Machining Of Materials Research Articles

Wear of Abrasive Tools during CMC Machining

Machining CMCs under productivity conditions while limiting tool wear and material damage is a challenge for applications such as jet aircraft engines and industrial turbines. This contribution focused on developing a method to characterize the wear of abrasive tools based on fractal dimensions. This solution allows characterization of the state of the tool after each machining and identification of the type of damage to the tool (regular wear of the diamond grains, cleavage, or breakage) and its influence on the cutting forces, in addition to damage to the machined material and the quality of the machined surface. Thus, the chipped area and the maximum chipping are directly associated with the fractal dimension of the tool surface and the metal removal rate of the process. The quality of the surface (Sa, Sz, and Sq) is associated with the fractal dimension of the surface of the tool characterizing the state of the grinding wheel and the radial depth of cut ae characterizing the engagement of the tool in the CMC material. Moreover, the results also demonstrated that the use of an abrasive tool associated with cutting conditions close to milling and not grinding is a viable solution.

Numerical Modeling of Cutting Characteristics during Short Hole Drilling: Modeling of Kinetic Characteristics

Analyzing the cutting process characteristics opens up significant opportunities to improve various material machining processes. Numerical modeling is a well-established, powerful technique for determining various characteristics of cutting processes. The developed spatial finite element model of short hole drilling is used to determine the kinetic characteristics of the machining process, in particular, the components of cutting force and cutting power. To determine the component model parameters for the numerical model of drilling, the constitutive equation parameters, and the parameters of the contact interaction between the drill and the machined material on the example of AISI 1045 steel machining, the orthogonal cutting process was used. These parameters are determined using the inverse method. The DOE (Design of Experiment) sensitivity analysis was applied as a procedure for determining the component models parameters, which is realized by multiple simulations using the developed spatial FEM model of orthogonal cutting and the subsequent determination of generalized values of the required parameters by finding the intersection of the individual value sets of these parameters. The target values for the DOE analysis were experimentally determined kinetic characteristics of the orthogonal cutting process. The constitutive equation and contact interaction parameters were used to simulate the short hole drilling process. The comparison of experimentally determined and simulated values of the kinetic characteristics of the drilling process for a significant range of cutting speed and drill feed changes has established their satisfactory coincidence. The simulated value deviation from the corresponding measured characteristics in the whole range of cutting speed and drill feed variation did not exceed 23%.

Investigation of 300M ultra-high-strength steel deposited by wire-based gas metal arc additive manufacturing

300 M ultra-high-strength steel (UHSS) is widely used to produce landing gear components for aircraft. The conventional manufacturing route for these components involves extensive machining and significant material wastage. Here, the application of wire-based gas metal arc additive manufacturing to produce 300 M UHSS parts was investigated. In particular, the influence of torch shielding atmosphere on the process stability and material performance of 300 M UHSS was investigated. The shielding gases used for comparison are pure Ar, Ar with 2.5% CO2, Ar with 8% CO2, Ar with 20% CO2, and Ar with 2% CO2 and 38% He. It was found that the arc length decreased, the transfer mode changed from spray to droplet mode, and spattering became more severe as the CO2 proportion increased. Additionally, replacing Ar with He led to a broader arc core, and a slightly shorter arc length and maintained a spray transfer, which decreased spatter. The wall surface roughness followed the trend in spatter, becoming worse with the increasing CO2 proportion, and better with He addition. Adding CO2 and He in pure Ar significantly increased the bead and wall width. The microstructure and mechanical properties exhibited a strong location dependence in the as-built state, with fresh martensite and higher strength in the top region, and tempered martensite and better ductility in the reheated bulk. Generally, torch shielding gas composition appeared to have no significant effect on the microstructure evolution. This study provides a reference for the subsequent application of gas metal arc additive manufacturing to aircraft landing gear mass production to achieve a high deposition rate and process stability simultaneously.

A proposition to teach engineering projects using Problem-based Learning (PBL) concepts

This article shows the design of a mechanical engineering project using problem-based learning concepts. The work shows the complexity of the teaching-learning process of a complex problem such as developing, simulating, and testing a prototype of a piezoresistive pressure sensor. This type of problem is typical in theoretical-practical classes involving different concepts learned during an undergraduate course. The cognitive structure may or may not be influenced by the presentation of ideas and methods for organizing the content and executing the desired project. Using a pressure sensor project made it possible to develop the concepts of learning models by applying the idea of project-based learning (PBL). The main results obtained were the product design topology, operating concepts of a sensor device, computer-aided design projects, analysis of simulation results and assembly, and mechanical prototyping concepts, involving different materials for machining and product encapsulation.

Analysis of fatigue fracture incident of centrifugal compressor blades in a small turbojet engine

In this study, performance verification tests were conducted on a small turbojet engine, during which a failure occurred at the root of the centrifugal compressor blades, which are made of aluminum alloy. A detailed disassembly and inspection was carried out to reveal the reason of the failure. It was found that the failure of one blade at the root led to jamming of other blades. Then the jammed blades experience sever rubbing and contact with the intake duct. Experimental measurements of material properties and a retrospective examination of the manufacturing process revealed that the yield strength of the material was lower than the design value, and the fillet radius at the blade root was smaller than specifications. The root cause of the fatigue failure of the compressor blades in this incident was attributed to substandard machining quality and material properties, which leads to crack initiation and fatigue propagation until failure occurred. The experience of identifying the root cause would provide engineering guidance for other small turbojet engines.

A novel quasi-intermittent vibration assisted swing cutting device: Design and experimental investigation

Elliptical vibration assisted cutting (EVAC) is gradually being one of the most potential machining methods for difficult to machine materials. However, the elliptical trajectory causes periodic residual traces on machined surface. A novel quasi-intermittent vibration assisted swing cutting (QVASC) device driven by two piezoelectric actuators is proposed to reduce the residual traces between adjacent paths and improve surface quality. An X-shaped flexure hinge was used to suppress the mutual interference between two driving shafts and realize kinematic decoupling. The mechanical configuration and geometric parameters of the proposed device were designed based on the analyzing of kinematics, dynamics, and flexible characteristics. The effectiveness of the proposed device was verified by finite element analysis and off-line performance test. Tests results show that the maximum coupling ratio of motion axis, maximum motion stroke, and minimum resolution of QVASC device are 1.65%, 19.943 μm, and 9.55 nm, which are satisfied with the design and machining requirements. Finally, systematic turning experiments were carried out to verify the effectiveness of the proposed device in restraining cutting residual traces. The experimental results indicate that the proposed device can effectively inhibit the generation of periodic residual traces, which validates the feasibility of the QVASC device.

Improvement of Analytical Model for Oblique Cutting—Part I: Identification of Mechanical Characteristics of Machined Material

Analytical cutting models have recently become quite widespread due to the simplicity and rapidity of calculations as well as the stability of the solutions. This paper considers a procedure for determining the mechanical properties of machined material based on parameters for the analytical model of oblique cutting for a certain range of changes in cutting modes and inclination angles of the tool cutting edge. The model is based on the energy method of determining the main cutting process characteristics using the extreme assumptions of continuum mechanics. It is proposed to determine the parameters characterizing the mechanical properties of the processed material using the Johnson–Cook constitutive equation in two stages: preliminary determination of the constitutive equation parameters based on the results of mechanical compression specimen tests and experimental data of the oblique cutting process, and specifying the generalized values of the constitutive equation parameters using the inverse method through the finite element cutting model. The adequacy of the applied analytical cutting model is confirmed by comparing the kinetic characteristic values calculated using the analytical model of oblique cutting with the application of the specified parameters of the constitutive equation and the measured values of the kinetic characteristics. The deviation between the calculated and measured values of the cutting force components when changing the cutting depth (undeformed chip thickness) does not exceed 15%. The difference between the calculated and measured values of the cutting force components when the cutting speed is changed is about 20%.

Inconel 625 Coatings on AISI 304 Steel using Laser Cladding: Microstructure and Hardness

Nickel-base super alloys such as Inconel 625 are preferred in high-temperature and corrosive environments. Since Inconel 625 is expensive and often difficult to machine, it is advantageous to deposit a protective coating of this alloy on a less costly and easily machinable substrate material such as stainless steel. In the present work, coatings were produced on AISI 304 steel substrate by depositing Inconel 625 powder using the laser cladding technique. As-received powder particles of Inconel 625 alloy were characterized using X-Ray Diffraction (XRD) and Field Emission Scanning Electron Microscopy (FESEM). After laser cladding, it becomes important to carry out the microstructural analysis of the cross-sectional areas of the coating and the substrate/coating interface region, for further understanding of the structure-property correlations. In this study, the microstructural features of the coatings and substrate/coating interface were examined using an FESEM equipped with X-ray elemental analysis. The phase analysis of the coating was carried out using XRD. In the coating region, the growth of planar, cellular, columnar dendritic, and equiaxed grains was noticed. It was observed that small amounts of Laves phase were precipitated. Furthermore, the laser-clad Inconel 625 coating showed superior microhardness over the stainless steel substrate.

A Novel Approach of Heat Assisted Parallel Turning Process

Hard materials are widely used in industry due to qualities such as strong fatigue strength and the ability to maintain strength at a high temperature. Still forming certain raw materials into the appropriate shapes is the challenge in subtractive manufacturing industries and these materials are categorized as hard to machine material. To solve this problem Heat Assisted Machining (HAM) is an emerging and most dominating method, which requires an external heat source subjected to the workpiece either before or during the machining to increase the ductility. As a result, the workpiece yield and shear strength are reduced. This is an advanced technique to enhance the tool’s life, and productivity. The present paper provides in-depth knowledge of thermal assisted machining process where various heat sources are used like laser, plasma, LPG, Induction heating and etc. The comparison analysis between various heat sources is made and their impact on various parameters like tool wear, material removal rate, surface roughness, stability and etc. were illustrated and provide the novel approach for selecting the correct heat-assisted technique which is used for turning process in order to increase the machining process.

Study of 3D Metal Printed and Metal Filled Epoxy Materials for Rapid Tooling in Injection Molding

Common rapid tooling techniques can be classified as indirect and direct methods. As indirect methods, casting a mixture of epoxy and metallic powder over a pattern to obtain the mold shape is currently a fast and reliable method. As direct methods, Additive Manufacturing (AM) technologies such as Selective Laser Melting (SLM) can directly manufacture a mold ready for operation. Recently, progress in Fused Deposition Modeling (FDM) materials have brought into play a large variety of 3D printed polymers with high percentage of fiber metals that can be more easily printed using the FDM technology instead of SLM or other more advance techniques. In this paper, a study is conducted to analyze the main characteristics of different FDM materials with metal fibers and different epoxy metal filled materials for rapid tooling in injection molding. The study analyzes the properties of these materials such as yield strength, tensile strength, thermal conductivity and wear resistance, and compares them with those from common traditional machined materials for molding such as tool steels and aluminum. Furthermore, the paper shows a comparison of costs and advantages and drawbacks of using these materials for a standard molding insert in industry.

Investigative study on the properties of magnetic materials for electrical machines

<p><span>The paper attempts to investigate the properties of the magnetic materials used in the construction of rotating electric machines, with a view to arrive at the appropriate choice for the induction motors in particular. Measurement of magnetic properties for rotating electrical machines are more important to both machine designer and operator. This paper discusses the influence of magnetic properties of electrical steel on performance of electrical machine. Here properties like BH curve, core loss, permeability and other vital parameters are measured using 400×400 Epstein tester over wide range flux density and frequency up to 50 Hz and 400 Hz. The results measured in terms of the core loss, BH curve and permeability showcase the benefits to decide on the suitability of the material for use in practice.</span></p>

Simulation-based investigation on ultra-precision machining of additively manufactured Ti-6Al-4V ELI alloy and the associated experimental study

Additive Manufacturing (AM) has shown excellent research potential for biomedical implants, complex aerofoil structures, military applications, high-pressure cryogenic vessels, and automobile components. The mechanical properties exhibited by the additively manufactured Ti6Al4V ELI alloy components are significantly different from traditionally manufactured Ti6Al4V alloy due to the material anisotropy, orientation of the microstructure, and variation in heat treatments. Among AM techniques, SLM (Selective laser melting) offers unparalleled design flexibility with minimum impurities and high reproducibility. However, post-processing of additive manufactured components is essential due to their poor surface finish and lack of dimensional accuracy. Ti6Al4V ELI (Extra Low Interstitials) alloy is a difficult-to-cut material in Ultra-Precision Machining (UPM) due to its excessive tool wear, hardness, and chemical reactivity. Optimizing machining parameters for better surface finish by UPM is time-consuming and often not economical. Modeling and simulation provide a low-cost approach for the investigation of machining. In this work, a series of cutting experiments have been carried out on additively manufactured Ti6Al4V ELI alloy to study the cutting mechanism during UPM. In addition, Finite Element Model (FEM) is employed to understand the chip formation and cutting forces in UPM with a built-in Johnson-Cook (JC) model and a Johnson-Cook-TANH (JC-TANH) vectorized user-defined material subroutine (VUMAT) model. Cutting forces corresponding to the JC model and JC-TANH are examined with the experimental forces in literature, and the results are found to be fairly close.

A Novel Polyester Varnish Nanocomposites for Electrical Machines with Improved Thermal and Dielectric Properties Using Functionalized TiO2 Nanoparticles.

Recently, there has been a growing interest in polymer insulating materials that incorporate nanoscale inorganic additives, as they have shown significantly improved dielectric, thermal, and mechanical properties, making them highly suitable for application in high-voltage insulating materials for electrical machines. This study aims to improve the dielectric and thermal properties of a commercial polyester varnish by incorporating different concentrations of titanium dioxide nanoparticles (TiO2) with proper surface functionalization. Permafil 9637 dipping varnish is the varnish used for this investigation, and vinyl silane is the coupling agent used in the surface functionalization of TiO2 nanoparticles. First, nanoparticles are characterized through Fourier transform infrared spectroscopy to validate the success of their surface functionalization. Then, varnish nanocomposites are characterized through field emission scanning electron microscopy to validate the dispersion and morphology of nanoparticles within the varnish matrix. Following characterization, varnish nanocomposites are evaluated for thermal and dielectric properties. Regarding thermal properties, the thermal conductivity of the prepared nanocomposites is assessed. Regarding dielectric properties, both permittivity and dielectric losses are evaluated over a wide frequency range, starting from 20 Hz up to 2 MHz. Moreover, the AC breakdown voltage is measured for varnish nanocomposites, and the obtained data are incorporated into a finite element method to obtain the dielectric breakdown strength. Finally, the physical mechanisms behind the obtained results are discussed, considering the role of nanoparticle loading and surface functionalization.

Multi-objective optimization of surface morphology using fractal and multi-fractal analysis for dry milling of AISI 4340

Machining of difficult-to-cut metals is typically associated with inconsistent machining quality, high machining costs, and significant environmental pollution. This work proposes a novel method that utilizes fractal and multi-fractal features of the machined surface morphology to evaluate surface quality in high-speed dry milling of 4340 steel. The results demonstrate that the fractal dimension can be used as an evaluation index for machined surface defects. It accurately characterizes the contour information of machined surface defects, including voids, tears, and material side flow. A smaller fractal dimension indicates fewer surface defects and represents a higher-quality machined surface. However, the surface defects cannot be described using the traditional evaluation method based solely on surface roughness (Ra). Moreover, multi-objective optimization of high-speed milling of 4340 steel is achieved by using the combined indices Ra and fractal features as responses. The Ra generated using the optimized parameters can reach 97 nm, which represents a reduction of 4.9 % compared to the non-optimization state. And typical defects on machined surfaces virtually disappear. Meanwhile, the machining cost has been reduced by 2.52 % and the machining efficiency has increased by 31.45 %. The results demonstrate that the proposed surface quality evaluation method is possible for practical engineering applications to achieve high-quality, high-efficiency and low-cost high-speed dry milling of high-strength steels.

Single-grain scratching of SiCf/SiC composite under minimum quantity lubrication: Force and material removal mechanism study

As one of the most novel fiber-reinforced ceramic matrix composites, SiCf/SiC composites are difficult to be processed machine materials. On top of that, the underlying material removal mechanism not yet completely understood. Along these lines, in this work, single-grain scratching orthogonal tests with different MQL methods were carried out to systematically analyze the influence of the different processing directions and lubrication methods on the material removal lubrication mechanism and the scratching force in the scratched surfaces. From the acquired results, it was demonstrated that the scratch force was the smallest when the processing direction is was 0° to the fiber direction. In addition, the utilization of MQL from vegetable oil can effectively reduce the cutting force. Diamond indenter caused significant damage to the surface of SiCf/SiC composites when the machining direction was 90° to the fiber direction, while narrow but deep grooves on the surface were observed when the angle was 0°. The dominant mode of material removal of SiCf/SiC composites was a brittle fracture, and the damage features mainly included direct fiber breakage, matrix fragmentation, fiber pullout, and fiber outcropping. The increase of the processing ratio of 0° and implementation of vegetable oil for MQL was proven as one of the best methods.

Multi-Body Dynamic Analysis of Hydrostatic Bearing with the MMC Material in Micro-Nano Machining.

This study focuses on the analysis of a linear hydrostatic bearing using harmonic frequency response and harmonic response simulations. The aim is to evaluate the feasibility of replacing the existing alloy steel material with a metal matrix composite (MMC) in terms of its performance and dynamic characteristics for both the base and carriage parts. The simulation results indicate that the MMC material exhibits higher resonant frequencies and improved damping capabilities compared to the structural steel material. The higher resonant frequencies observed in the MMC material are attributed to its stiffness and structural properties. These properties contribute to increased natural frequencies and improved vibration damping characteristics. This suggests that incorporating the MMC material in the bearing design could enhance motion control, improving the ability to precisely control and manipulate the movement of components or systems. In the context of ultraprecision machining applications, incorporating the MMC material in the hydrostatic bearing design can also lead to a more accurate and controlled motion, resulting in improved precision and finer machining outcomes. The displacement analysis confirms that both materials meet the specifications provided by the manufacturer, supporting the viability of using MMC as an alternative. However, further experimental validation and considerations of material feasibility, manufacturing factors, and cost-effectiveness are necessary before implementing the MMC material in practical applications. Overall, this research highlights the potential benefits of MMC in the design of linear hydrostatic bearings, paving the way for enhanced performance in ultraprecision machining processes.

Enabling Jet-Electrochemical Discharge Machining on Niobium-Like Passivating Metal and the Single Step Fabrication of Coated Microstructures

Analogous to difficult-to-cut materials in mechanical machining, Niobium (Nb) is a difficult-to-dissolve metal by electrochemical machining (ECM) due to its prone-to-passivation nature. Jet-electrochemical discharge machining (Jet-ECDM), which uses anodic discharge rather than the cathodic discharge as in traditional ECDM, has been previously demonstrated as an efficient method for machining inert semiconductors like Si, 4H-SiC. However, applying Jet-ECDM on Nb-like passivating metal is very challenging because plasma electrolytic oxidation (PEO) is very prone to occur in the machining area due to anodic discharges, forming an insoluble, highly stable oxide coating that prevents material removal. This study reveals the principles of overcoming PEO to enable Jet-ECDM on metals. The findings show that the discharge intensity, affected by the electric field and pulse frequency, is decisive in achieving Nb material removal. The electrolyte chemistry significantly influences material removal fashions, depending on the electrolyte’s chemical activity. NaOH is the preferred choice for higher removal efficiency (maximum 1.92 mm min−1) and machining localization, while NaCl ensures better surface quality (Sa 99.4 nm). Moreover, the Jet-ECDM generated microstructure surface presents a thin layer of PEO coatings (<1 μm). This demonstrates the high potential of Jet-ECDM technology for efficient fabrication of coated microstructures in a single-step process.

Unleashing the Power of Artificial Intelligence in Materials Design.

The integration of artificial intelligence (AI) algorithms in materials design is revolutionizing the field of materials engineering thanks to their power to predict material properties, design de novo materials with enhanced features, and discover new mechanisms beyond intuition. In addition, they can be used to infer complex design principles and identify high-quality candidates more rapidly than trial-and-error experimentation. From this perspective, herein we describe how these tools can enable the acceleration and enrichment of each stage of the discovery cycle of novel materials with optimized properties. We begin by outlining the state-of-the-art AI models in materials design, including machine learning (ML), deep learning, and materials informatics tools. These methodologies enable the extraction of meaningful information from vast amounts of data, enabling researchers to uncover complex correlations and patterns within material properties, structures, and compositions. Next, a comprehensive overview of AI-driven materials design is provided and its potential future prospects are highlighted. By leveraging such AI algorithms, researchers can efficiently search and analyze databases containing a wide range of material properties, enabling the identification of promising candidates for specific applications. This capability has profound implications across various industries, from drug development to energy storage, where materials performance is crucial. Ultimately, AI-based approaches are poised to revolutionize our understanding and design of materials, ushering in a new era of accelerated innovation and advancement.

Structural, elastic, electronic, bonding, thermo-mechanical and optical properties of predicted NbAlB MAB phase in comparison to MoAlB: DFT based ab-initio insights

In recent times transition metal ternary borides with layered structure have attracted much attention of the materials science community. In this study, we have used density functional theory (DFT) based first-principles investigation of the physical properties of prospective NbAlB compound for the first time. From the analysis of the cohesive energy and enthalpy of formation, it was found that NbAlB is expected to be chemically stable. The physical properties of NbAlB have been compared and contrasted with those obtained for MoAlB. Both these MAB phases are elastically anisotropic, mechanically stable, machinable and brittle materials. Structural and elastic features reflect the layered features. The estimated hardness of NbAlB is 19.0 GPa comparable to that of MoAlB (20.8 GPa) suggesting that predicted NbAlB is a hard compound and is suitable for heavy duty industrial applications. NbAlB is more machinable than MoAlB. Electronic band structure calculations reveal conventional metallic behavior with the electronic density of states at the Fermi level arising mainly due to the Nb 4d orbitals in NbAlB. The electronic density of states at the Fermi level is significantly higher in NbAlB in comparison to MoAlB, indicating that NbAlB is expected to exhibit higher level of electrical conductivity. Electronic dispersion is highly anisotropic for both MoAlB and NbAlB with substantially large electronic effective masses in the out-of-plane directions. The bonding features have been elucidated via the analysis of the band structure and charge density distribution. Both the compounds have mixed covalent, ionic and metallic bonding characteristics. The Fermi surfaces of MoAlB and NbAlB consists of electron and hole like sheets. The Debye temperatures of MoAlB and NbAlB are comparable. The estimated melting temperature of NbAlB is somewhat lower than that of MoAlB. NbAlB shows excellent reflection characteristics suitable to be used as an efficient solar reflector. NbAlB is also expected to absorb ultraviolet radiation very effectively. Unlike elastic, bonding, and electronic anisotropy, the optical spectra are fairly isotropic for NbAlB with respect to the polarization of the incident electric field.

A Review on the Usage of Different Optimization Techniques for Wire Electro Discharge Machining of Stainless Steels

Wire electrical discharge machining (WEDM) is a non-traditional metal cutting procedure and the overall cutting process is contactless between the wire and work material. A plasma channel is created by the electrical energy between work piece and wire, which convert the electrical energy into thermal energy and the temperature rises (8000°C to 12000°C). Due to this mechanism, metal is melted from the upper surface of work piece. Generally difficult to machine material is used to cut in WEDM. However, stainless steel (SS) is one of them, it is a metal alloy, which is mixed with steel and other elements such as chromium (Cr), nickel (Ni), molybdenum (Mo), silicon (Si), carbon (C), nitrogen (N2), and manganese (Mn) etc. SS has some excellent properties, such as high durability, high tensile strength, and corrosion resistant etc. Due to these properties SS is mainly used in automobile industries, biogas tank, combustion chamber and petrochemical industries etc. The present paper discussed about the machining of different SS grades in WEDM and effect of several input parameters (such as pulse on time (Ton), pulse off time (Toff), servo voltage (SV), wire feed (WF) etc.) on response parameters (such as material removal rate (MRR), surface roughness (SR), kerf width (KW) etc.). The review paper also reports the uses of different optimization techniques (such as taguchi technique (TT), response surface method (RSM), gray relational analysis (GRA) etc.) on various SS grades for optimizing the response parameters on the basis of different input variables. Furthermore, the research shows how to vary the value of output responses corresponding to input parameters value. Keywords: WEDM; stainless steels; input variables; output variables; optimization techniques.