Machining Forces Research Articles

Influence of V concentration in TiAlSiVN coating on self-lubrication, friction and tool wear during two-pass dry turning of austenitic steel 316 L

The present work investigates the performance of TiAlSiVN coating with 5 and 11 at% of V concentration deposited on the Al2O3/SiC cutting tools during dry turning of austenitic 316 L stainless steel. The maximum flank wear reduction compared to the uncoated tool for coated tools with 11% and 5% V concentration was 85% and 67%, respectively. The Raman analysis indicated the formation of V2O5 in the cutting zone, which helps to reduce friction and machining forces for the coated tools. Overall, the presence of higher V content (11 at%) enhances the self-lubrication behaviour of the TiAlSiVN coating, accounting to lower fluctuations in cutting forces, superior surface finish, and lower flank wear when compared to the TiAlSiV5N coated and uncoated cutting tools.

Magnetomotive Forces of Slotless Electrical Machines with Fractional Windings and Number of Coils per Pole and Phase q < 1

Magnetomotive Forces of Slotless Electrical Machines with Fractional Windings and Number of Coils per Pole and Phase q < 1

Analytical calculation of magnetic field in surface-mounted permanent-magnet vernier motors

This paper proposes an analytical method to calculate the on-load magnetic field, Back electromotive force (BEMF) and torque of the surface-mounted permanent-magnet vernier machine (SMPMVM) accounting for slots, tooth-tips, flux modulation pole slots (FMPS) and the shape of magnet. The on-load magnetic field is predicted according to the surface-current method of permanent magnet, subdomain model and the superposition principle. BEMF and torque are calculated based on the magnetic field. The results show that THD of open-circuit and on-load radial flux density in the SMPMVM with concentric magnet poles is smaller than that in the conventional SMPMVM with eccentric magnet poles. 30th and 50th harmonic orders are obvious between two motors. Moreover, the peak cogging torque of the motor with concentric magnet poles is almost six times of the peak cogging torque of motor with eccentric magnet poles. The finite-element and experimental results confirm that the developed analytical method has high accuracy for predicting the magnetic field, BEMF, cogging torque and on-load electro-magnetic torque of SMPMVM with different shape of magnet.

Molecular Gas-Phase Conformational Ensembles.

Accurately determining the global minima of a molecular structure is important in diverse scientific fields, including drug design, materials science, and chemical synthesis. Conformational search engines serve as valuable tools for exploring the extensive conformational space of molecules and for identifying energetically favorable conformations. In this study, we present a comparison of Auto3D, CREST, Balloon, and ETKDG (from RDKit), which are freely available conformational search engines, to evaluate their effectiveness in locating global minima. These engines employ distinct methodologies, including machine learning (ML) potential-based, semiempirical, and force field-based approaches. To validate these methods, we propose the use of collisional cross-section (CCS) values obtained from ion mobility-mass spectrometry studies. We hypothesize that experimental gas-phase CCS values can provide experimental evidence that we likely have the global minimum for a given molecule. To facilitate this effort, we used our gas-phase conformation library (GPCL) which currently consists of the full ensembles of 20 small molecules and can be used by the community to validate any conformational search engine. Further members of the GPCL can be readily created for any molecule of interest using our standard workflow used to compute CCS values, expanding the ability of the GPCL in validation exercises. These innovative validation techniques enhance our understanding of the conformational landscape and provide valuable insights into the performance of conformational generation engines. Our findings shed light on the strengths and limitations of each search engine, enabling informed decisions for their utilization in various scientific fields, where accurate molecular structure determination is crucial for understanding biological activity and designing targeted interventions. By facilitating the identification of reliable conformations, this study significantly contributes to enhancing the efficiency and accuracy of molecular structure determination, with particular focus on metabolite structure elucidation. The findings of this research also provide valuable insights for developing effective workflows for predicting the structures of unknown compounds with high precision.

On the surface integrity of machined aero-engine grade Ni-based superalloy billets produced by the field-assisted sintering technology (FAST) route

High performance powder-based Ni-based superalloys exhibit exceptional in-service properties at elevated temperature, however this leads to reduced machinability and the potential for significant machining induced damage. Field assisted sintering technology (FAST) is capable of consolidating powder rapidly and efficiently, allowing for precise control of the microstructure via the dissolution of strengthening phases. In this study, subsolvus and supersolvus dwell temperatures were utilised to produce fine and coarse grain forms of an advanced Ni-based disk alloy. Surface integrity and machining forces were then evaluated after single point turning for a range of surface speeds. Higher cutting forces and lower depths of subsurface damage were generated when machining the fine grain (subsolvus) material when compared to the coarser grained (supersolvus) material. For both material conditions tested, higher surface speeds led to a reduced depth of subsurface deformation due to increased local temperatures, promoting workpiece softening. In addition, at higher cutting speeds the deformation of near surface γ’ precipitates were observed to be greater. These results demonstrate that the FAST process can be utilised to control microstructure, and as a result, tailor the machinability of Ni-based superalloy material.

Analysis of Surface Roughness, Cutting Force and Cutting Fluid Consumption in Turning Operation with and Without Use of Cutting Fluid Optimizer

In the present work, cutting fluid consumption, surface roughness, component of forces and tool temperature were analyzed with and without online regulation cutting fluid. Cutting Fluid Optimizer (CFO) is a device that automatically regulates the supply of cutting fluid based on the temperature of the tool tip generated during the machining. Taguchi orthogonal L9 is employed for design of experiments using MINITAB-21. Every experiment was conducted on mild steel work material with use of a tungsten carbide tool insert on the conventional lathe. The best parameter is determined via grey relational analysis. Optimal condition of regulation of coolant with the Cutting Fluid Optimizer (CFO) and non-regulation of coolant with the cutting fluid optimizer are compared. Minimum surface roughness, machining forces, tool–work piece temperature was recorded in case of non-regulation of cutting fluid with the CFO at the cost of the consuming large amount cutting fluid. However, regulation of cutting fluid with the CFO was able to reduce coolant consumption by 15.3% but significantly resulting 3.3 % increase in component of forces, surface roughness and tool-work piece temperature.

Rapid acquisition of digital fingerprints of Ti-6Al-4V macrotexture from machining force measurement data

Titanium alloys display anisotropic deformation properties due to the hexagonal close-packed (hcp) crystal structure of the α-phase. When subjected to localised deformation during machining, this behaviour influences fluctuations in the cutting force response of the material as the tool encounters grains of different orientations. In this research, cutting force signals acquired during face turning of Ti–6Al–4V possessing a lamellar α colony structure have been spatially mapped demonstrating the ability to identify microstructural features such as prior-β grain boundaries, grain boundary α, and α colonies. Measured cutting forces have been correlated to texture using orientation information acquired from large area EBSD analysis. A relationship between the misalignment of the crystallographic a slip vector with respect to the cutting direction and the passive cutting force response has been established, demonstrating a rise in cutting forces as this misalignment is increased. This novel approach to in-process materials evaluation offers manufacturers the potential of a powerful digital quality assurance tool, with the results presented here demonstrating the possibility for rapid characterisation of entire component surfaces, revealing microstructural features, and inferring the crystallographic orientation of macrotextured regions in Ti–6Al–4V.

Effect of Microstructure on the Machinability of Natural Fiber Reinforced Plastic Composites: A Novel Explainable Machine Learning (XML) Approach

Abstract Natural fiber-reinforced plastic (NFRP) composites are ecofriendly and biodegradable materials that offer tremendous ecological advantages while preserving unique structures and properties. Studies on using these natural fibers as alternatives to conventional synthetic fibers in fiber-reinforced materials have opened up possibilities for industrial applications, especially for sustainable manufacturing. However, critical issues reside in the machinability of such materials because of their multiscale structure and the randomness of the reinforcing elements distributed within the matrix basis. This paper reports a comprehensive investigation of the effect of microstructure heterogeneity on the resultant behaviors of cutting forces for NFRP machining. A convolutional neural network (CNN) links the microstructural reinforcing fibers and their impacts on changing the cutting forces (with an estimated R-squared value over 90%). Next, a model-agnostic explainable machine learning approach is implemented to decipher this CNN black-box model by discovering the underlying mechanisms of relating the reinforcing elements/fibers’ microstructures. The presented xml approach extracts physical descriptors from the in-process monitoring microscopic images and finds the causality of the fibrous structures’ heterogeneity to the resultant machining forces. The results suggest that, for the heterogeneous fibers, the tightly and evenly bounded fiber elements (i.e., with lower aspect ratio, lower eccentricity, and higher compactness) strengthen the material and thereafter play a significant role in increasing the cutting forces during NFRP machining. Therefore, the presented framework of the explainable machine learning approach opens an opportunity to discover the causality of material microstructures on the resultant process dynamics and accurately predict the cutting behaviors during material removal processes.

Performance assessment of vegetable-based additive enriched cutting fluid for eco-friendly machining environment.

The investigation focuses on determining the effects of canola oil-based cutting fluid with three different volume percentages of boric acid additives over the machining forces and surface roughness while turning hardened AISI 1018 mild steel. Experiments were carried out under Taguchi's design of the experiment concept. The minimum quantity lubrication (MQL) technique was followed to minimize the cutting fluid consumption. The homogeneity of the additives dispersed in the fluid has been validated through a zeta potential study. Machining forces and surface roughness were considered as chief machining objectives. The hybrid mathematical model, grey relational analysis (GRA)-artificial neural network (ANN), has been implemented to assess the performance of developed cutting fluid. The results explored that the canola oil cutting fluid with 5 wt% of boric acid additive exhibits lesser cutting forces and surface roughness. The optimal machining parameters identified by the hybrid modeling are 665rpm of cutting speed, 35mm/min of feed rate, and 0.3mm of depth of cut, along with 5 wt% of boric acid composition in cutting fluid. The results explore the 2.677 times improvement in machining objective in comparison with a non-optimal set of parameters. The implementation of hybrid modeling is considered to be a novel attempt to minimize the machining objectives. It has been recorded a negligible error percentage of 0.66% between GRA and ANN prediction.

CAN FORCE MEASUREMENTS TAKEN BY A STRAIN GAUGE ACT AS AN INDICATION OF BONE HEALING IN CIRCULAR EXTERNAL FIXATION FRAMES? A LABORATORY AND CLINICAL PILOT

AbstractOBJECTIVESTo determine if force measured using a strain gauge in circular external fixation frames is different for 1) different simulated stages of bone healing, and for 2) fractures clinically deemed either united or un-united.METHODSIn a laboratory study, 3 similar Ilizarov frame constructs were assembled using a Perspex bone analogue. Constructs were tested in 10 different clinical situations simulating different stages of bone healing including with the bone analogue intact, with 1,3 and 50mm gaps, and with 6 materials of varying stiffness's within the 50mm gap. A Bluetooth strain gauge was inserted across the simulated fracture focus, replacing one of the 4 threaded rods used to construct the frame. Constructs were loaded to 700N using an Instron testing machine and maximum force during loading was measured by the strain gauge. Testing was repeated with the strain gauge replacing each of the 4 threaded rods in turn, with measurements being repeated 3 times, across all 3 frame constructs for all 10 simulated clinical situations (n=360). Force measurements between the situations were compared using a Kruskal-Wallis test (KW) and a post-hoc Steel test was used for multiple comparison against control (intact bone model). Additionally, a pilot study has been initiated to assess clinical efficacy of the strain gauge measurement in patients with circular frames. The strain gauge replaced the anterior rod across the fracture focus for each patient. Patients were asked to step on a weighing scale with their affected limb, and maximum weight transfer through the limb and maximal force measured in the frame were recorded. This was repeated 3 times and a mean ratio of force to weight through affected limb was calculated for each patient. The clinical situation at each measurement was designated as united or un-united by one of the senior authors for analysis. Force measurements between the situations were compared using a Wilcoxon-Mann-Whitney test.RESULTSIn the laboratory study, including all constructs with the strain gauge in all positions, a statistically significant relationship between model stability and force measured was identified (KW test for overall relationship p<0.0001). The largest force was measured in the model with a 50mm gap (median 170N, IQR 155–192, range 83–213) and the smallest in the intact bone model (median 3N, IQR 1–8, range 0–11). Multiple comparison testing found a significant difference between intact bone and all the unstable situations (p=0.002 or better). Examining initial results from our pilot clinical study, nine measurements were available in seven patients. Three of these were taken in patients with fractures yet to unite, six in patients where union has since been confirmed clinically. The median force measured was significantly greater where the fracture was not united (median 1.66 N/kg, range 1.07–1.99 vs 0.12 N/kg, range 0.05–0.73, p=0.02).CONCLUSIONSThis laboratory study demonstrates that force measurement may be different at different stages of healing, and although only limited data was available, a pilot clinical study showed a significant relationship between the force measured and clinical union of the patient's fracture.Declaration of Interest(b) declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported:I declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research project.

Understanding tool chip interaction through experimental and numerical analysis during vibration assisted turning of AISI D3 steel

Vibration Assisted Turning (VAT) is a hybrid machining process where the material is machined with the help of a tool vibrating at ultrasonic frequency. VAT results in significant changes in process characteristics compared to conventional machining, like reducing the machining forces and tool wear. The chips produced during the machining operation can provide valuable insight into the process characteristics like machining zone temperature, friction at the tool-chip interface and chip load that primarily alter the process performance. One can understand and have a better control on the machining process performance by studying the formation of these chips and the tool-chip interaction. The work presents an experimental and numerical study to analyze the chip formation during VAT while machining AISI D3 steel. The chips formed while machining at different vibration amplitudes were observed to be of different colors, widths, and thicknesses. These were found to correlate to the forces generated and the surface integrity produced. A decrease in the chip width and thickness was observed with an increase in the amplitude that helps to reduce the chip load and hence forces. Also, the temperature at the machining zone increased with an increase in amplitude as seen from different color of chips produced and carbon content of the chip. The numerical model, developed to analyze the effect of the vibration amplitude on the contact pressure at the chip-tool interface, showed that the average contact pressure reduced upon applying ultrasonic vibration to the tool, thereby reducing the coefficient of friction and frictional forces. Also, with increase in vibration amplitude, the coefficient of friction was found increasing but it still remained lower than that in conventional turning. The study would help to understand the reduction the overall machining forces and chip morphology and thereby to have a better control on the process performance.

Influence of Magnet Field Harmonics on Radial Force of Fractional-Slot PM Machines Considering Slot/Pole Combinations

Influence of Magnet Field Harmonics on Radial Force of Fractional-Slot PM Machines Considering Slot/Pole Combinations

Surface Roughness Prediction in Ultra-Precision Milling: An Extreme Learning Machine Method with Data Fusion.

This paper pioneers the use of the extreme learning machine (ELM) approach for surface roughness prediction in ultra-precision milling, leveraging the excellent fitting ability with small datasets and the fast learning speed of the extreme learning machine method. By providing abundant machining information, the machining parameters and force signal data are fused on the feature level to further improve ELM prediction accuracy. An ultra-precision milling experiment was designed and conducted to verify our proposed data-fusion-based ELM method. The results show that the ELM with data fusion outperforms other state-of-art methods in surface roughness prediction. It achieves an impressively low mean absolute percentage error of 1.6% while requiring a mere 18 s for model training.

Accurate prediction method for a microstructure profile based on the force–displacement coupled servo model

Microstructures of specified shapes have been widely applied in electronics, communication, optics, avionics, medical science, and the automotive field. The ultraprecision single-point diamond turning lathe is a core instrument used in microstructure preparation. As a key technical indicator of an ultraprecision lathe, the servo control accuracy of a system directly affects the machining accuracy of the lathe. Because the profile error of microstructures machined by the slow tool servo of the ultraprecision lathe is at the micrometer level, any disturbance reduces the accuracy of parts machining. This paper proposes a tracking error prediction model based on the force–displacement coupled servo model to study the mechanism of action for the cutting force disturbance on a servo control system. The repeated positioning error of an ultraprecision lathe’s linear axis is added to the force–displacement coupled servo model to propose a more practical profile error prediction model and analyze the effect of the cutting force on the part profile. The experimental results indicate that the force–displacement coupled servo tracking error and profile error prediction model proposed in this paper is more accurate than the existing tracking error modeling method without cutting force disturbance. In addition, this paper analyzes how the cutting force in ultraprecision machining affects the servo system and part profile, which provides a reference for subsequent ultraprecision lathe error analysis and improved machining accuracy.

Comparison Study On Pinch-Hitting Vibration Signal Analysis for Automotive Bearing: I-KazTM and I-Kaz 3D

Rotating machines are now an essential part of the automotive industry. Meanwhile, a bearing is playing the most important component of rotating machinery. To sustain the system's smooth running, maintenance methods such as preventive maintenance, breakdown maintenance, and predictive maintenance are used. Under preventive maintenance, vibration analysis is used to diagnose machines bearing faults. The main objective is to recognize bearing defects in a mechanical device by acquiring signals from the bearing using data acquisition hardware. This analysis is conducted under various load torque conditions, speeds, and defect types. A modular hardware configuration consisting of an accelerometer acquires the vibration signal. The signals are analyzed by using I-kazTM and I-kaz 3D signal analysis and its main objective is to observe the degree of dispersion data from its mean point. This analysis resolves the issues associated with time domain analysis. This pinch-hitting analysis research was conducted in two stages. The first stage is an experimental process that uses 3 types of bearings, the healthy (BL), inner race fault (IRF), and defect at outer race (ORF) bearing on the Machine Fault Simulator and forces with a different type of speed (1000, 1500 and 2500 rpm) and load variation (0.0564, 0.564 and 1.1298 N-m). In the second stage, computing the coefficient value and plots of signal’s I-kazTM and I-kaz 3D based on the bearings type were done accordingly. As a result, the analysis for detecting inner race fault, the deviation percentage averages calculation obtained the I-kazTM coefficient shows a better result with 96.86% by comparing to the I-kaz 3D that achieves 94.20%. Similarly, for the outer race defect, I-kazTM lead with 65.40% compared to I-kaz 3D with only 54.82%.

Compensating varying size effect in diamond cutting of SiCp/Al by ultrasonic elliptical vibration

The heterogeneous mechanical properties of individual phases in SiCp/Al result in significant varying size effect (SE) existed in its deformation process. And modulating the varying SE is crucial for improving the machined surface finish of SiCp/Al in mechanical machining. In this study, we elucidate the mechanisms governing the varying SE in conventional cutting and ultrasonic elliptical vibration-assisted cutting (UEVC) of SiCp/Al using diamond tools by theoretical analysis, numerical simulations and experiments. Specifically, the impact of cutting tool-workpiece contact states in UEVC on the fundamental cutting behavior of SiCp/Al, in terms of microscopic deformation modes and their correlations with machining force variation, machined surface morphology and chip profile, is evaluated. Subsequently, ultrasonic elliptical vibration-assisted diamond turning of SiCp/Al is performed to achieve a surface roughness of 20 nm accompanied with significantly suppressed tool wear. Finally, the compensation effect on the varying SE in SiCp/Al cutting by ultrasonic elliptical vibration of cutting tool is discovered, which leads to decreased brittle fracture and improved surface integrity. The research findings provide a theoretical support for understanding the machining mechanisms of UEVC of SiCp/Al, as well as proposing new perspectives for improving the machinability of SiCp/Al composite accompanied by suppressed varying SE.

Analytical modeling of cutting force in machining of SiCp/Al composites by ultrasonic elliptical vibration-assisted turning

To predict the cutting force in machining of SiCp/Al composites by ultrasonic elliptical vibration-assisted turning (UEVT) technology, a semi-empirical geometric model considering the deformation and friction characteristics in different deformation areas is established in this paper. During UEVT, the resistance force acting on cutting edge is divided into three parts according to different deformation zones: shear force, interface friction, and plowing force. The vibration characteristic functions are also coupled to the semi-empirical geometric model of cutting force. A three factor and four level orthogonal tests is implemented to verify the validity of geometric model, and the single factor cutting experiments are also conducted to evaluate the influence law of relevant parameter on cutting force. Experimental results show that the deviation between the calculated value of cutting force and measured average value is less than 17%, and the average deviation is 8.16%, which proved that the semi-empirical geometric model can effectively predict the cutting force of SiCp/Al composites during UEVT. In addition, the influence of cutting parameters and volume fraction on cutting force is discussed, which provides a theoretical guidance for the outstanding machinability of SiCp/Al composites in UEVT.

Linear Resonator Actuator-Constructed Wearable Haptic System with the Application of Converting Remote Grinding Force to Vibratory Sensation

This study developed a three-axis vibrational haptic wearable device (RCWS) utilizing Linear Resonant Actuators (LRAs) to simulate grinding vibrations. The implementation of RCWS is described in detail. By recording the normal force during manual grinding with a load cell and converting it into a series of PWM commands, the LRA on the RCWS was controlled in open-loop mode using these PWM commands. Three methods were tested for force-to-PWM conversion, two of which showed a linear correlation (>0.7) with raw data. In the correlation between PWM commands and generated acceleration, all three methods exhibited a high linearity of at least 0.85. This wearable RCWS offers a promising approach for users to experience the machining force from the versatile and critical remote machining process with a finger vibratory sensation.

Experimental investigation of novel internal thread fabrication: A drill thread milling

In this study, a novel method for fabricating internal threads called drill thread milling (DTM) was experimentally investigated. DTM is a fabrication process that combines drilling and thread milling into a single process, thereby eliminating the need for a pilot hole and making it a viable alternative to existing methods. To optimize the DTM process, the characteristics of DTM must first be understood. In this study, the machining characteristics of DTM were examined using a variety of materials and machining parameters. The results were then compared with those obtained using the tapping method. During the experiments, the machining force and vibration were recorded, and the results indicated that DTM required less machining time than did the tapping method. However, DTM exhibited an additional periodic components in the machining force, which could resulted in chatter. In certain materials, a tool offset was required to pass the thread gauge, indicating substantial tool deflection occurred during the machining process. The examination of the resulting threads revealed that, for the same thread depth, DTM required a shallower hole than that required in the tapping method.

Towards an understanding of Ti-6Al-4V machining and machinability

Commercially pure titanium and its alloys play an important role in the applications of numerous technical disciplines, as well as in multidisciplinary domains. Because of its exceptional qualities, titanium and its alloys are currently employed mostly in the automotive, aerospace, and biomedical industries. Titanium and its alloys have challenging machinability because to characteristics such as strong chemical reactivity, hardness, and low heat conductivity. The titanium alloy Ti-6Al-4V is commonly used in aeronautical applications. The machining characteristics of Ti-6Al-4V are described and highlighted in this review study, which focuses on machining forces, chip forms, cutting temperatures, and approaches for cutting improvement, as well as their respective analyses.