium matrix composites with particular attention given to thickness of the defected layer after machining. Influence of various machining parameters on the behaviour of saffil fibres and matrix material in the affected zone is presented. Scanning micrographs and roughness measurements are used to analyse surface finish following machining. The influence of used current parameters on the quality of surface layer after electrical discharge machining is discussed. The results for composite materials are compared with those for aluminum alloys. [ABSTRACT FROM AUTHOR]

The use of response surface methodology for minimizing the surface roughness in machining titanium alloy, a topic of current interest, has been discussed in this article. The surface roughness model has been developed in terms of cutting parameters such as cutting speed, feed, and depth of cut. Machining tests have been carried out using CVD (TiN-TiCN-Al2O3-TiN) coated carbide insert under different cutting conditions using Taguchi's orthogonal array. The experimental results have been investigated using analysis of variance (ANOVA). The results indicated that the feed rate is the main influencing factor on surface roughness. Surface roughness increased with increasing feed rate, but decreased with increasing cutting speed and depth of cut. The predicted results are fairly close to experimental values and hence, the developed models can be used for prediction satisfactorily. [ABSTRACT FROM AUTHOR]

In the hard-turning process, tool geometry and cutting conditions determine the time and cost of production which ultimately affect the quality of the final product. So reliable models and methods are required for the prediction of the output performance of the process. In the present work, experimental investigation has been conducted to see the effect of the tool geometry (effective rake angle and nose radius) and cutting conditions (cutting speed and feed) on the surface finish during the hard turning of the bearing steel. First- and second-order mathematical models were developed in terms of machining parameters by using the response surface methodology on the basis of the experimental results. The surface roughness prediction model has been optimized to obtain the surface roughness values by using genetic algorithms. The genetic algorithm program gives minimum values of surface roughness and their respective optimal conditions. [ABSTRACT FROM AUTHOR]

In this experimental study, three SiC/Al metal matrix composites (MMCs) with SiC particles of 30, 45 and 110μm in mean sizes were produced using a melt stirring-squeeze casting route. Machining tests were carried out on the MMCs using cubic boron nitride (CBN) cutting tools at various cutting speeds under a constant feed rate and depth of cut. The effect of reinforcement particulate sizes and cutting speeds on tool wear was investigated. Furthermore, surface roughness measurements were also carried out on the machined surfaces. The results showed that tool wear was mainly dominated by flank wear and strongly influenced by reinforcement particulate size. The MMC containing SiC particles of 110μm proved to be unsuitable for the machining operation using CBN cutting tools due to the heavy fracture of the cutting edge and nose. In the composites reinforced with SiC particles of 30 and 45μm, 150m/min cutting speeds led to the lowest tool flank wear values while 100 and 200m/min cutting speeds resulted in higher tool flank wear values. [Copyright &y& Elsevier]

To understand the effect of surface machining on the resistance of to SCC (stress–corrosion cracking) in marine environments, we tested nuts surface-machined by different methods in a seawater-spraying chamber. Two forms of cracks were observed: on the machined surface and underneath it. On the surface, cracks connected with the pitting sites were observed to propagate perpendicular to the hoop-stress direction, identifying them as stress–corrosion cracks. Under the surface, catastrophic transgranular cracks developed, likely driven by hydrogen embrittlement caused by the chloride-concentrating level of humidity in the testing environment. Under constant testing conditions, significantly different SCC resistance was observed depending on how the nuts had been machined. Statistical evaluation of the nut surface-crack density indicates that machining by a "form" tool yields a crack density one order of magnitude lower than machining by a "single-point" tool. Microstructural analysis of form-tool-machined nuts revealed a homogeneous deformed subsurface zone with nanosized grains, leading to enhanced surface hardness. Apparently, the reduced grain size and/or the associated mechanical hardening improve resistance to SCC. The nanograin subsurface zone was not observed on nuts machined by a single-point tool. Surface roughness measurements indicate that single-point-tool-machined nuts have a rougher surface than form-tool machined nuts. Apparently, surface roughness reduces SCC resistance by increasing the susceptibility to etch attack in Cl--rich solutions. The results of X-ray diffractometry and transmission electron microscopy diffractometry indicate that machining with either tool generates a small volume fraction (< 0.01) of strain-induced martensite. However, considering the small volume fraction and absence of martensite in regions of cracking, martensite is not primarily responsible for SCC in marine environments. [ABSTRACT FROM AUTHOR]

To meet the requirements for high-performance products, the aerospace industry increasingly needs to assess the behavior of new and advanced materials during manufacturing processes and to ensure they possess adequate machinability, as well as high performance and an extensive lifecycles. Over the years, industrial research works have focused on developing new alloys with an increased thermal conductivity as well as increased strength. High silicon content aluminum (Al–Si) alloys, due to their increased thermal conductivity, low coefficient of thermal expansion, and low density, have been identified as suitable materials for space applications. Some of these applications require the use of intricate parts with tight tolerances and surface integrity. These challenges are often tied to the machining conditions and strategies, as well as to workpiece materials. In this study, experimental milling tests were performed on a rapidly solidified (RS) Al–Si alloy with a prominent silicon content (over 50%) to address challenges linked to material expansion in deep space applications. The tests were performed using a polycrystalline cubic boron nitride (PCBN) tool coated with amorphous diamond to reduce tool wear, material adhesion, surface oxidation, and particle diffusion. The effects of cutting parameters on part surface roughness and microstructure were analyzed. A comparative analysis of the surface with a conventionally utilized Al6061-T6 alloy showed an improvement in surface roughness measurements when using the RS Al–Si alloy. The results indicated that lower cutting speed and feed rate on both conventional and RS Al–Si alloys produced a better surface finish. Reduced vibrations were also identified in the RS Al–Si alloy, which possessed a stable cutting time at low cutting speeds but only displayed notable vibrations at cutting speeds above 120 m/min. [ABSTRACT FROM AUTHOR]