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Turning is an important aspect of life underwater, playing integral roles in predator avoidance, prey capture, and communication. While turning abilities have been explored in a diversity of adult nekton, little is currently known about turning in early ontogeny, especially for cephalopods. In this study, we investigated the turning abilities of hatchling common cuttlefish (Sepia officinalis, n = 49) and dwarf cuttlefish (Sepia bandensis, n = 30), using both kinematic and wake-based analyses. Using body tracking software and particle image velocimetry (PIV), we found that S. officinalis turned faster than S. bandensis, but both species completed equally tight turns. Orientation (arms-first or tail-first) did not have a significant effect on turning performance for either species. Cuttlefish hatchlings used multiple short jets for more controlled turning, with jet mode I (isolated vortex rings) being 3–4 times more common than jet mode II (elongated jets with leading ring structures) for both species. While both hatchlings turned more broadly than adult squid and cuttlefish, S. officinalis hatchlings turned faster than adult cuttlefish, and both hatchlings turned more tightly than other jet-propelled animals and some non-jet-propelled swimmers. [ABSTRACT FROM AUTHOR]

Tool wear in machining is inevitable, and determining the precise moment to change the tool is challenging, as the tool transitions from the steady wear phase to the rapid wear phase, where wear accelerates significantly. If the tool is not replaced correctly, it can result in poor machining performance. On the other hand, changing the tool too early can lead to unnecessary downtime and increased tooling costs. This makes it critical to closely monitor tool wear and utilize predictive maintenance strategies, such as tool condition monitoring systems, to optimize tool life and maintain machining efficiency. Acoustic emission (AE) is a widely used technique for indirect monitoring. This study investigated the use of Short-Time Fourier Transform (STFT) for real-time monitoring of tool wear in machining AISI 4340 steel using carbide tools. The research aimed to identify specific wear mechanisms, such as abrasive and adhesive ones, through AE signals, providing deeper insights into the temporal evolution of these phenomena. Machining tests were conducted at various cutting speeds, feed rates, and depths of cut, utilizing uncoated and AlCrN-coated carbide tools. AE signals were acquired and analyzed using STFT to isolate wear-related signals from those associated with material deformation. The results showed that STFT effectively identified key frequencies related to wear, such as abrasive between 200 and 1000 kHz and crack propagation between 350 and 550 kHz, enabling a precise characterization of wear mechanisms. Comparative analysis of uncoated and coated tools revealed that AlCrN coatings reduced tool wear extending tool life, demonstrating superior performance in severe cutting conditions. The findings highlight the potential of STFT as a robust tool for monitoring tool wear in machining operations, offering valuable information to optimize tool maintenance and enhance machining efficiency. [ABSTRACT FROM AUTHOR]

In metal cutting, a large amount of mechanical energy converts into heat, leading to a rapid temperature rise. Excessive heat accelerates tool wear, shortens tool life, and hinders chip breakage. Most existing thermal studies have focused on dry machining, with limited research on the effects of cutting fluids. This study addresses that gap by investigating the thermal behavior of cutting tools during continuous and interrupted turning with cutting fluid. Tool temperatures were first measured experimentally by embedding a thermocouple in a defined position within the tool. These experimental results were then combined with simulations to evaluate temperature changes, heat partition, and cooling efficiency under various cutting conditions. This work presents novel analytical and numerical models. Both models accurately predicted the temperature distribution, with the analytical model offering a computationally more efficient solution for industrial use. Experimental results showed that tool temperature increased with cutting speed, feed, and cutting depth, but the heat partition into the tool decreased. In continuous cutting, cooling efficiency was mainly influenced by feed rate and cutting depth, while cutting speed had minimal impact. Interrupted cutting improved cooling efficiency, as the absence of chips and workpieces during non-cutting phases allowed the cutting fluid to flow over the tool surface at higher speeds. The convective cooling coefficient was determined through inverse calibration. A comparative analysis of the analytical and numerical simulations revealed that the analytical model can underestimate the temperature distribution for complex tool structures, particularly non-orthogonal hexahedral geometries. However, the relative error remained consistent across different cutting conditions, with less error observed in interrupted cutting compared to continuous cutting. These findings highlight the potential of analytical models for optimizing thermal management in metal turning processes. [ABSTRACT FROM AUTHOR]

The publication verifies the theoretical possibilities of reducing production costs and production time for machine clamping jaws. The primary idea involves maintaining the design for conventional production while replacing the steel alloy 1.7225 with the ONYX plastic composite material reinforced with carbon fiber. The study was first verified computationally and then experimentally in industrial operations. The results of the study were recorded and carefully analyzed. The usability of the ONYX composite, in conjunction with carbon fiber, does not support its use in industrial operations. Although the rotary system was significantly lighter, the clamping elements exhibited relatively high elasticity values. Therefore, the results were unsatisfactory but highly beneficial for the practice and usability of plastic composites. [ABSTRACT FROM AUTHOR]

We proposed a deep learning method using a convolutional neural network on time-series (TS) images to detect and differentiate affected body parts in people with Parkinson's disease (PD) and freezing of gait (FOG) during 360° turning tasks. The 360° turning task was performed by 90 participants (60 people with PD [30 freezers and 30 nonfreezers] and 30 age-matched older adults (controls) at their preferred speed. The position and acceleration underwent preprocessing. The analysis was expanded from temporal to visual data using TS imaging methods. According to the PD vs. controls classification, the right lower third of the lateral shank (RTIB) on the least affected side (LAS) and the right calcaneus (RHEE) on the LAS were the most relevant body segments in the position and acceleration TS images. The RHEE marker exhibited the highest accuracy in the acceleration TS images. The identified markers for the classification of freezers vs. nonfreezers vs. controls were the left lateral humeral epicondyle (LELB) on the more affected side and the left posterior superior iliac spine (LPSI). The LPSI marker in the acceleration TS images displayed the highest accuracy. This approach could be a useful supplementary tool for determining PD severity and FOG. [ABSTRACT FROM AUTHOR]

Most metal turning processes utilize cutting fluids. Despite extensive experimental and analytical studies, the mechanisms of chip formation under consideration of a cutting fluid are still not entirely understood. Due to fluid-structure interaction, simulating wet cutting processes for an extended duration has not been feasible. The primary objective of this study is to utilize a simulation approach to provide additional information about the wet chip formation process in contrast to measurement methods, with a view to drawing conclusions. As methodology the Finite-Pointset-Method (FPM) is employed to simulate the chip formation process for dry, flood and specifically high-pressure cooling conditions during machining of carbon steel C45 as well as nickel-based alloy Inconel 718. Due to the increased relative velocity between workpiece and cutting fluid with the use of high-pressure cooling compared to flood cooling, numerical stability issues are present. Initially, the modeling approach to handle high-pressure cooling conditions is described and validated by an impact test. Subsequently the cutting simulation model is presented in detail and verified by measurements. The simulation results of stress, temperature and plastic strain rate fields are used to elucidate the observed discrepancies between various cutting fluid strategies in detail. These findings suggest explanations for the high efficiency of high-pressure cooling such as a decline of hydrostatic stresses or activation of ductile damaging. [ABSTRACT FROM AUTHOR]

This work investigates the characterization of a cryo-processed AlTiN-coated tool and its turning characteristics for Inconel 600. The microhardness was enhanced by 3.68% under cryo-treatment when compared with the as-received condition of the inserts because of the wear-protective coating formed on the surfaces of the cutting tool. This was confirmed through EDS elemental analysis of carbon element growth and change in chemical composition, as well as XRD phase analysis. Next, this work studied the influence of cryo-treated inserts on roughness and mechanism of wear during turning Inconel 600 using varying cutting velocities (37, 60, and 100 m/min) under dry conditions. The output responses revealed that the use of cryo-treated tools reduced the roughness of the product by 11–27% and the rate of tool wear when compared with the untreated conditions. Due to these enhanced properties with cryo-treated conditions, it remains a suitable cutting tool for a significant contribution to sustainable machining toward dry cutting of aerospace alloys. [ABSTRACT FROM AUTHOR]

This study was more focused upon the determination of most influencing input parameter for desirable or undesirable output, apart from it the main aim was selection of optimal parameters for improved surface finish and high productivity. The approach used for the optimization of the process capabilities for oil & Gas components machining will be described. These components are machined by turning of stainless steel castings work pieces. For this purpose, a proper Design of Experiments (DOE) plan has been designed and executed: as output of the experimentation, data about tool wear have been collected. The DOE has been designed starting from the cutting speed and feed values recommended by the tools manufacturer; the depth of cut parameter has been maintained as a constant. Wear data has been obtained by means the observation of the tool flank wear under an optical microscope: the data acquisition has been carried out at regular intervals of working times. The optimization approach used is a multi-objective optimization, which minimizes the production time and the number of cutting tools used, under the constraint on a defined flank wear level. [ABSTRACT FROM AUTHOR]

The performance of the final part of the turning process, a topic of practical importance, heavily depends on the cutting parameters. Surface quality, a crucial product attribute in manufacturing, often tops consumer demands during machining due to its significant influence on product functionality. This paper assesses the correlation between the detected vibration signal, statistical parameters (Crest, Kurtosis and I-kaz3D coefficient) and surface roughness and provides valuable insights for practical applications. When the tool experiences vibrations during material removal, these oscillations leave a ripple effect on the surface of the workpiece. We aim to determine the impact of cutting parameters on surface roughness while turning 42CrMo4 steel using a carbide tool insert. Cutting parameters, such as spindle speed, feed, and depth of cut, were used. Signal processing is carried out using different techniques to identify the effect of the cutting parameters on vibration signals. Finally, we delve into the interaction effects between the cutting parameters, vibration signals and surface roughness, offering a comprehensive understanding of real-world manufacturing scenarios. Higher I-kaz3D coefficients correspond to higher surface roughness values. The I-kaz3D coefficient decreases as the surface roughness measurements decrease, indicating that the I-kaz3D technique can accurately indicate an increase or decrease in surface roughness. On the other hand, the cutting force Fc was the component most strongly correlated with surface roughness (Ra), yielding the best results across all indices (adjusted R²adj = 95.1%, er=.8 ± 2.3%). [ABSTRACT FROM AUTHOR]

The work deals with the influence of the reach of the applied tool holder on the edge wear, dimensional accuracy and surface quality defined by the topography as well as the roughness of the machined surface. The research has been conducted on specimens made of Inconel 718 in the configuration of sleeves, within the scope of finish turning with constant cutting parameters, vc = 85 m/min; f = 0.14 mm/rev; ap = 0.2 mm. The material under machining has undergone heat treatment procedures such as solution treatment and precipitation hardening, resulting in a hardness of 45 ± 2 HRC. Two kinds of turning holders have been used with the reaches of 120 mm and 700 mm. The tools are intended for turning external and internal surfaces, respectively. The tests have been conducted using V-shaped cutting inserts manufactured by different producers, made of fine-grained carbide with coatings applied by the PVD (Physical Vapour Deposition) and CVD (Chemical Vapour Deposition) methods. The edge wear has been evaluated. The value of the achieved diameter dimensions has also been assessed in relation to the set ones, as well as the recorded values of surface roughness and the surface topography parameters have also been assessed. It has been determined that the quality of the manufactured surface evaluated by the 2D and 3D roughness parameters, as well as the dimensional quality are influenced by the kind of the applied tool holder. The influence is also visible considering the edge wear. The smallest values of the deviations from the nominal dimensions have been obtained for the coated inserts of the range of higher abrasion resistance (taking into account information from the producers). The obtained results show that in predicting the dimensional accuracy in the process of turning Inconel 718 alloy with long-overhang tools, one should consider the necessity of correction of the tool path. Taking into account the achieved surface roughness, it should be pointed out that not only the kind of the tool coating but also the character of its wear has a great influence, particularly, when a long cutting distance is required. [ABSTRACT FROM AUTHOR]

This research studied the effect of rice husk ash (RHA) during the turning of AlSi10Mg aluminum alloy. Stir casting was the chosen fabrication technique for this investigation. The combined effects of the following turning process parameters including cutting speed (s), feed (f), depth of cut (d), and weight fraction of reinforcement ( w t ) on the responses; that is the tool wear and surface roughness were studied. Taguchi L 16 orthogonal array was adopted to determine the experimental runs. The analysis of variance (ANOVA) for the tool wear and the surface roughness showed that the feed and the cutting speed were the most significant factors influencing the tool wear and surface roughness, respectively. Using single objective optimization also affirmed the feed and cutting speed as the most influencing parameters for the tool wear and surface roughness, respectively. The predicted model for tool wear and surface roughness obtained from the regression equation shows a good correlation with the experimental results. A correlation of 95% and 94% of tool wear and surface roughness was determined between the predicted and corresponding experimental results. [ABSTRACT FROM AUTHOR]

The main objective of this study is to analyze how input parameters such as cutting speed (Vc), depth of cut (ap), feed per revolution (f), and tool nose radius (r) influence the performance of dry turning AISI 304 stainless steel. Performance evaluation includes cutting force components (Fx, Fy, and Fz), surface roughness (SR), material removal rate (MRR), cutting power (Cp), and cutting temperature (T). Experiments are planned using the Taguchi L18 experimental design, and a coated carbide tool (GC 2025) is employed. ANOVA revealed that the most influential factors on SR are f and r, contributing 52.40% and 26.54%, respectively. Axial and tangential cutting force components are influenced by ap and f, with contributions of 72.99% and 5.93% for Fx and 81.57% and 13.38% for Fz, respectively. The radial component is influenced by ap (85.74%). Vc, f, and ap all contribute to cutting power, with contributions of 55.13%, 24.35%, and 10.74%, respectively. Finally, ap and the interaction f*ap contribute 45.18% and 8.81%, respectively, to the temperature in the cutting zone. This article introduces a novel multi-objective optimization method based on weighted principal component analysis. This method distinguishes itself by its ability to address challenges related to data matrix normalization, the ambiguity of eigenvector signs, and the issue of negative signs in Taguchi's philosophy. The results of the new method, the desirability function, and the classical WPCA method are compared. The results show that the new method suggests a compromise solution that is similar to the desirability function and better than the classical WPCA's suggestion. [ABSTRACT FROM AUTHOR]

Background/Objectives: Hip mobility and joint loading in hip osteoarthritis (HOA) patients are mostly assessed during straight walking. Yet, mobility limitations in the frontal and transverse planes are rarely found during this task in subjects with mild-to-moderate symptoms. Turning movements are frequently encountered during everyday life and might require larger hip mobility compared to straight walking, especially in the frontal and transverse planes. Thus, hip mobility and hip loading during straight walking and 90° turns in persons with HOA and healthy older adults were compared in this study. Methods: A retrospective analysis was conducted on 21 subjects with mild-to-moderate HOA and 21 healthy controls. Hip angles and moments were assessed during straight walking and 90° step and spin turns. Gait analysis was conducted using a motion capture system and a force plate. Group and movement task differences were assessed with a mixed-model ANOVA. Results: Peak abduction and adduction angles were largest during the step and spin turn, respectively, as were the group differences between HOA subjects and healthy subjects. Both turns require a greater transverse hip range of motion compared to straight walking. Limitations in transverse hip mobility in the HOA group were especially prominent during the step turn. Both turns cause higher joint moments than straight walking. Conclusions: The additional inclusion of 90° step and spin turns into gait analysis can enhance early identification of hip mobility limitations in the frontal and transverse planes in subjects with mild-to-moderate hip osteoarthritis. Early diagnosis is crucial for the timely application of conservative treatment strategies. [ABSTRACT FROM AUTHOR]

Purpose: Knee adduction, flexion moment, and adduction angle are often used as surrogate parameters of knee medial force. To verify whether these parameters are suitable as surrogates under different walking states, we investigated the correlation between knee medial loading with the surrogates during walking and turning. Methods: Sixteen healthy subjects were recruited to complete straight walk (SW), step turn (ST), and crossover turn (CT). Knee joint moments were obtained using inverse dynamics, and knee medial force was computed using a previously validated musculoskeletal model, Freebody. Linear regression was used to predict the peak of knee medial force with the peaks of the surrogate parameters and walking speed. Results: There was no significant difference in walking speed among these three tasks. The peak knee adduction moment (pKAM) was a significant predictor of the peak knee medial force (pKMF) for SW, ST, and CT (p < 0.001), while the peak knee flexion moment (pKFM) was only a significant predictor of the pKMF for SW (p = 0.034). The statistical analysis showed that the pKMF increased, while the pKFM and the peak knee adduction angle (pKAA) decreased significantly during CT compared to those of SW and ST (p < 0.001). The correlation analysis indicated that the knee parameters during SW and ST were quite similar. Conclusions: This study investigated the relationship between knee medial force and some surrogate parameters during walking and turning. KAM was still the best surrogate parameter for SW, ST, and CT. It is necessary to consider the type of movement when comparing the surrogate predictors of knee medial force, as the prediction equations differ significantly among movement types. [ABSTRACT FROM AUTHOR]

With the rapid advancement of 3D-printing technology, additive manufacturing using FDM extrusion has emerged as a prominent method in manufacturing. However, it encounters certain limitations, notably in surface quality and dimensional accuracy. Addressing issues related to stability and surface roughness necessitates the integration of 3D-printing technology with traditional machining, a strategy known as the hybrid technique. This paper presents a study of the surface geometric parameters and microstructure of plastic parts produced by FDM. Sleeve-shaped samples were 3D-printed from polyethylene terephthalate glycol material using variable layer heights of 0.1 mm and 0.2 mm and then subjected to the turning process with PVD-coated DCMT11T304 turning inserts using variable cutting parameters. The cutting depth was constant at 0.82 mm. Surface roughness values were correlated with the cutting tool feed rate and the printing layer height applied. The selected specimen's microstructure was studied with a Zeiss EVO MA 15 scanning electron microscope. The roundness was measured with a Keyence VR-6200 3D optical profilometer. The research results confirmed that the additional application of turning, combined with a reduction in the feed rate (0.0506 mm/rev) and the height of the printed layer (0.1 mm), reduced the surface roughness of the sleeve (Ra = 1.94 μm) and increased its geometric accuracy. [ABSTRACT FROM AUTHOR]

Turning difficulties have been reported in stroke persons, but studies have indicated that fall history might not significantly affect turning performance. Fear of falling (FOF) is common after a fall, although it can occur in individuals without a fall history. Could FOF have an impact on turning performance among chronic stroke patients? This cross-sectional study recruited 97 stroke persons. They were instructed to perform 180° and 360° turns, and their performance was represented by angular velocity. FOF was evaluated using the Falls Efficacy Scale-International (FES-I). Falls that occurred 12 months prior to the study assessment were recorded. A higher FES-I score was significantly correlated with a decline in angular velocity in all turning tasks after adjustment for demographic data. The correlation remained significant after controlling for falls history. Participants with a high level of FOF exhibited significantly slower angular velocities during all turning tasks compared with those with a low level of FOF. Participants with a moderate level of FOF had a significantly slower angular velocity than did those with a low level of FOF during the 360° turn to the paretic side only. A higher level of FOF, regardless of fall history, was significantly associated with a reduced angular velocity during turning. A high level of FOF affected turning performance in all tasks. Turning performance may not be affected by fall experience. Anxiety about falling may have a greater effect on turning performance than does fall history. • Fear of falling may have a greater effect than does fall history on turning. • Turning performance may not be affected by fall history. • Assessing fear of falling might be helpful for understanding the motor control during turning. [ABSTRACT FROM AUTHOR]

Super Duplex Stainless Steels (SDSS), in spite of their numerous commercial applications is considered to be extremely difficult to machine owing to its poor thermal conductivity, severe chemical affinity, and work hardening nature. Several studies have analysed the possibility of adopting conventional lubrication/cooling methods and coating techniques to address the machinability-related challenges of the alloy. However, limited studies have explored the use of multi-layered coatings to enhance the tool life properties while machining the alloy. Hence, this work intends to investigate the impact of using CVD TiCN-Al2O3 coated tools to analyse the significance of parameters like speed, feed rate, and depth of cut on the machinability aspects of SDSS 2507 in dry turning conditions. The experimentation analysis revealed that while speed, feed rate, and depth of cut had a significant impact on influencing the tool wear characteristics, surface roughness values were impacted by only feed rate values. Similarly, feed rate, depth of cut, and interaction effects between these factors were noted to have a considerable influence on the cutting forces. Meanwhile, the study also focuses on developing an analytical model to predict the cutting forces that consider the sticking-sliding effects by incorporating the chip groove area across the machining interface. The predicted cutting force values were observed to be in close agreement with the experimental results. The error values were noted to be below 15% in the majority of the cases, which confirms the significance of the predicted model. [ABSTRACT FROM AUTHOR]

The use of metal-based composite materials, especially aluminum composites, has found wide applications in various industries such as automotive, aerospace, military, etc., due to their favorable mechanical properties, high strength-to-weight ratio, and high wear resistance and hardness. On the other hand, these mechanical properties and high hardness and wear resistance, which is due to the presence of reinforcing particles such as silicon carbide in these composites, makes them difficult to machine, so that only special tools and blades, such as polycrystalline diamond tools, can machine these composites optimally. The findings from this study can be valuable in optimizing the turning process of aluminum-based metal matrix composites. In this study, the effects of four input parameters - cutting speed, feed rate, feed force in the X direction, and feed force in the Z direction - on the output parameter of tool wear rate in the dry turning process of A359 aluminum alloy metal matrix composite reinforced with 20 vol.% of silicon carbide particles using polycrystalline diamond tools were investigated. The numerical investigation of the effect of each of the four input parameters on the output parameter was done using the E-fast statistical sensitivity analysis method, which has high speed in quantitative and qualitative data analysis. The results showed that the parameters of feed force in X direction, feed rate, feed force in Z direction, and cutting speed have 88%, 8%, 3%, and 1% effect on tool wear, respectively. [ABSTRACT FROM AUTHOR]

The article is devoted to the development of neural network models of digital counterparts of metal cutting processes on metal-cutting machines of the turning group. The article considers an example of a study of vibration signals removed from a cutting tool. The results of a series of experiments conducted on a 1K625 lathe made it possible to form a sample of eleven informative features, five of which turned out to be enough to form a list of input signals of the projected neural network. The designed neural network, after training using the error back propagation algorithm, allows us to estimate the proximity of the current processing mode to a certain local optimum in terms of cutting speed. [ABSTRACT FROM AUTHOR]

This study describes the cutting performance of Monel 400 alloy using a cryo-treated AlTiN carbide tool. The AlTiN carbide tool was cryo-treated at −196°C for 24 h of soaking at a cooling rate of 0.5°C/min and then tempered at 200°C for 2 h at a heating rate of 0.5°C/min. In this work, we evaluate and compare the hardness, composition, and phases of untreated and cryo-treated AlTiN-coated carbide inserts and also the turning performance of Monel 400 alloy. The machinability characteristics of cutting temperature, turning force, roughness parameter (Ra), form of chip, and SEM-EDS analysis of turned inserts are evaluated and then compared. It was found that the cryo-treated (CT) inserts offered a higher hardness value by 1.5% than the untreated (UT) ones, due to the formation of a new hard surface coating with cryogenic treatment. Cryo-treated AlTiN coated carbide inserts provided the following benefits over untreated ones: lower the cutting temperature at the cutting zone by a maximum of 10%; decreased the cutting force by 6–14%; reduced the Ra values in the turned surface by a maximum of 83%; a reduction in the size of the serrated form of chip; a reduced rate of insert wear; and lower deposition of work material constituents in the turned insert. The reason is enhanced resistance to wear due to an increase in hardness and the formation of a new hard surface coating with cryo-treated AlTiN coated carbide inserts, which was confirmed by analyses of hardness, SEM coupled with EDS, and X-ray diffraction. From the comparison of the characterisation and machinability indices of untreated and cryo-treated AlTiN coated carbide inserts, it was found that the cryo-treated AlTiN-coated carbide inserts provided the favourable turning performance of Monel 400 alloy. [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM) techniques enable new design concepts for performance improvements and functional integration in a wide range of industries. One promising application is in additively manufactured cutting tools for machining, improving process reliability on the one hand and increasing tool life and process productivity on the other hand. Compared to conventional manufacturing processes, AM allows for new and complex geometrical designs, enables the production of individualized parts, and offers new possibilities for alloy composition and material design. This work gives a comprehensive and systematic review of scientific as well as industrial activities, studies, and solutions regarding AM cutting tools and their fields of application. Four different areas are identified, including cooling and coolant supply, damping and vibrational behavior, lightweight design and topology optimization, and functional integration. Thus, the relevant and promising approaches for the industrialization of AM cutting tools are highlighted, and a perspective is given on where further scientific knowledge is needed. [ABSTRACT FROM AUTHOR]

The current work presents an approach for the optimization of machining parameters on the turning of Al7075-T6 aerospace alloy. The alloy was turned on a lathe machine equipped with four different metalworking fluid (MF) setups: minimum quantity lubrication (MQL), Ranque–Hilsch vortex tube (RHVT), compressed air, and dry cutting using coated carbide tools. Taguchi technique was considered for the design of the L16 experimental array with three variable factors and four levels, and S/N ratios were obtained. The turning parameters feed rate and cutting speed are optimized in the experiment, taking into account responses such as surface roughness and tool wear. ANOVA determined the significant parameters that majorly influenced the responses. The results demonstrated that the condition of machining (<99% probability) was the most influential parameter followed by cutting speed (<95% probability) which affects the surface roughness and tool wear. Moreover, turning with MQL at a low cutting speed represented the optimum machining setup for reducing surface roughness and tool wear of this alloy. It was due to the fact that MQL decreases the friction between the tool and the workpiece which reduce the mechanical and thermal stresses on the cutting tool, resulting in lessened tool flank wear and effectively improving the surface quality. [ABSTRACT FROM AUTHOR]

The near-beta titanium alloy Ti5333 with high strength is difficult to cut, and accurate FE simulation models are needed to assess its machinability. This work compares for the practical turning process of the performances of two material plastic models, i.e., the Johnson–Cook model without strain softening and the TANH model with strain softening. To obtain accurate simulation results, the parameters of the JC model are directly determined from the quasi-static/dynamic compression test results, whereas the non-physical meaning parameters of the TANH model are obtained from the machining tests using an inverse method. The comparison results reveal that the TANH model predicts the cutting forces with smaller simulation errors in both the cutting speed and feed directions and gives larger force amplitude variations closer to the experimental variations. In addition, the simulation results from the TANH model generate smaller residual stresses and plastic strains than the JC model as the TANH model gives smaller flow stresses and lower temperatures due to the strain softening effect. The verified FE simulation models can be further used for cutting process optimization of near-beta alloy Ti5333. [ABSTRACT FROM AUTHOR]

Abstract We proposed a deep learning method using a convolutional neural network on time-series (TS) images to detect and differentiate affected body parts in people with Parkinson’s disease (PD) and freezing of gait (FOG) during 360° turning tasks. The 360° turning task was performed by 90 participants (60 people with PD [30 freezers and 30 nonfreezers] and 30 age-matched older adults (controls) at their preferred speed. The position and acceleration underwent preprocessing. The analysis was expanded from temporal to visual data using TS imaging methods. According to the PD vs. controls classification, the right lower third of the lateral shank (RTIB) on the least affected side (LAS) and the right calcaneus (RHEE) on the LAS were the most relevant body segments in the position and acceleration TS images. The RHEE marker exhibited the highest accuracy in the acceleration TS images. The identified markers for the classification of freezers vs. nonfreezers vs. controls were the left lateral humeral epicondyle (LELB) on the more affected side and the left posterior superior iliac spine (LPSI). The LPSI marker in the acceleration TS images displayed the highest accuracy. This approach could be a useful supplementary tool for determining PD severity and FOG.

Abstract The Aluminum alloy AA7075 workpiece material is observed under dry finishing turning operation. This work is an investigation reporting promising potential of deep adaptive learning enhanced artificial intelligence process models for L18 (6133) Taguchi orthogonal array experiments and major cost saving potential in machining process optimization. Six different tool inserts are used as categorical parameter along with three continuous operational parameters i.e., depth of cut, feed rate and cutting speed to study the effect of these parameters on workpiece surface roughness and tool life. The data obtained from special L18 (6133) orthogonal array experimental design in dry finishing turning process is used to train AI models. Multi-layer perceptron based artificial neural networks (MLP-ANNs), support vector machines (SVMs) and decision trees are compared for better understanding ability of low resolution experimental design. The AI models can be used with low resolution experimental design to obtain causal relationships between input and output variables. The best performing operational input ranges are identified for output parameters. AI-response surfaces indicate different tool life behavior for alloy based coated tool inserts and non-alloy based coated tool inserts. The AI-Taguchi hybrid modelling and optimization technique helped in achieving 26% of experimental savings (obtaining causal relation with 26% less number of experiments) compared to conventional Taguchi design combined with two screened factors three levels full factorial experimentation.

In this article, Aluminum (Al2219) as a matrix, and particles of n-B4C and MoS2 were chosen as reinforcements. By means of the stir casting technique, the unhybrid and hybrid nano metal matrix composites were prepared. The turning experiment was done through CCD design of experiment with TiN coated carbide insert using a Computer Numerically Controlled Lathe. Also, for turned inserts tool wear measurement was done using a Mitutoyo profile projector with digital readout. By ANOVA the significant contribution for tool wear of each parameter can be identified and the confirmation test is performed in sort to validate the tool wear results. Furthermore, the formation of chips during turning nano MMCs (unhybrid and hybrid) are studied for different feed rates (f) and cutting speeds (v) at 0.5 mm constant depth of cut. The outcome showed that both increases in cutting speed and feed rate increase the tool wear. For Al 2219, unhybrid and hybrid nano metal matrix composites feed rate is the important factor. The value of tool wear of the Al2219 matrix is minimal and for unhybrid nano composite is maximum. The leading wear mechanism in unhybrid nano composite is abrasion. Moreover, with the addition of 2%MoS2 in the hybrid nanocomposite the tool wears is decreased. The development of Build Up Edge (BUE) was seen on the flank face of the cutting tool for hybrid nanocomposite at 0.5 mm depth of cut, (v = 114.64 m/min) and (f = 0.441 mm/rev). The obtained % error among the modeled and experimental values is <5% and it is well within the limit. The analysis of chip formation was studied for nanocomposites at lower as well as higher feed rates, cutting speeds, and constant depth of cut during turning. [ABSTRACT FROM AUTHOR]

The mechanical properties of Aluminum metal matrix composites (AMMCs) have made them a popular choice in various industries such as automotive, aerospace, and marine. However, their composition, which includes abrasive reinforcements, makes them difficult to machine using conventional techniques. So, unconventional machining processes play a vital role in the machining of these materials. Electrical discharge turning (EDT) is one of the configurations of electrical discharge machining (EDM) that is utilized to machine cylindrical-shaped workpieces. In this study, AMMC Al 7075/ZrO2 was fabricated using the stir casting method. Further, investigated the effect of machining parameters of EDT, namely pulse Current (I), pulse on time (T-ON), and rotating speed (RPM), on Al 7075/ZrO2 in terms of material removal rate (MRR), tool wear rate (TWR), and overcut (OC) using one parameter at a time (OPAT) method. The outcome of the experiment reveals that MRR, TWR, and OC are more impacted by pulse current than by rotational speed. A decrease in TWR was also found with an increase in pulse on time for all rotational speeds. The size of the craters and globules observed lower with 1400 RPM in the micrograph image. [ABSTRACT FROM AUTHOR]

Turning is one of the most important material removal processes in manufacturing, where the proper understanding of the process is crucial for the quality of the final product. In this study, the stochastic cutting force is utilized to enhance the existing 1-degree-of-freedom turning model. A stochastic model is adopted to address the stochastic resonance phenomenon occurring near stability boundaries. Additionally, a novel simplified stochastic model is introduced with additive noise only. The comparison of the two models reveals that, with the recommended noise intensity of 0.1 to 1%, there is no significant difference in the stability charts and mean square characteristics between the two models. As a result, the time-consuming numerical methods can be bypassed, as the simplified model offers a computationally more efficient analytical approach to compute variance based on power spectral density (PSD). By combining techniques such as D-separation to determine stability boundaries and the PSD-based variance calculation, it only takes a minute instead of hours to construct a heatmap using the introduced simplified stochastic turning model that clearly outlines dangerous stochastic resonance regions inside the stable domain. [ABSTRACT FROM AUTHOR]

Integrating fiber reinforcement plastics (FRP) materials into the industry plays a key role especially for pipes. However, due to the production methods of CFRP pipes, surface finishing processes are inevitable at the end of production. Despite the widespread use of CFRP materials, the predominant focus in the literature has been on their mechanical performance. This study aims to contribute to the limited research on the machinability of CFRP materials. In this context, the turning machining process for CFRP pipes was experimentally investigated in the present study. For this purpose, carbon fiber pipes with an inner diameter of 30 mm and an outer diameter of 60 mm were produced and subjected to computer numerical control (CNC) turning. First, a cylindrical aluminum pipe is used as a mold to manufacture CFRP pipes. Unidirectional (UD) carbon fabrics were wrapped on these aluminum molds. Shrink tape was used to enhance the surface smoothness and required pressure to prevent delaminating of the end product during the process. UD carbon fabrics are wrapped on to the mold at the selected angles (0°, 45°, and 90°) and the CFRP pipe specimens were manufactured using epoxy matrix. Pipes were processed on CNC lathe at 120, 160, 200 rev/min speeds and f 0.4 mm/rev feed rate. The surfaces of the machined specimens were measured with a microscope and a surface roughness device. On the other hand, wear on the tools was observed after the process. Highlights: CFRP pipes were produced with different fibre orientations, i.e., 0°, 45°, and 90°.All CFRP pipes are made under equal conditions and cured at 80°.Turning of CFRP pipes was examined under dry environments.Performance criteria: surface roughness, temperature, tool wear, and chip formation were explored.45° fibre angles CFRP pipes showed the best machinability performance. [ABSTRACT FROM AUTHOR]

Chatter vibration is an undesired phenomenon in machining operations. Chatter can lead to reduced machining quality, productivity, and tool life. The main cause of chatter is the dynamic instability between the cutting tool and the workpiece. Several attempts have been made to detect chatter. Some manual feature extraction methods used to detect the chatter involve wavelet packet transform (WPT), ensemble empirical mode decomposition (EEMD), local mean decomposition (LMD), and variational mode decomposition (VMD). These methods require human expertise for manual feature extraction. In recent time, convolution neural network (CNN) has been evolved as one of the techniques for automatic features extraction. However, CNN uses images and depends on the initial weights and hyperparameters. Creating images from acquired signals for CNN input is still cumbersome and adds one more step in signal processing making it computationally heavy. In this study, a simple, accurate, and robust online chatter detection method is proposed based on wavelet scattering network (WSN). This deep network iterates over standard wavelet transform, nonlinear modulus, and averaging operators of the acoustic signals. Experiments are performed to collect the acoustic signal during the turning operation to train and validate the algorithm. The automatic extracted chatter features are then used in supervised machine learning (ML) algorithms. The results clearly show that the WSN featurization method with SVM algorithm can significantly reduce the complexity of the existing online chatter detection systems without compromising the accuracy. [ABSTRACT FROM AUTHOR]

Chip morphology is an intrinsic characteristic of the machining process that determines the quality of the process. When machining low machinability materials, the chips formed are usually long, continuous, and difficult to break. Due to the negative effect of the accumulation of the chip along the process, chip breakage and the correct extraction out of the machining area have become indispensable requirements. Although numerous chip-breaking methodologies have been proposed, modulation-assisted machining (MAM) is one of the most promising approaches, due to its independence from the workpiece material, tool geometry, and cutting conditions. In this work, a comparison of different modulation-assisted machining strategies, based on the modulation of the feed (F-MAM) or the depth of cut (D-MAM), were experimentally evaluated and compared to conventional turning in terms of chip morphology, surface roughness, and tool wear. Results showed that both MAM strategies enabled chip breakage and improved chip evacuation in comparison to conventional turning; however, D-MAM showed a better performance in terms of tool wear and surface roughness. [ABSTRACT FROM AUTHOR]

This paper investigates the performance of a novel viscous passive damping solution to mitigate the chatter vibrations issue in the context of turning thin-walled cylindrical shell components for aerospace and other industries. This study involves the use of two different viscous fluids, motor oil and silicone oil, which have viscosities of 102 cSt and 350 cSt, respectively, to fill the in-house developed tube components with the aim of improving machining performance. Fast Fourier Transform (FFT) graphs were studied for chatter analysis, and surface roughness parameters such as average surface roughness (Ra) and mean roughness depth (Rz) were considered for studying the effectiveness of the viscous damping fluids. The results obtained with viscous damping were then compared with an undamped/unfilled tube with the same geometry. The cutting experiments showed that the motor oil reduced the excessive vibrations while silicone oil was able to eliminate them. For the tube with motor oil, the magnitude of the process sound at chatter frequency was reduced by 6.6 times as compared to an unfilled tube, whereas for the tube with silicone oil, the amplitude at chatter frequency was reduced by 14.8 times. Moreover, the surface quality of the tubes with motor oil and silicone oil shows almost equal improvement, indicating the need for future research on the type and amount of viscous fluids for implementing the concept in real cases. [ABSTRACT FROM AUTHOR]

This work deals with the optimization of the machining process of EN-GJL-250 gray cast iron with a CBN/Tin-coated insert. The multiobjective optimization was performed by four methods, in order to find the optimal cutting conditions (cutting speed (Vc), feed rate (f), and depth of cut (ap)) that would satisfy the goals of improving surface quality, minimizing power consumption, and maximizing productivity simultaneously. The aim is to evaluate the performance of different techniques, namely desirability function approach, Grey relational analysis, technique of order preference similarity to the ideal solution (TOPSIS), and nondominated sorting genetic algorithm coupled with TOPSIS. The outcomes revealed that the methods propose different solutions, where significant divergences were mainly observed in power consumption and material removal rate objectives. This raises the issue of selecting the most appropriate optimization method for industrial needs and confirms the need for further efforts in this field, i.e. optimization of the machining process. [ABSTRACT FROM AUTHOR]

The motivation of research in modern manufacturing systems demands the least expensive operations to produce the best quality products. To achieve the same objective, the current study analyses and optimizes the Coated tungsten carbide cutting tool's performance compared to the uncoated tool. For the study the coating over the cutting tool has been done using the novel Scalable Pulse Power Plasma (S3P) physical vapor deposition. For the experiments, cutting velocity (Vc), feed rate (f) and depth of cut (d) have been considered as the process or independent variable, while surface roughness and material removal rate have been taken as the response. During the study, Taguchi's L18 orthogonal array is used for the design of experiments, and S/N ratios are used to obtain the impact of process variables on the responses; analysis of variance (ANOVA) is used to get the regression equations used as an objective function for optimization. Grasshopper's optimization algorithm is used for the optimization. The results show that the individual optimization coated tool is suitable for generating smoother surfaces while for higher material removal rate uncoated tool favours. Multi-objective optimization suggested 0.1 mm depth of cut, 0.812 mm/rev feed rate and 70.45 mm/min cutting speed with a coated tool as the optimum parameters for the machining operation, which produces surface roughness of 4.843 μm and 5.47 cm3/min MRR. [ABSTRACT FROM AUTHOR]

In this study, the application of physical vapor deposition (PVD) coatings on various cermet substrates for the machining of nodular cast iron was investigated, given that cermet materials are traditionally not the primary choice for such applications. Through the evaluation of key parameters including wear on the flank face and surface roughness, and with vibration analysis serving as a supplementary measurement, it was discovered that machining stability is compromised by the inherent brittleness of cermet and the adhesion of material on the rake face. While the application of coatings was found to extend tool life, the cermet-coating combinations did not surpass the performance of other materials such as cemented carbide with multi-layer coatings. Notably, the stability of surface roughness across various stages of tool wear was observed. [ABSTRACT FROM AUTHOR]

Minimum Quantity Lubrication (MQL) is a technique used to reduce the utilization of cutting liquids in accomplishing a perfect and well-disposed condition. In this examination, the machinability of M2 steel which is hard-to-machine material utilized in key applications was researched under three separate cutting strategies such as dry environment, oil environment, and copper nanofluids with MQL as environment. The turning tests were conducted utilizing carbide inserts on five separate cutting speed with constant feed and depth of cut. The maximum roughness value obtained with dry condition is 3.75 µm, for oil is 1.7 µm and nanofluid is 0.81 µm. The extreme ank wear values attained is 0.16 mm, 0.055 mm and 0.04 mm for dry, oil and nanofluid conditions. The reduced value of surface roughness (0.45 µm) and ank wear (0.04 mm) were obtained when the machining was performed under copper nanofluid as a coolant. [ABSTRACT FROM AUTHOR]

This work investigates the performance of modified tungsten carbide inserts when turning supermartensitic stainless steel with cutting fluid and/or air jet applied in two directions: either cutting fluid under high pressure or compressed air under low pressure supplied on the back of the chip (through a hole produced near the principal cutting edge), together with either cutting fluid or compressed air, both under low pressure, directed at the clearance face. Tool performance is evaluated by means of the principal cutting force, temperature distribution (using FEM), visual evaluation of the rake face, morphology of the chips and the quality of the machined surface. The findings indicate that the groove reduces the cutting force when dry cutting. Cutting fluid applied under low pressure at the clearance face is more efficient in decreasing both the cutting force and chip temperature than cutting fluid at high pressure supplied at the back of the chip. A chrome oxide layer is formed on the chip when air jet is applied, thus leading to an unfavorable cutting condition. The simultaneous application of cutting fluid under high pressure to reach the back of the chip and compressed air supplied through the clearance face provides the best surface quality. [ABSTRACT FROM AUTHOR]

Background: The laterality of motor symptoms is considered a key feature of Parkinson's disease (PD). Here, we investigated whether gait and turning asymmetry coincided with symptom laterality as determined by the MDS-UPRDS part III and whether it was increased compared to healthy controls (HC). Methods: We analyzed the asymmetry of gait and turning with and without a cognitive dual task (DT) using motion capture systems and wearable sensors in 97 PD patients mostly from Hoehn & Yahr stage II and III and 36 age-matched HC. We also assessed motor symptom asymmetry using the bilateral sub-items of the MDS-UPDRS-III. Finally, we examined the strength of the association between gait asymmetry and symptom laterality. Results: Participants with PD had increased gait but not more turning asymmetry compared to HC (p < 0.05). Only 53.7% of patients had a shorter step length on the more affected body side as determined by the MDS-UPDRS-III. Also, 54% took more time and 29% more steps during turns toward the more affected side. The degree of asymmetry in the different domains did not correlate with each other and was not influenced by DT-load. Conclusions: We found a striking mismatch between the side and the degree of asymmetry in different motor domains, i.e., in gait, turning, and distal symptom severity in individuals with PD. We speculate that motor execution in different body parts relies on different neural control mechanisms. Our findings warrant further investigation to understand the complexity of gait asymmetry in PD. [ABSTRACT FROM AUTHOR]

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 θ 0 and φ 0. Since the engagement conditions of milling and drilling are complex, analogy experiments are conducted in turning with variation of the setting κ r and inclination angles λ s. In this study, process forces and surface roughness were measured as a function of the complete range of fibre cutting angle θ. [ABSTRACT FROM AUTHOR]

Finish turning is one of the key operations governing the residual stress of functional surfaces. The residual stress state is determined by the cutting conditions and the selected cutting tool system (macro geometry, cutting edge preparation, tool substrate, multi-layer coating...). However, this initial configuration evolves over time due to tool wear. Therefore, it seems fundamental to reproduce the wear process of the tool in order to understand the evolution of thermo-mechanical loadings applied to the machined surface. This work presents a numerical methodology for predicting the wear-induced residual stress drift in longitudinal turning. The complete 3D cutting tool is discretized into elementary 2D sections. A finite element based procedure is developed to calculate, considering each local tool geometry, the local loads withstood by the machined material. The latter are merged to generate equivalent 3D thermomechanical loadings implemented in a second macroscopic model able to calculate the residual stress state under different wear levels. Experimental cutting tests with artificially worn tools have confirmed that good agreement can be achieved. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Carbon fibre-reinforced polymer (CFRP) is favored for its high strength to weight ratio, outstanding direction dependent mechanical properties and the high potential for load adapted design. However, machining unidirectional CFRP is challenging due to its anisotropic behavior, resulting in variable surface quality under identical machining parameters with different fibre orientations. Recently, a universal, process-independent model describing the engagement conditions in oblique cutting of unidirectional CFRPs has been developed, introducing the spatial fibre cutting angle θ 0 and the spatial engagement angle ϕ 0. Milling and drilling are mostly used for machining CFRP. Since the engagement conditions are rather complex, first analogy experiments are conducted in turning with variation of the setting and inclination angles. In this study, continuous surface profiles were recorded as a function of the spatial fibre cutting angle. Phenomenological and continuous wavelet analyses can be used to describe the surface profiles as a function of the spatial engagement conditions and to accurately predict them and the surface roughness using an inverse wavelet transformation. Experimental investigations with a side milling process of CFRP validate the prediction approach and show a good agreement between the experimental and predicted surface profiles. [ABSTRACT FROM AUTHOR]

Duplex stainless steels (DSSs) are used in many applications due to their properties, such as high mechanical strength, good corrosion resistance, and relatively low cost. Nevertheless, DSS belongs to the materials group that is difficult to machine. The demand for a total increase in the production requires the optimization of cutting conditions. This paper examines the influence of cutting parameters, namely cutting velocity, feed, and the depth of cut on the surface roughness and chip compression ratio (CCR) after the DSS wet turning process. The study employed Taguchi optimization to determine the ideal cutting parameters for wet turning finishing operations on steel 1.4462. Using the Taguchi design, experiments focused on surface roughness (Ra) and CCR. Utilizing a TiAlN/TiN-PVD coating insert with a 0.4 mm nose radius, cutting velocity of 200 m/min, feed rates of 0.05 mm/rev, and cutting depths of 1 mm yielded the lowest Ra at 0.433 μm. Meanwhile, a cutting velocity of 200 m/min, feed rate of 0.15 mm/rev, and cutting depth of 0.5 mm resulted in the smallest CCR at 1.39, indicating minimal plastic deformation. The inclusion of additional cooling proved beneficial for surface roughness compared to dry and wet turning methods. The experimental data holds value for training and validating artificial intelligence models, preventing overfitting by ensuring sufficient data collection. [ABSTRACT FROM AUTHOR]

An innovative technology is described for improving tool performance in external turning of stainless steels: the application of new coatings to VK8 hard alloy tools. Tool performance is determined from the life of the replaceable standard cutting inserts. The working life of the inserts ends when the wear at the rear face reaches the limiting permissible value (0.5 mm). Such coatings may increase the working life of VK8 alloy tools as much as threefold, without impairing the productivity or the surface quality of the workpiece. [ABSTRACT FROM AUTHOR]

The occurrence of tool chatter can have a detrimental impact on the quality of the workpiece. In order to improve surface quality, machining stability, and reduce tool wear cycles, it is essential to monitor the workpiece machining process in real time during the turning process. This paper presents a tool chatter state recognition model based on a denoising autoencoder (DAE) for feature dimensionality reduction and a bidirectional long short-term memory (BiLSTM) network. This study examines the feature dimensionality reduction method of the DAE, whereby the reduced-dimensional data are concatenated and input into the BiLSTM model for training. This approach reduces the learning difficulty of the network and enhances its anti-interference capability. Turning experiments were conducted on a SK50P lathe to collect the dataset for model performance validation. The experimental results and analysis indicate that the proposed DAE-BiLSTM model outperforms other models in terms of prediction and classification accuracy in distinguishing between stable machining, over-machining, and severe chatter stages in turning chatter state recognition. The overall classification accuracy reached 96.28%. [ABSTRACT FROM AUTHOR]

In the present study, Experimental investigation of the effects of various cutting parameters on the response parameters so as cutting zone temperature (T) and material removal rate (MRR) in the turning of EN AW 1350 Aluminum Alloy by coated carbide tool. The input control parameters selected for the present work were the cutting speed, feed rate and depth of cut. The objective of the present work is to examine the cutting zone temperature and material removal rate for better productivity. The design of experiments was done with the help of Taguchi L27 orthogonal array. Analysis of variance (ANOVA) was used to find out the significance of the input parameters on the response parameters. Percentage contribution for each control parameter was calculated using ANOVA with 95 % confidence interval. From results, it was observed that cutting speed is the most dominant factor for temperature and the depth of cut is the most significant control parameter for material removal rate. Finally, the multiple response optimization of cutting zone temperature and material removal rate was carried out using the desirability function approach. [ABSTRACT FROM AUTHOR]

In this study, hybrid nanocomposites of aluminium (NHAMMCs) made from AA5052 are fabricated via stir casting route by reinforcing 12 wt% Si3N4 and 0.5 wt% of graphene to study its machining characteristics through traditional turning process. The machining factors taken for the consideration in this work are rate of feed, machining speed and machining depth and nose radius. A mixed level Latin square orthogonal array (L18 21, 37) is considered for designing the experimental array. Multi-Objective optimization based on ratio analysis (MOORA) method is adopted for optimizing tool wear, surface roughness, and resultant cutting force. A population-based meta-heuristic optimization procedure; teaching–learning based optimization (TLBO) is also implemented to optimize the outputs. Observation presents that all the considered input factors have a significant influence on the measured outputs. The performance of TLBO algorithm outplays the MOORA method as observed for the results of validation experiment. [ABSTRACT FROM AUTHOR]

The aim of this study is to investigate the impact of input factors, namely spindle speed (Ss), feed rate (Fr), and depth of cut (DOC), on the output response of surface roughness (Ra) and metal removal rate (MRR) during the dry turning process of AA-6061. The material under study, AA-6061, is strengthened with 6% and 8% weight of titanium carbide (TiC) particles, having an average particle size (APS) of 2 microns. To create experimental designs, the Box-Behnken design (BBD) of response surface methodology (RSM) and mathematical models were used. The desirability-function approach of RSM was applied to obtain optimal input factor values. The findings showed that, for 6% TiC composites, Ss had the greatest effect on both Ra and MRR, followed by Fr and DOC. Similarly, for 8% TiC composites, Ss had the most impact on Ra, followed by DOC and Fr, while DOC had the greatest influence on MRR. To validate the accuracy of the proposed models, confirmation tests were conducted. The outcomes of the confirmation test show that the proposed models are valid. The outcome of the study can be applied in manufacturing industries for optimizing machining processes, resulting in increased efficiency and reduced production costs. [ABSTRACT FROM AUTHOR]

Purpose: Despite the accuracy of heart rate (HR) as an indicator of the aerobic engagement has been evaluated in several intermittent on-court activities, its validity as an oxygen uptake (${\dot V_{{O_2}}}$ V ˙ O 2 ) indicator during shuttle running over short paths remains uncertain. Moreover, it is unclear whether speed may affect such validity. This study evaluated the HR ability in estimating the ${\dot V_{{O_2}}}$ V ˙ O 2 during 5-m shuttle running at different speeds. Methods: ${\dot V_{{O_2}}}$ V ˙ O 2 and HR of 12 physically active young men were recorded during an incremental forward running (FW) protocol and a 5-m shuttle test at 50%, 60%, and 75% of maximal aerobic speed (MAS). Slope and intercept of the relationship between HR and ${\dot V_{{O_2}}}$ V ˙ O 2 (HR/ ${\dot V_{{O_2}}}$ V ˙ O 2 ) were individually determined, in both protocols. The HR measured during the shuttle test was used in the FW HR/ ${\dot V_{{O_2}}}$ V ˙ O 2 to estimate ${\dot V_{{O_2}}}$ V ˙ O 2 at each shuttle speed. A paired Student's t-test compared slopes and intercepts of the two HR/ ${\dot V_{{O_2}}}$ V ˙ O 2 . A two-way RM-ANOVA and an equality test examined, respectively, the differences and the equality between measured and estimated ${\dot V_{{O_2}}}$ V ˙ O 2 . Lastly, a Bland–Altman plot described the accuracy and precision of the estimated ${\dot V_{{O_2}}}$ V ˙ O 2 at each shuttle intensity. Results: Slopes and intercepts of the HR/ ${\dot V_{{O_2}}}$ V ˙ O 2 appeared not different between FW and shuttle running. At 50%MAS, HR underestimated the ${\dot V_{{O_2}}}$ V ˙ O 2 (~7%), whereas returned accurate values at the two higher velocities, although with high variability (±18%). Conclusions: When using HR as ${\dot V_{{O_2}}}$ V ˙ O 2 indicator during shuttle running over short paths, a separated analysis of the HR validity as ${\dot V_{{O_2}}}$ V ˙ O 2 indicator is recommended especially when administering different exercise intensities. [ABSTRACT FROM AUTHOR]

During the machining process, problems such as tool wear, high temperature, force distribution, and surface quality deterioration must be fully understood. Control of these problems with experimental studies and numerical analyses is important in ensuring dimensional accuracy and surface integrity of the cutting tool, workpiece, and also the finished product. The aim of this study is to investigate the effects of machining parameters on chip morphology, residual stresses and tool wear in turning operations of ASTM-F75 CoCrMo alloy experimentally and by finite element method (FEM) simulation. The study was carried out at three different feed rates (0.1, 0.2, 0.3 mm/rev) and at a constant cutting speed of 80 m/min both experimentally on a CNC turning machine and with FEM simulation. From the obtained results, the formation of cracks and adhesions on the surfaces of the chip were observed due to the increase of the feed rate. According to the orthogonal cutting model, chip height ratio (Gs) and tooth pitch (Pc) values of saw-tooth chips supported each other with measurements taken from both FEM images and experimental images. With the increase of the forward speed, the Gs ratio decreased, while the Pc increased. In addition, microscopic images obtained from the cutting tool also showed that the rate of crater wear gradually increased with increasing feed rate. As a result, it is seen that machining parameters have a significant effect on cutting tool and chip morphology in CoCrMo ASTM-F75 alloy turning. [ABSTRACT FROM AUTHOR]