Machining Forces Research Articles

Damage Mechanism of Subsurface of FeCoNiCrAl High-Entropy Alloys B ased on Molecular Dynamics Simulation Under Different Temperature

This study investigates how thermal conditions affect the nanomachining of FeCoNiCrAl high-entropy alloys, using molecular dynamics simulations at 100[Formula: see text]K, 150[Formula: see text]K and 200[Formula: see text]K. Key findings include a direct relationship between stress intensification and machining velocity at all temperatures, with stress concentrating at intergranular boundaries. At subsonic speeds ([Formula: see text]200[Formula: see text]m/s), stress inversely correlates with temperature, while at supersonic speeds ([Formula: see text]200[Formula: see text]m/s), stress increases with temperature. Incremental cutting depths affect chip morphology, with chips at 150[Formula: see text]K being 1.38 times thicker than at 200K. Minimum machining forces were 94.5[Formula: see text]Nn, 101.2[Formula: see text]Nn and 92.5Nn along [100], and 87.3[Formula: see text]Nn, 85.3[Formula: see text]Nn and 86.1[Formula: see text]Nn along [001]. Dislocation densities showed higher values at lower temperatures, with peak 1/2 [Formula: see text] densities at 100[Formula: see text]K being 1.43 and 1.45 times greater than at 150[Formula: see text]K and 200[Formula: see text]K, respectively.

Machining Performance of Ti6Al4V Nano Composites Processed at Al2O3 Nano Particles Mixed Minimum Quantity Lubrication Condition

Introduction: In this research work, an attempt was made to machine Ti6Al4V nano composites utilizing Al2O3 mixed nano fluid at minimum quantity lubrication condition, in which experiments were designed using the L16 orthogonal array, whereas Material Removal Rate, Surface Roughness, machining force and power were recorded as responses. Methods: The nano composites were fabricated using the stir casting technique and the nano particles were synthesized using the sol-gel technique. the microstructure revealed that the homogeneous dispersion of particles with dendric arms. Increased cutting speed and feed lead to more tool wear, which in turn causes a decrease in surface quality and an increase in surface roughness. Results: Larger areas of cut are often the consequence of higher feed rates, which increases the amount of friction between the work piece and the cutting edge. The machining force increases when the feed rate is increased. A higher feed rate produces a large volume of the cut material in a given length of time in addition to having a dynamic impact on the cutting forces. Conclusion: It also results in a corresponding increase in the typical contact stress at the tool chip interface and in the tool chip contact zone.

Comparison of machining forces, power consumption, and specific cutting energy in tools with grooved cutting edges for sustainable manufacturing

ABSTRACT The ease at which a material is cut or formed to the required shape is defined as machinability. Higher machinability, superior productivity, and sustainability are the three key parameters used to evaluate machining performance. The tools designed to support these performance parameters are intended to consume less power, generate lower forces, produce surfaces with lesser roughness, and provide a higher tool life. Hence, the purpose of the investigation is to compare the efficiency of milling inserts with grooves (serrations) on the cutting edges (also called porcupine edges) in machining AISI 304 austenitic stainless steel and AISI 4140 low-alloy, medium-carbon steel materials. The metal cutting test results show that the milling inserts with grooved cutting edges consumed 8% to 17% less power and specific cutting energy, and exhibited 7% to 16% lower resultant force in AISI 304 steel. Similarly, 9% to 15% less power consumption, specific cutting energy, and 10% to 14% lower resultant force than the tools with straight cutting edges were also observed in AISI 4140 steel. The reduction in cutting power, specific cutting energy, and forces is credited to the decreased contact length between the tool edge and workpiece, providing lesser resistance in the inserts with grooved cutting edges.

Design and real-time implementation of a sliding mode observer utilizing voltage signal injection and PLL for sensorless control of IPMSMs

In this study, a sliding mode observer (SMO) based on high-frequency (HF) voltage signal injection and a phase-locked loop (PLL) is proposed for estimating the extended electromotive force (EEMF), rotor position, and rotor velocity of an interior permanent magnet synchronous machine (IPMSM). This approach addresses real-time estimation challenges associated with standard SMO and PLL at very low speeds and standstill. A reliable and accurate sensorless speed control system for IPMSM is then developed and implemented in real time using the proposed SMO and PLL, covering a wide range of speeds, including low-speed and standstill conditions. The SMO effectively estimates the EEMF, while the PLL extracts the rotor velocity and position based on these estimates. Compared to conventional SMO and PLL methods, real-time results from an 8-pole, 0.4 kW IPMSM demonstrate the superior efficiency of the proposed system.

Simultaneous cutting and grinding of micropins using cylindrical microtools

Decreasing cutting force is always crucial in cutting processes. One method to achieve this is by minimizing tool wear, for which rotary cutting is a highly effective technique. The use of a cylindrical tool offers the additional benefit of easy tool fabrication, which is especially advantageous for a microtool capable of machining micropins. However, there have been no reported studies on rotary cutting using a cylindrical microtool. It should be noted that if a microtool is fabricated by electrical discharge machining, it is expected to engage in cylindrical grinding as well. This suggests that both rotary cutting and cylindrical grinding can be carried out simultaneously; however, there have also been no reported studies on simultaneous cutting and grinding. Therefore, the present study investigated whether this machining method can perform micropin machining, if it actually involves both cutting and grinding actions, and whether the combination of these actions enhances material removal capability. In turning and grinding experiments, where only one of the tool and workpiece was rotated, both actions were observed. Furthermore, it was confirmed that micropin machining can be performed by rotating both the tool and workpiece, resulting in a decrease in machining force to approximately one-quarter to one-half compared to that of turning. This indicates that simultaneous cutting and grinding was carried out, and the overlap of their actions enhanced material removal capability. In addition, the relationship between the machining conditions and machining force was investigated. At a small depth of cut, a tool with smaller surface roughness exhibited lower machining force than a tool with larger roughness, and the opposite was true at a large depth of cut. Finally, an ultrasmall-diameter micropin with a diameter less than 3 μm was successfully machined using conditions capable of reducing machining force.

Portable Machine Tools by Small Piezoelectric Robots for Scalable and Waviness‐Adaptive Fabrication of Surface Microstructures

Surface functional microstructures exhibit extensive application requirements in an array of breakthrough areas. One critical problem that restricts their industrial application is the lack of scalable fabrication techniques due to the limitation of conventional machine tools. This study proposes a scalable surface texturing technique using a portable small (30 × 19 × 22 mm) three‐leg robot that walks and works on the workpiece surface. Due to the elliptical tool vibration, microgrooves can be created on the workpiece surface periodically; meanwhile, the machining force drives the robot to walk forward. Surface texturing experiments are conducted on aluminum and copper workpieces to explore the machining performance of the small robot. The robot can reach a maximum moving velocity of 6.3 mm s−1 and can produce microstructures with a spacing of 4–14 μm on workpiece surfaces. Owing to its unique working principle, the small robot can maintain a constant depth of cut, demonstrating its capacity to adapt to the surface waviness of the workpiece. Finally, the motion straightness of the robot is greatly improved by combining it with the auxiliary track, and multiline microstructures are obtained. In short, the developed small robot presents a promising solution to the challenge of scalable surface texturing.

Rotary ultrasonic surface machining of silicon: Effects of ultrasonic power and tool rotational speed

The surging demand for monocrystalline silicon materials in the production of microelectronic components highlights its crucial role in the semiconductor and optic industries. Hence it is inevitable to produce a silicon workpiece with high quality finish to meet the demand in semiconductor industries. Due to high brittleness, controlling the quality of silicon in surface machining is quite difficult. Traditional manufacturing processes induce issues like rough surfaces and edge chipping. It was reported that rotary ultrasonic surface machining (RUSM) can effectively reduce cutting force, roughness, and edge chipping in machining of brittle materials. There have been several studies on drilling and sliding silicon materials using rotary ultrasonic machining investigating the effects of machining parameters on the output variables such as cutting force, torque, edge chipping, surface roughness etc. However, to the best of the authors’ knowledge, there are no reported investigations on effects of machining variables (ultrasonic power and tool rotation speed) in surface machining of silicon materials using the rotary ultrasonic machining. This study aimed to investigate the impacts of ultrasonic power and tool rotation speed on the cutting force, edge chipping, and surface roughness. Experimental results show that the ultrasonic vibration and tool rotation speed had a notable impact on edge chipping and cutting forces. Lastly, the current research has paved the way for widening the research on investigating grinding of the silicon wafer in semiconductor manufacturing with ultrasonic vibration and high rotation speed. In semiconductor wafer manufacturing, grinding process is used to reduce the flatness but generate surface and subsurface damage. With further investigations, RUSM can contribute to reducing these damages.

Energy features of friction thermomechanical handling (FTMH) of steel products and the effect on the state of their surface structure

Abstract. Problem. The article deals with the influence of energy and power characteristics of frictional thermomechanical handling of steel products (FTMH) on the state of their surface. Goal. The goal of this work is to study the relationship between the energy and power parameters of steel FTMР and the strengthening result. Methodology. To achieve this goal, the following tasks were solved: fabrication of samples from 65G steel, preliminary hardening heat treatment of samples, hardening of the working surface of samples using FTMO, measurement of the components of the cutting force arising from FTMO using a dynamometer, analysis of the microstructure and microhardness of each sample, comparison of the microstructure, microhardness, and depth of hardening of the experimental samples, conclusions regarding the relationship between the effectiveness of hardening of samples during processing and the energy and power parameters of FTMH. Results. Changes in the structures and properties of samples made of steel, which is used for products requiring a hard and wearresistant surface under the influence of processing to form surfaces with altered properties, are shown. Originality. Measurements of the machining process at FTMH using a dynamometer were carried out and the circumferential (circular) cutting (machining) force was calculated, which made it possible to construct graphical dependencies that allow characterizing the surface hardening taking into account the thickness of the disk. It is shown that the microhardness of the surface of the prototypes was increased to 1300 kg/mm2, which is equivalent to 13000 MPa. Practical value. Recommendations on the optimal thickness of the hardening disk have been made, taking into account the results obtained. The research results can be used in production and research.

Orthogonal cutting of 3D printed multi-material workpiece: numerical investigation of machining forces, stress, and temperature distribution

AbstractWith the development of 3D metal printers for rapid prototyping and industrial component production, heightened attention was directed towards post-processing operations for achieving precise surface quality and geometrical tolerances for these components. This paper investigated the orthogonal cutting of multi-material 3D printed workpieces using a coated cutting tool through finite element simulation. The workpieces featured different horizontal and vertical arrangements of layers composed of aluminum 7075-T6 alloy (Al), stainless steel 316 low alloy (SS), and Ti6Al4V alloy (Ti). The study explored the impacts of multi-material composition, coating thickness, and the rake angle of the cutting tool on machining forces, stress distribution, temperature distribution, and chip formation geometry. The results revealed a bimodal chip morphology in the machining process of horizontally arranged SS layers combined with other alloys. The SS layer resulted in a relatively uniform chip formation, while layers with two other materials exhibited a serrated chip formation. In contrast, a discontinuous chip formed when combining Al and Ti materials, as well as in the horizontally arranged layers made of Al, SS, and Ti alloys. The cutting force increased by 2.26 times when cutting workpieces with the horizontal arrangement of SS and Al layers compared to those with a single Al material. For the horizontal and vertical arrangement of layers made of Al and SS, von Mises stress values over the edge of the coated cutting tool significantly increased where the tool contacted the SS layer. Additionally, the horizontal arrangement of layers made of Al and SS materials caused the coated cutting tool to exhibit an extensive temperature distribution, with the maximum recorded temperature reaching 1448 °K. Increasing coating thickness led to a decrease in maximum principal stress at the surface of the tool and a rise in temperature at the cutting edge of the insert.

Improving the Performance of the Machining Process by Using Ultra‐Advanced Tools in a Clean Turning of Inconel 686 Using the Minimum Quantity Lubrication Method

ABSTRACTThe high tensile strength and high resistance of nickel‐based superalloy 686 against high temperatures and corrosion rates have made it a widely used in important applications such as the aerospace industry, high pollution‐ and corrosion‐resistance equipment manufacturing and petrochemical industry. Therefore, the machining of this advanced alloy with its unique properties is extremely important and can be challenging. Significant increase in input parameters levels, reduction of machining costs, improvement of surface and subsurface properties and clean production are among the issues that should be considered in dealing with Inconel 686 turning operations. Simultaneous application of advanced tools such as polycrystalline diamond (PCD) and polycrystalline cubic boron nitride (PCBN) and optimised minimum quantity lubrication (MQL) method and evaluating the results obtained with a wide range of output parameters related to machining process performance and tribological properties can be proposed as an innovation and a solution to this problem in this article. This study analyses several output parameters with different speeds and feeds to evaluate the effect of cutting insert type on machining process performance and tribological properties. The output parameters include tool wear, residual stress, cutting zone temperature, surface smoothness, machining forces and workpiece surface defects. The results indicated that using the optimised MQL method reduces the size of lubricant droplets and increases the surface covered by cooling. With these changes, the performance of the machining process and the parameters related to the surface integrity increase significantly. Among the parameters associated with the performance of the machining process, the PCD tool reduces the cutting zone temperature by 23%, the tool wear by 19% and the machining forces by 18% compared to the PCBN tool. In the parameters related to surface integrity, this method reduces the residual stress by 19% and the surface roughness by 9% compared to the PCBN tool. From the production index perspective, the PCD tool can significantly increase the cutting speed and feed rate, reducing production time and costs.

A thermo-mechanical fully coupled model for high-speed machining of Ti6Al4V

PurposeThis study aims to further refine the model, explore the influence of cutting parameters on the machining process, and apply it to practical engineering to improve the efficiency and quality of titanium alloy machining.Design/methodology/approachThis paper establishes a comprehensive thermo-mechanical fully coupled orthogonal cutting model. This paper aims to couple the modified Johnson–Cook constitutive model, damage model and contact model to construct a two-dimensional orthogonal cutting thermo-mechanical coupling model for high-speed cutting of Ti6Al4V. The model considers the evolution of microstructures such as plastic deformation, grain dislocation rearrangement, dynamic recrystallization, as well as stress softening and hardening occurring continuously in Ti6Al4V metal during high-speed cutting. Additionally, the model incorporates friction and contact between the tool and the workpiece. It can be used to predict parameters such as cutting process, cutting force, temperature distribution, stress and strain in titanium alloy machining. The study establishes the model and implements corresponding functions by writing Abaqus VUMAT and VFRICTION subroutines.FindingsThe use of different material constitutive models can significantly impact the prediction of the cutting process. Some models may more accurately describe the mechanical behavior of the material, thus providing more reliable prediction results, while other models may exhibit larger deviations. Compared to the Tanh model, the proposed model achieves a maximum improvement of 8.9% in the prediction of cutting force and a maximum improvement of 20.9% in the prediction of chip morphology parameters. Compared to experiments, the proposed model achieves a minimum prediction error of 2.8% for average cutting force and a minimum error of 0.57% for sawtooth parameters. This study provides a comprehensive theoretical foundation and practical guidance for orthogonal cutting of titanium alloys. The model not only helps engineers and researchers better understand various phenomena in the cutting process but also serves as an important reference for optimizing cutting processes.Originality/valueThe originality of this research is guaranteed, as it has not been previously published in any journal or publication.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0168/

Robust and effective ab initio molecular dynamics simulations on the GPU cloud infrastructure using the Schrödinger Materials Science Suite

Ab initio Born-Oppenheimer molecular dynamics (AIMD) is a valuable method for simulating physico-chemical processes of complex systems, including reactive systems, and for training machine learning models and force fields. Speed and stability issues on traditional hardware preclude routine AIMD simulations for larger systems and longer timescales. We postulate that any practically useful AIMD simulation must generate a trajectory of a minimum 1000 MD steps a day on a moderate cloud resource. In this work, we implement a computing workflow that enables routine calculations at this throughput and demonstrate results for several non-trivial atomistic dynamical systems. In particular, we have employed the GPU implementation of the Quantum ESPRESSO code which we will show increases AIMD productivity compared to the CPU version. In order to take advantage of transient servers (which are more cost and energy effective compared to the stable servers), we have implemented automatic restart/continuation of the AIMD runs within the Schrödinger Materials Science Suite. Finally, to reduce simulation size and thus reduce compute time when modeling surfaces, we have implemented a wall potential constraint. Our benchmarks using several reactive systems (lithium anode surface/solvent interface, hydrogen diffusion in an iron grain boundary) show a significant speed up when running on a GPU-enabled transient server using our updated implementation.

Sustainable machining of AISI 4340 steel using semi-vegetable oil blends

ABSTRACT This study concentrates on the utility of the newly formulated machining fluid used for turning AISI 4340 steel under the near dry machining method. The preparation of the novel machining fluid involves a blending of vegetable oils and conventional lubricant in a 50:50 ratio. Three distinct compositions were investigated within this work. The biodegradability tests confirms that the novel lubricantaligns with the ethos of “Green Machining.” The study’s focal points include an analysis of the following crucial metrics – machining force, machining temperature, and surface finish. From the analysis, the best-formulated blend was identified. To evaluate its performance, the variance analysis on the dataset (ANOVA) and Weighted Entropy decision-making method that ranks the best option along with alternatives was executed. Further, the optimal process parameters were determined using Dragon Fly Algorithm (DFO) and Particle Swarm Algorithm (PSO) to enhance the efficacy and quality of machining.

COMPARISON OF CUTTING TOOL GEOMETRIES BASED ON CUTTING FORCES AND ROUGHNESS OF HARD TURNED SURFACES

Surface quality and energy consumption are two widely studied topics of hard machining. Due to the increasing need of companies for new, more efficient materials, tools and procedures, their manufacturers or suppliers have to deliver innovative solutions from time to time. In this study the latest development of a hard turning insert manufacturer is used in comprehensive machining experiments to show how the new tool (a wiper insert) behaves compared to its standard counterpart. Based on surface roughness and machining force measurement and analysis, this efficiency is proved by quantitative results: the wiper geometry ensures significantly better surface quality, while the energy consumption of the used machine tool is considerably lower.

Mechanical and surface characteristics in laser-assisted machining of NiFeCr alloy: An atomic-scale understanding

This investigation explores mechanical characteristics and subsurface damage of NiFeCr alloy in laser-assisted machining through molecular dynamics simulation. The results of machining force, friction coefficient, local strain/stress, temperature distribution, subsurface damage, surface morphology, and worn volume are comprehensively explored, thereby revealing the mechanism of laser-assisted machining under different working conditions. Compared to conventional processing, average machining force, shear strain, subsurface damage, and dislocated length are all reduced in laser-assisted machining, which improves surface finish quality. Amorphization of removed chips in laser-assisted machining enhances the material removal efficiency. Analysis of various laser powers shows a decreased machining force with increasing laser power. However, residual stress and temperature rise, potentially impacting surface integrity. The subsurface damage depth exhibits nonlinearity with increasing laser energy, highlighting the competition between mechanical stress and thermal effect. The surface morphology and atomic flow demonstrate effective material removal with increasing laser power. The average machining force, friction coefficient, and subsurface damage depth show nonlinear relationships with cutting speed. The number of worn atoms is proportional to machining length and cutting speed, indicating enhanced material removal during high-speed machining.

A Novel Discrete EMN for Electromagnetic Force and Vibration Computation of SPM Machine Considering Carrier Harmonics

A Novel Discrete EMN for Electromagnetic Force and Vibration Computation of SPM Machine Considering Carrier Harmonics

The Impact of nanoparticles (B4C-Al2O3) on mechanical, wear, fracture behavior and machining properties of formwork grade Al7075 composites

This study explores how ageing temperature and the volume percentage of Al2O3+B4C nanoparticles influence the machinability and hardness of stir-cast Al-7075 Metal Matrix Composite (MMC). Using liquid metallurgy techniques, hybrid materials were created by reinforcing Al7075 metal matrix with varying weight percentages of nanosized B4C (1.5%, 3%, and 4.5%) and Al2O3 (1%, 1.5%, and 2%). After fabrication, the samples were subjected to five-hour ageing process at temperatures of 100, 120, and 140 degrees Celsius, followed by cooling to ambient temperature (27 degrees Celsius). Hybrid nano composites that had been heat treated were tested for wear, tensile strength, and hardness. Results shows that, the addition of nanoparticles and heat treatment considerably improves the tensile strength, hardness, and wear resistance of hybrid composites by 3%, 17%, and 10%, respectively, for samples reinforced with 4.5% B4C + 2% Al2O3. SEM analysis was used to investigate the type of wear and the tensile fracture mode of nano composite samples by analyzing the wornout surface and the surface where tensile fracture occurred. Machinability was assessed using L27 orthogonal array tests, focusing on three key process parameters: feed rate (0.1 mm/min), depth of cut (0.2 mm/min), and spindle speed (1000 rpm). Outcomes show that, increasing the wt. % of nano-Al2O3/B4C leads to higher machining force and surface roughness (Ra) of MMCs. Conversely, higher ageing temperatures result in decreased machining force and surface roughness. Optimal surface roughness and machining force were achieved with 1% Al2O3 + 1.5% B4C and an ageing temperature of 140°C. These findings offer valuable insights into the ease of machining of composite metal alloys, emphasizing the importance of parameter selection and optimization for desired machining outcomes.

Packaging machine vibration reduction by dynamic balancing

In this article vibrations transmitted to the frame of a packaging machine are reduced through dynamic balancing. It is known that unbalanced inertial forces and moments result in undesirable vibrations that negatively affect the performance and durability of machines. These shaking forces and shaking moments must be completely balanced to eliminate the vibrations. Balancing generally increases other dynamic characteristics like driving torque, bearing reactions in joints and the overall mass of the mechanism and can lead to a more complex mechanism. Instead of a complete balance of shaking force and moment, these can be minimized through optimization techniques. In this work, an optimization procedure is formulated to determine the masses and locations of counterweights that provides the minimum shaking force and moment of a packaging machine sealing head, thus reducing the vibrations transferred to the frame.

Influence of spatial engagement angles on machining forces and surface roughness in turning of unidirectional CFRP

Carbon fibre-reinforced polymer (CFRP) is being widely used due to its low specific weight and outstanding mechanical properties. However, using identical machining parameters on unidirectional CFRP can lead to different results depending on the fibre orientation.Recently, a process-independent model describing the engagement conditions in oblique cutting of unidirectional CFRP has been developed, introducing the spatial angles θ0 and φ0. Since the engagement conditions of milling and drilling are complex, analogy experiments are conducted in turning with variation of the setting κrand inclination angles λs. In this study, process forces and surface roughness were measured as a function of the complete range of fibre cutting angle θ.

Tool wear monitoring based on scSE-ResNet-50-TSCNN model integrating machine vision and force signals

In the realm of mechanical machining, tool wear is an unavoidable phenomenon. Monitoring the condition of tool wear is crucial for enhancing machining quality and advancing automation in the manufacturing process. This paper investigates an innovative approach to tool wear monitoring that integrates machine vision with force signal analysis. It relies on a deep residual two-stream convolutional model optimized with the scSE (concurrent spatial and channel squeeze and excitation) attention mechanism (scSE-ResNet-50-TSCNN). The force signals are converted into the corresponding wavelet scale images following wavelet threshold denoising and continuous wavelet transform. Concurrently, the images undergo processing using contrast limited adaptive histogram equalization and the structural similarity index method, allowing for the selection of the most suitable image inputs. The processed data are subsequently input into the developed scSE-ResNet-50-TSCNN model for precise identification of the tool wear state. To validate the model, the paper employed X850 carbon fibre reinforced polymer and Ti–6Al–4V titanium alloy as laminated experimental materials, conducting a series of tool wear tests while collecting pertinent machining data. The experimental results underscore the model’s effectiveness, achieving an impressive recognition accuracy of 93.86%. When compared with alternative models, the proposed approach surpasses them in performance on the identical dataset, showcasing its efficient monitoring capabilities in contrast to single-stream networks or unoptimized networks. Consequently, it excels in monitoring tool wear status and promots crucial technical support for enhancing machining quality control and advancing the field of intelligent manufacturing.