Metal Removal Operations Research Articles

Experimental and image processing-based characterization of sustainable bio-coolant for metal removal operations

Experimental and image processing-based characterization of sustainable bio-coolant for metal removal operations

Prediction of significant oil properties using image processing based on RGB pixel intensity

Renewable oils from different feedstocks are considered a potential replacement for the current petroleum products, and they are widely used in various applications like alternative fuels to heat engines and bio-coolants for metal removal operations, and their analysis of significant physicochemical properties is significant before their application. This study attempts to analyze the significant oil properties of different edible and non-edible oils using an image processing technique. For this purpose, 11 different oils are considered for experimentation, and their surface images of all the oils are captured and utilized to extract significant pixel information of Red, Green and Blue (RGB). The RGB pixel information is correlated with experimental properties (viscosity, density, flash point, fire point, cloud and pour points) and the developed model is validated with KNN, SVM and Fiji techniques and observed a high prediction accuracy (99%, 90.9% and 99%). Finally, two different oils which are not used in the experiment are chosen to test the prediction accuracy of the developed model. The results show that the RGB pixel predicts the significant oil properties, and they are validated experimentally and observed that the developed model predicts the oil properties with 91.7% accuracy.

Optimization of Surface Roughness and Material Removal Rate in Turning of AISI D3 Steel with Coated Carbide Inserts

The aim of this paper is to optimize the metal removal rate and surface roughness through turning on AISI D3 Steel with coated carbide inserts. As per the current market scenario, for the metal cutting industries the most important challenge in the turning process is to satisfy both requirements quality as well as high productivity in less time in order to remain competitive. Among all the different cutting processes, the turning process is one of the most applied and fundamental metal removal operations in the real manufacturing environment. This work examines the impact of machining factors like speed, depth of cut & feed on roughness and MRR of AISI D3 steel which have a hardness value of 60 HRC with coated carbide inserts. At high speed and feed rate optimum MRR was achieved and opposite to that at low feed and depth of cut optimum surface roughness was obtained. Taguchi L9 (3)3 OA has been applied for experimental design. ANOVA analysis is performed just after DOE to identify the significant factor which influences MRR and surface roughness. Among the three machining factors, depth of cut and speed has more influencing effect on roughness and the feed influences MRR. Effort was made to find optimum solution to minimize the roughness and maximize the MRR by Taguchi and ANOVA technique.

Optimization of Dimensional Tolerances and Material Removal Rate in the Orthogonal Turning of AISI 4340 Steel

Turning is one of the most used metal removal operations in the industry. It can remove material faster, giving reasonably good surface quality apart from geometrical requirements. Conformity of geometry is one of the most significant requirements of turned components to perform their intended functions. Apart from dimensional requirements, the important geometrical necessities are Circularity, Straightness, Cylindricity, Perpendicularity, etc. Since they have a direct influence on the functioning of the components, the effect of the cutting parameters on them has greater significance. In this paper experiments are carried out to examine the effect of turning parameters such as cutting speed, feed rate, and depth of cut on responses like; straightness, roundness, surface roughness, and material removal rate during turning of AISI 4340 steel. Analysis of Variance (ANOVA) is performed and the influence of parameters on each response is studied. The optimal values of parameters obtained from the study are further confirmed by conducting experiments.

Thermal modelling of cutting tool temperatures and heat partition in orthogonal machining of high-strength alloy steel

Cutting temperatures and heat partition into the cutting tool are critical factors that significantly affect tool life and part accuracy during metal removal operations, especially in dry machining. Among many thermal modelling studies, uniform heat partition ratio, and/or uniform heat intensity along the tool-chip interface are frequently assumed. This assumption is not valid in actual machining and can lead to erroneous estimated results in the presence of sticking and sliding friction zones. Therefore, it is necessary to accurately predict the cutting tool temperature and heat partition during machining. This paper presents an analytical thermal modelling approach which considers the combined effect of the primary and the secondary heat sources and determines the temperature rise and non-uniform heat partition ratio along the tool-chip interface. Cutting tests were conducted on AISI/SAE 4140 high-strength alloy steel using carbide cutting tools over a wide range of cutting speeds. Cutting temperatures were measured experimentally using an infrared thermal imaging camera. Experimentally established sticking and sliding friction regions were used to evaluate non-uniform frictional heat intensity along the tool-chip interface. The temperature matching condition along the tool-chip interface leads to the solution of distributed non-uniform heat partition ratio by solving a set of linear equations through programming in MATLAB®. Experimental results show to be consistent well with those obtained from the thermal model, yielding a relative difference of predicted average tool-chip interface temperature from −0.8% to 6.3%. It is found that average heat partition into the cutting tool ( RT) varies from 35% down to 15% for the entire range of cutting speeds. These results suggest that, to address the thermal problem in metal cutting, the research and development of tooling should also focus on reducing friction on the tool rake face in addition to the contribution of the combined effect of primary and secondary heat sources on temperature rise at the tool-chip interface.

Determining the Binding Capacities of Cr (VI) and Zn (II) Ions of Oscillatoria sp.

This study aimed to determine the removal capacity for Cr (VI) and Zn (II) ions from high concentration of aqueous solutions by using Oscillatoria microalgae. In the biosorption process, live and dead Oscillatoria cells were exposed for 24 hours to Cr and Zn metals of different concentrations (2.5, 5 and 10 mg/L). In addition, chlorophyll-a analysis have been made to examine the effects on cell metabolism of chromium and zinc metals. The best metal removal percentages was obtained; of chromium ion is 46.74% with dead cells and for zinc ion 82.53% with living cells. Chlorophyll-a analysis shows that when the metals separately applied on Oscillatoria cells, chlorophyll-a content of organism increase but when metals together applied decrease of chlorophyll-a content was observed. For this study, Freundlich model best fitted the data for two metal ions with 1/n value <1. This study revealed that Oscillatoria cells were an effective adsorbent for removal of the two heavy metals, especially Zn ions from aqueous solutions due to its high efficiency of Zn adsorption. It shows that it is a kind of potential for this heavy metal removal operations.

Development of a new model for determine of cutting parameters in metal drilling processes

Metal drilling and cutting processes are used commonly in many areas of the industry. When these processes investigated analytically, it is seen that they have a very complicated structure. This complicated structure can find easy solutions with finite element-based simulation tools. In metal removal operations, it is very difficult to calculate the cutting parameters such as cutting tool stresses, residual stresses, cutting tool–chip interface temperature and shear angle both experimentally and analytically. But, these operations could be easily calculated by computer-supported simulation tools. In these types of numeric simulations, using finite element method, it is needed to identify clearly the friction, material model load and limiting conditions. In this paper, the cutting parameters as cutting and thrust power, heat transfer coefficient and friction coefficient at chip–tool interface which is needed to find the temperature distribution on drilling bit and workpiece material were calculated using analytic models.

Spheroidize Annealing and Mechanical Property Evaluation of AISI 1040 Steel

The importance of medium carbon steels as engineering materials is reflected by the fact that out of the vast majority of engineering grade ferrous alloys available and used in the market today, a large proportion of them are from the family of medium carbon steels. Typically medium carbon steels have a carbon range of 0.25 to 0.65% by weight, and a manganese content ranging from 0.060 to 1.65% by weight. Medium carbon steels are more resistive to cutting, welding and forming as compared to low carbon steels. From the last two decades a number of research scholars reported the use of veritiy of heat treatments to tailor the properties of medium carbon steels. Spheroidising is the novel industrial heat treatment employed to improve formability and machinability of medium/high carbon low alloy steels. This exclusive study covers procedure, the effects and possible outcomes of various heat treatments on medium carbon steels. The austenite phase present in steel above the critical temperature has the tendency to form variety of non equilibrium phases depending upon the degree of supercooling or cooling rates. The near spherical or curved shaped carbides records least resistance for machining because the blunt cornered shapes are having least free energy with minimum internal stresses. There is a need to formulate the heat treatment process to tailor the characteristics in line with the application. The age old normalizing treatment provides more nucleation sites required for so that finer spheroids are dispersed in the matrix to improve toughness with balanced bulk hardness related properties to improve machinability. In line with requirements, the heat treatment cycle to balance mechanical and microstructural properties of AISI 1040 structural steel is designed. It is observed that lower spheroidizing temperature gives finer spheroids, more in number with better improvement in toughness whereas higher Spheroidization temperature reduces hardness values with lesser spheroid density, accordingly reduces strength and impact resistance. The balanced improvement in properties may be incorporated for metal removal operations to improve productivity and tool life.

DYNAMIC ANALYSIS AND OPTIMIZATION OF PROCESS PARAMETERS IN TURNING OPERATION BY USING ADAMS SOFTWARE

Metal turning process is a widely used process in Metal removal operations for reducing the diameter of workpiece. The force obtained in these operations are investigated experimentally and analytically with the help of numerical and optimization methods. Since, these machining operations have a complex structure; it is quite difficult to solve them analytically. Experimental method is also both costly and time consuming. However, this complex structure can be solved and analyze easily by using CAD based dynamic analysis software like ADAMs. This paper consist a software approach for dynamic analysis and optimization of process parameter in turning operation. The process of turning is influenced by many parameters such as cutting speed, feed rate and depth of cut; which are difficult to analyze analytically and experimentally; can be easily identified by using simulation tools on ADAMs. This Paper work contains a three dimensional dynamic modeling of turning process and simulation of model, to identify the effect of process parameter on various forces like Cutting force, Feed Force and Radial force and also to optimize the parameters for minimum cutting force. The magnitude of force variation thus obtained is further validated with the experimental results. The dynamic force magnitudes obtained experimentally and obtained in ADAMs are closely matching. This proves that the accuracy of the developed 3D model, dynamic analysis software and analytical model.

Development of three-dimensional finite element model to calculate the turning processing parameters in turning operations

Metal turning is a widely used process in metal removal operations. These operations are investigated experimentally, analytically and numerically. Since these operations have a very complex structure, it is quite difficult to solve them analytically. Experimental method is both costly and time-consuming. However, this complex structure can be solved easily by using numeric analyses based on finite element method (FEM). Modeling metal turning processes in three dimensional (3D) by using FEM may be useful for validation of experimental studies and it can be also considered as a reliable tool for new metal removal techniques. Parameters such as cutting tool stresses, cutting forces, tool wears, cutting tool temperature, workpiece temperature, chip temperature, cutting tool–chip interface temperature, residual stresses and shear angle, which are difficult to determined analytically and experimentally during turning processes, can be easily identified by using simulation tools based on FEM on the computer. In this study, a 3D FEM model and software were developed for turning processes. Mechanical power, heat transfer coefficients and friction coefficient at the tool–chip interface can be calculated for numeric analyses by using the software developed. A comparison was performed for temperature, main cutting force and thrust force obtained from experimental results and numerical analyses. It can be said that the 3D FEM model gives reasonable results with experimental results in view of temperature, main cutting force, thrust force, shear angle.

Cutting force-based adaptive neuro-fuzzy approach for accurate surface roughness prediction in end milling operation for intelligent machining

End milling is one of the most common metal removal operations encountered in industrial processes. Product quality is a critical issue as it plays a vital role in how products perform and is also a factor with great influence on manufacturing cost. Surface roughness usually serves as an indicator of product quality. During cutting, surface roughness measurement is impossible as the cutting tool is engaged with the workpiece, chip and cutting fluid. However, cutting force measurement is easier and could be used as an indirect parameter to predict surface roughness. In this research work, a correlation analysis was initially performed to determine the degree of association between cutting parameters (speed, feed rate, and depth of cut) and cutting force and surface roughness using adaptive neuro-fuzzy inference system (ANFIS) modeling. Furthermore, the cutting force values were employed to develop an ANFIS model for accurate surface roughness prediction in CNC end milling. This model provided good prediction accuracy (96.65 % average accuracy) of surface roughness, indicating that the ANFIS model can accurately predict surface roughness during cutting using the cutting force signal in the intelligent machining process to achieve the required product quality and productivity.

Simulations of Milling Process of Inconel 718 Alloy Based on Three Dimensional Finite Element Models

Nickel-based alloy is known as one of the most difficult–to-machine materials and the milling process is one of the most common metal removal operations. Modeling and simulation of milling process have the potential for understanding the milling mechanism, improving cutting tool designs and selecting optimum conditions, especially in advanced applications such as high-speed milling. This paper presents a 3D coupled thermo-mechanical finite element model based on ABAQUS\Explicit for the simulation of Inconel 718 chip formation in metal cutting. In the simulations, a Lagrangian formulation with an explicit solution scheme and a penalty contact algorithm has been used. The material behavior is modeled with classical Johnson-cook plasticity constitutive model and dynamic failure criteria for element removal, coupled with adaptive meshing and mass scaling technology for limiting the calculation time. The milling tool is modeled in UG software according to the real tool geometry, and meshed as a rigid tool. In order to verify the accuracy of 3D simulation, results (cutting forces and cutting temperature) were compared with the experimental results under the same cutting conditions as the simulations. The results obtained indicate that the simulation methodology is capable of predicting the cutting forces and cutting temperature. It suggests that 3D finite element simulation model of cutting processes can be truly trusted.

Experimental Analysis by Measurement of Surface Roughness Variations in Turning Process of Duplex Stainless Steel

Abstract The objective of the investigation was to identify surface roughness after turning with wedges of coated sintered carbide. The investigation included predic ting the average surface roughness in the dry machining of Duplex Stainless Steel (DSS) and the determination of load curves together with roughness profiles for various cutting conditions. The load curves and roughness profiles for various cutting wedges and variable cutting parameters were compared. It has been shown that dry cutting leads to a decrease in friction for lubricated surfaces, providing a small initial contact area where the surface is contacted. The st udy has been performed within a production facility during the production of electric motor parts and deep-well pumps. Keywords: turning, coatings, friction-reducing, optical microscopy, surface roughness analysis and models. © 2014 Polish Academy of Sciences. All rights reserved 1. Introduction Engineering surfaces, particularly those generated using multi-step manufacturing processes and intended for tribological applications such as bearings and gears, rarely if ever have perfectly normal distributed elevations [1]. Surface roughness measurements of any workpiece are among the most important ones in length and angle metrology, both in theory and practice. According to Wieczorowski et al. [2], there are great discrepancies in these measurements because of the large variety of instruments for surface roughness analysis. Hence, three-dimensional surface topography parameters are necessary for assessing the surface roughness characteristics more effectively [3]. According to Mahovic Poljacek et al. [4], a precise characterization of roughness and surface topography is of prime importance in many engineering industries because certain functional properties of the materials are often determined by the surface structure and characteristics. Estimation of the magnitude of surface roughness under the given cutting conditions resulting from metal removal operations is one of the major goals in this area [5, 6]. According to Benardos and Vosniakos [7], surface roughness is a widely used index of product quality and in most cases a technical requirement for mechanical products. Achieving the desired surface quality is of great importance for the functional behaviour of a part. Surface profilometry is for many years a well-known method of topography inspection [8–12]. Topography parameters represent surface properties is much better than 2D ones. Using the surface parameters can be determined functions describing surface behaviour. The workpiece material is duplex stainless steel because this stainless steel is widely used for many industrial applications due to its unique properties. Cabrera et al. [13] and Park et al. [14] consider that the good combination of their mechanical properties (high strength and toughness) and corrosion resistance makes them of great interest for a wide range of

A thermo-mechanical model of dry orthogonal cutting and its experimental validation through embedded micro-scale thin film thermocouple arrays in PCBN tooling

Cutting temperature and its distribution in the cutting zone are a critical factor that significantly affects tool life and degrades part accuracy during metal removal operations. However, issues surrounding their modeling and experimental validation in the immediate cutting zone still remain an unresolved issue. A major impediment is the unavailability of adequate temperature measurement methods with sufficient temporal and spatial resolution to measure actual temperatures and validate predictive models. In this paper, a model for the dry orthogonal cutting process with thermo-mechanical coupling effects, i.e., interactions between the stress state, strain rates and the temperature softening of material in the plastic deformation zone, is proposed to predict cutting temperature distribution in the cutting zone. The feasibility and prediction accuracy of the model is verified by experimental measurements through Thin Film Thermocouple (TFTC) arrays embedded at the immediate vicinity of the cutting zone into Polycrystalline Cubic Boron Nitride (PCBN) tooling. The experimental verification is performed under hard turning conditions. It has been shown that the predictions of the proposed model are in very close agreement with the experimentally measured results including the cutting forces, chip thickness and cutting temperature distributions on the rake and flank faces in the cutting zone. Furthermore, the modeling results have also provided an essential understanding on the stress distributions at the tool/chip and work/tool interfaces as well as of the nature of the chip flow velocity along the rake face of the cutting tool.

Historical Phases of EDM Development Driven by the Dual Influence of “Market Pull” and “Science Push”

Electrical discharges are a well-known effect in nature and are accompanied by a lot of physical phenomena, such as light, shock-waves, electromagnetic radiation, high temperature, material transfer and noise. Benjamin Priestley recognized in 1751 marks of material removal as “footprints”, when electrical discharges take place between two electrodes. Josef Priestley described in 1766 the formation of ring-marks with discharges from “Leiden Jars”. Meritens started in 1881 the use of electrical discharges with material transfer for arc-welding purposes, but it took until years around World War 2, before electrical discharges were used for controlled metal removal operations. This application is today nearly 75 years going on and developed to an important industry-branch. The authors analyze the important development steps, driven continuously by two forces, the “Science Push” and the “Market Pull”. The history of EDM is proving the strength and effectiveness of a dual training for applied engineering, developing knowledge and experience in parallel. Important personalities, successful product-developments and applications, and recognized brands will be presented.

Productivity improvement through chatter-free milling in workshops

High-speed machining has improved performance in manufacturing sectors such as the aeronautical, automotive, and mould and die industries. However, one problem of reaching such high speeds is the self-excitation of the spindle-tool system during the machining process. This so-called chatter vibration produces several negative effects: a reduction in surface quality and accuracy, and in tool and spindle life. Nowadays, it is still the most common limitation to increased productivity and quality of metal-removal operations. Although theoretically calculated stability-lobe diagrams can be used to calculate stable cutting conditions, some uncertainties affect the accuracy of this solution. This paper presents a method based on experimental tests where an inclined plane in the workpiece is machined at several spindle speeds. The gradual increase of the axial depth of cut allows the milling to be interrupted when chatter is detected. The final result is that the stability lobes are machined in the workpiece. This method can be used for process optimization and avoiding trial and error tests to determine optimal depths of cut and spindle speeds. The creation of a database with the optimal cutting conditions for a given spindle-tool holder-tool system can help the computer aided manufacturing (CAM) programmer select the cutting conditions that maximize the material removal rate and avoid vibration problems. The method presented is especially suitable for small- and medium-sized workshops where operators are unfamiliar with analytical methods or modelling techniques. It is an interesting way of saving money that does not require complex knowledge, and can easily be applied without additional costs owing to its simplicity.

A system for optimising cutting parameters when planning milling operations in high-speed machining

A highly important element when computer aided process planning (CAPP) is used consists to choose the manufacturing route in metal removal processes. The paper focuses on this problem related to high-speed machining technology. At present, decisions concerning the cutting parameters used in metal removal operations are based on experience.The goal is to design a system which helps to select the parameters in the cutting process of milling and high speed milling. The algorithm is based on optimising the cost of the operation. The result is the parameters that take into account all the existing restrictive factors included in machining operations.A wide range of parts have been evaluated, using group technology in order to choose representative cases. The results are evaluated with the values proposed in the reference manuals. The experiment has served to determine the different relationships between the factors that have an influence on milling operations when high-speed machining technology is used for all the pieces studied.Applying our method helps to make the right decisions on the optimal parameters in mill and high speed mill operations as applied to the machining processes, and, leads to a reduction for both conventional milling and high speed milling operations in processing times while ensuring optimal finishing conditions.

A decision support system for optimising the selection of parameters when planning milling operations

The paper focuses on the problem of choosing the manufacturing route in metal removal processes, a highly important element in computer aided process planning (CAPP) systems. At present, decisions concerning the cutting parameters used in metal removal operations are based on experience. The object of this work has been to design a system to help select the parameters in the cutting process in the case of milling. The algorithm is based on optimising the cost of the operation. The result is the selection of parameters that take into account all the existing restrictive factors (material, geometry, roughness, machine and tool). A wide range of parts have been evaluated, using group technology in order to choose representative cases. We compared the results of our system with the values proposed in the reference manuals. The experiment has served to determine the different relationships between the factors that have an influence on milling operations and the features which allow us to take into account the wide range of geometrical possibilities existing for all the pieces we studied. Applying our method helps to make the right decisions on the optimal parameters in mill operations as applied to the machining processes, and, in our experiments, leads to a reduction of about 35% in processing times while ensuring optimal finishing conditions.

The case against routine metal removal.

Metal removal is one of the most commonly performed operations in pediatric orthopedics. Many of these operations are performed electively in asymptomatic patients. In a retrospective study of 138 patients who had metal removal operations, the indication for surgery was uncomplicated healing in 69%. The overall complication rate was 13%, including incomplete removal in 7% and refracture in 1.4% after metal removal. Operations to remove metal from the proximal femur were associated with the highest complication rates, especially in patients with slipped capital femoral epiphysis. In a comparison of the risks associated with metal removal operations and the risks of long-term metal retention, little evidence was found to support a policy of routinely removing asymptomatic implants after the completion of bone healing.

Simulation of flexible automated systems for the discrete production of metal components by forging and machining

The integration of metal forming and metal removal operations in a single flexible manufacturing cell will advance further the area of application of the flexible manufacturing system and will contribute to the flexible automation of traditionally high volume applications. Forming operations will first be employed to achieve a near net shape of the components, so that only a minimum of subsequent machining operations will be required to manufacture the final forms. The efficient use of these systems depends considerably on the proper design of the system. A simulation model written in the PASCAL language is presented, capable of simulating a mixed type FMC. With the aid of this model the effect of the batch size and the carrying capacity of the pallets on utilisation of the machine tool and the throughput times of the orders is examined.