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The wear of a cutting tool can lead to tool failure and product quality deterioration, and thus timely maintenance of tools is crucial. Meanwhile, the wear of tools from a same population usually exhibits heterogeneous patterns. Therefore, this paper proposes a dynamic condition-based maintenance (CBM) policy for heterogeneous-wearing tools with considering the product quality deterioration caused by tool wear. The tool wear is modelled by an Inverse Gaussian (IG) process, and the wear rate is assumed to be a random variable to characterise the heterogeneity among tool wear processes. The posterior distribution of reciprocal of tool wear rate is dynamically estimated using the online wear data based on a Bayesian approach. Moreover, the impact of tool wear on product quality deterioration is modelled. The IG process is discretized into a discrete time Markov chain (DTMC). Under the frame of the DTMC, a cost function, containing product quality loss, preventive maintenance (PM) cost and corrective maintenance cost, is developed to determine the optimal PM threshold. The cost function updates dynamically with the dynamic estimation of tool wear rate and thus enables the optimal PM threshold to be dynamically revised. The effectiveness of the proposed CBM policy is demonstrated through a case study. [ABSTRACT FROM AUTHOR]

The dimensional, geometrical, thermal and tool deflection errors which have a big portion of the overall error of machined parts need more attention in precision of components produced by using CNC machine tools. As a result, it is essential to simulate and compensate the errors in the machined components in order to increase accuracy of machined parts. In order to simulate and analyse the real manufactured components in virtual environments, virtual machining systems are proposed. In this paper, application of virtual machining system is investigated in order to simulate and compensate dimensional, geometrical, thermal and tool deflection errors in 5-axis milling operations of free form surfaces. The volumetric error vectors regarding the dimensional, geometrical, thermal and tool deflection errors at each cutting tool location throughout the machining pathways are calculated and compensated utilising the study's created virtual machining technology. In order to validate the study, a sample workpiece free from surfaces is milled by using the 5-axis CNC machine tool. The machine part is then measured by suing the CMM machine in order to obtain the dimensional, geometrical, thermal and tool deflection errors during milling operations of free form surfaces. Thermal sensors are also installed to the different locations of CNC machine tool in order to measure the thermal error of CNC machine tool during machining operations. Finally, in order to improve accuracy in 5-axis milling operations of free form surfaces, new cutting tool paths regarding the compensated volumetric errors of dimensional, geometrical, thermal, and tool deflection errors are generated. As a result, by utilising the proposed virtual machining system in the research work, precision as well as reliability during 5-axis milling operations of free form surfaces can be enhanced. [ABSTRACT FROM AUTHOR]

In recent years, the superalloys such as Inconel, Incoloy and Waspaloy are widely employed in aerospace, nuclear, automobile and marine applications due to their excellent properties. Besides, significant improvements in cutting tools and coatings have been done in recent years, which can be employed in machine superalloys for improving the machining performance. Their high temperature strength and toughness, quick work hardening, low thermal conductivity, tendency to weld onto cutting tools and ability to form built-up edges (BuE) make a challenge to machine nickel-based aerospace superalloys. The phenomena of BuE results in poor surface integrity and rapid tool wear. The selection of appropriate tool & coating material is based on type or grade of nickel alloy, its metallurgical condition and the machining operation to be performed. In this paper, a detailed review is presented to understand the current practices on advanced cutting tools and coating materials, coatings designs and effect of various tool coatings on machining performance. Further, the tool wear mechanism and machining performance under dry and other advanced sustainable environments such as MQL based vegetable oils, supercritical carbon-dioxide and hybrid nanofluids is presented in detail. [ABSTRACT FROM AUTHOR]

Abstract\nHIGHLIGHTSThe growth mechanism and kinetic characteristics of SiC whiskers for novel bionic ceramic cutting tools were analyzed by modified Arrhenius equation, which reveals the regulation effect of SiC whisker growth on the microstructure evolution. Furthermore, the influence of the growth mechanism on the toughening mechanism under shear and indentation failure was investigated. The results showed that the formed transition area at the bonding interface can improve the residual thermal stress distribution. The synergistic effect of multiple macro/micro-toughening mechanisms and interfacial strengthening mechanisms enabled the bionic ceramic cutting tool materials to exhibit excellent fracture resistance under shear and indentation failure.Analyze growth behavior and kinetics of SiC whiskers by the modified Arrhenius equation.Toughening mechanisms taking into account growth kinetics of SiC whiskers.Multiple macro- and micro-toughening mechanisms enhance the fracture resistance. [ABSTRACT FROM AUTHOR]

In rock and mining engineering, it is essential to predict rock cuttability and drillability for estimating drilling costs, selecting suitable drilling/cutting machine and tools, and achieving high productivity. To predict the drillability and cuttability, many destructive methods have been developed. However, they are often expensive and time-consuming. To explore a non-destructive method, this paper builds a series of empirical relationships between rock characteristic impedance and its drillability and cuttability indices by using a large quantity of measured data from various laboratory and field tests in previous publications. The relationships between rock’s UCS (uniaxial compressive strength) and its drillability and cuttability indices are also built for comparison. The results indicate that: (1) the penetration rates of both percussive drilling and rotary drilling depend on rock characteristic impedance, and they decrease with increasing impedance. (2) The specific energies in percussive drilling, rotary drilling and cutting all increase with increasing rock impedance. (3) Most of current drillability indices such as alfa, DRI, CLI and Shore hardness have a certain relationship with rock impedance. (4) Characteristic impedance has a more confident relation with drillability and cuttability than the UCS. Since determination of rock impedance does not necessarily require a destructive method, characteristic impedance has a great potential to be taken as an index to predict rock drillability and cuttability. [ABSTRACT FROM AUTHOR]

High‐speed dry milling (HSDM) technology is one of the most attractive solutions for improving the cutting performance of difficult‐to‐machine materials. However, the study of HSDM performance for 30CrMnSiNi2A steel has not been reported. In this article, HSDM for 30CrMnSiNi2A steel is investigated using TiN‐coated and AlTiN‐coated tools, focusing on cutting force, vibration, surface roughness, residual stress, and tool wear. The effects of cutting parameters on cutting force and vibration are remarkably similar. At a spindle speed of 7500 r min−1, both cutting force and vibration are minimized. TiN‐coated and AlTiN‐coated tools exhibit distinct performance differences. But, HSDM of 30CrMnSiNi2A steel using TiN‐coated and AlTiN‐coated tools can achieve low surface roughness. The depth of cut significantly affects surface roughness, which is lowest at the depth of cut (0.8 mm). Most of the workpiece surface shows residual compressive stress. The main wear mechanisms for both coated tools are abrasive wear, adhesive wear, and oxidative wear. Furthermore, the AlTiN‐coated tool is more wear resistant on the flank face compared to the TiN‐coated tool. Chipping due to crater wear is the leading cause of tool failure for the AlTiN‐coated tool. Upon various comparisons, the AlTiN‐coated tool is more suitable for HSDM of 30CrMnSiNi2A steel. [ABSTRACT FROM AUTHOR]

Considering the extensive applications of turning and facing operations in mechanical engineering manufacturing, the energy consumption of machining equipment has emerged as a significant concern in the manufacturing industries, such as aerospace and automotive. This article focuses on establishing a predictive model and optimizing energy consumption for facing and turning operations on two types of steel, namely, AISI 1038 and AISI 4142, using two different cutting tools. The experiments were planned using Taguchi's L16 orthogonal array, and the coefficients of the predictive model were determined through a linear regression approach. Additionally, a genetic algorithm (GA) with two distinct selection techniques was employed to optimize the three main variables: cutting depth, cutting speed, and feed rate, all aimed at reducing energy consumption. The results of this study show that the selection method used in GA significantly affects convergence toward the optimal solution, while the choice of cutting tool has a considerable impact on energy usage. Moreover, the variation in the effect of cutting parameters on machining energy consumption is analyzed to determine which parameters contribute most to energy savings. The results underscore the importance for manufacturers of using advanced predictive and optimization tools, offering them a competitive edge by achieving economic, environmental, and performance-related benefits. [ABSTRACT FROM AUTHOR]

The complex thermal-mechanical coupling among Ti(C, N)-based cermet tool, workpiece and chip affects immensely the tool life, machining quality and costs during high-speed cutting, which makes the investigation on wear mechanisms of tools quite important. In this work, submicron and ultrafine Ti(C, N)-based cermet tools were prepared by vacuum sintering technology, and the cutting performance of the tools was evaluated by continuous dry cutting. The aim of this work is to unravel the wear mechanisms of submicron and ultrafine Ti(C, N)-based cermet tools based on the cutting performance and wear characteristics of both the cutting tools and chips generated during high-speed cutting. The Vickers hardness, flexural strength and tool lifespan of ultrafine Ti(C, N)-based cermets are significantly superior to those of submicron Ti(C, N)-based cermets because of grain refinement strengthening and the improved distribution of metal phases. Tool wear depends to a large extent upon the contact states and heat transfer ability at different locations of the tool edge, which are characterized by simultaneous action and mutual transition from abrasive, adhesion, surface fatigue and oxidative wear. Overall, ultrafine Ti(C, N)-based cermet tools with excellent comprehensive properties exhibit a distinctly reduced tool wear at different wear regions. [ABSTRACT FROM AUTHOR]

This article discusses the issue of the joint use of neural network algorithms for data processing and deterministic mathematical models. The use of a new approach is proposed, to determine the discrepancy between data from a vibration monitoring system of the cutting process and the calculated data obtained by modeling mathematical models of the digital twin system of the cutting process. This approach is justified by the fact that some coordinates for the state of the cutting process cannot be measured, and the vibration signals measured by the vibration monitoring system (the vibration acceleration of the tip of the cutting tool) are subject to external disturbing influences. Both the experimental method and the Matlab 2022b simulation method were used as research methods. The experimental research method is based on the widespread use of modern analog vibration transducers, the signals from which undergo the process of digitalization and further processing in order to identify arrays of additional information required for virtual digital twin models. The results obtained allow us to formulate a new conceptual approach to the construction of systems for determining the degree of cutting tool wear, based on the joint use of computational virtual models of the digital twin system and data obtained from the vibration monitoring system of the cutting process. [ABSTRACT FROM AUTHOR]

Magnesium alloys are an important group of materials that are used in many industries, primarily due to their low weight. Constantly increasing quality requirements make it necessary to improve the accuracy of manufactured products. In this study, the precision milling process for AZ91D and AZ31B magnesium alloys was investigated, and the results obtained with uncoated and TiB2-coated end mills were compared. The impact of variable cutting parameters was also investigated. Specifically, the study focused on the dimensional accuracy of the machined parts. The results showed that even though the dimensional accuracy obtained in milling both magnesium alloys was comparable, it was higher in the case of the AZ31B alloy by up to 22%. The study also demonstrated that the use of the TiB2 coating did not have the desired effect and that higher dimensional accuracy up to 27% was obtained with the uncoated tool. [ABSTRACT FROM AUTHOR]

This paper examines the challenges of machining structural alloy steels for carburizing, with a particular focus on gear manufacturing. TiN0.85-Ti coatings were applied to cutting tool blades to improve machining quality and tool life. The research, supported by mathematical modeling, demonstrated that these coatings significantly reduce adhesive wear and improve blade life. The Kolmogorov–Arnold Network (KAN) was identified as the most effective model comprehensively describing tool life as a function of cutting speed, coating thickness, and feed rate. The results indicate that gear production efficiency can be significantly increased using TiN0.85-Ti coatings. [ABSTRACT FROM AUTHOR]

In the machining of high-strength materials, shear localization in serrated chip formation leads to time-varying thermo-mechanical loads exerted by the cutting tool on the machined surface. This results in periodic changes to surface integrity. This article explains the formation mechanism of machined surface microfeatures and residual stress fluctuations associated with serrated chip formation, based on a finite element model of machining Waspaloy using the coupled Eulerian-Lagrangian method. The model is validated by comparing the simulation results with experimentally measured chip morphologies and machined surface profiles. During machining with a constant chip thickness, the machined surface exhibits a uniformly distributed residual stress pattern along the cutting velocity direction. However, increased cutting velocity and serrated chip formation cause periodic shear bands, leading to time-varying location of the stagnation point on the cutting tool. This results in variations in the workpiece material volume and the thermo-mechanical loads in the plowing region. After machining, the periodical variation in the elastic recovery of the plowed material at the bottom of the cutting tool creates waveforms on the finished surface, accompanied by fluctuations in residual stress at the same frequency as chip serration. The simulations quantitatively determine the normal/shear contact force at the tool-workpiece interfaces to reveal the effect of the time-varying stagnation point location on surface topographies and residual stress distributions. [ABSTRACT FROM AUTHOR]

Diamond rope saws are one of the important tools for cutting large structures in deep water, and exploring their ability to remove steel materials is a prerequisite for improving cutting efficiency. In this paper, based on the observation results of an optical profilometer on the surface morphology of diamond beads, using statistical theory to analyse the data on the spatial parameters of abrasive grains, a method of three-dimensional digital characterisation of diamond beads based on the spatial description of the coordinate system of the column is proposed. Based on the above research, the theoretical models for material removal prediction and the finite element simulation model of diamond bead cutting steel material are established to analyse the removal ability of steel material under different cutting conditions with the synergistic effect of multiple abrasive grains in the process of diamond beads cutting steel material. Experiments were used to perform error analysis on the theoretical model, optimise the cutting parameters and correct the theoretical model for material removal. The results show that the cutting speed of 21 m/s and the feed speed of 1 mm/min resulted in a low theoretical and real removal error and less bead wear, which is favourable for continuous cutting. This current work provides a theoretical basis for the intelligent monitoring of the cutting process state of underwater diamond rope saws. [ABSTRACT FROM AUTHOR]

This study aims to extend the work-life of diamond-cutting segments and to economize the operating cost of diamond-cutting tools. In order to achieve this object, bronze matrix sandwich segments reinforced with SiC and B 4 C were produced utilizing the hot pressing technique. In the term of the cutting segments, it is favorable that the outer layers are wear-resistant and the middle layer is tough. SEM and XRD analysis were used to determine the microstructural properties. Mechanical properties were evaluated by conducting hardness, wear, cutting performance, and three-point bending tests. The cutting performance of the segments was determined by turning andesite marble. SEM examinations showed that SiC and B 4 C grains were homogeneously distributed in the bronze matrix. The highest hardness value was 113.9 HB in the B 4 C reinforced sandwich segment. The reciprocating wear test findings indicated that the matrix exhibited the lowest wear rate in the B 4 C reinforced sandwich composite segment, followed by the hybrid sandwich composite segment. The lowest amount of cutting loss after turning andesite stone was achieved in the SiC, and B 4 C reinforced hybrid sandwich composite segment. The cutting performance of the hybrid sandwich composite segment increased by 46.15 % compared to the conventional segment without additives. The highest value of the transverse rupture strength of the specimens was 380 MPa for the B 4 C reinforced sandwich composite segment and 352 MPa for the hybrid sandwich composite segment. Considering all the tests and analyses, the hybrid sandwich composite segment sample may be the most suitable for diamond-cutting tools. [ABSTRACT FROM AUTHOR]

The aim of this study was to develop a concept for an angular positioning method for a round cutting insert in a torus cutter body dedicated to the multi-axis milling process under high-speed machining cutting conditions. The method concept is based on a developed wear model using a non-linear estimation method adopting a quasi-linear function. In addition, a tool life model was developed, taking into account the cutting blade work angle parameter, the laser marking method for the round cutting insert, and a wear measurement methodology. The developed tool wear model provides an accuracy of 90% in predicting the flank wear of the cutting blade. The developed procedure for angular positioning of the round cutting insert enables the entire cutting edge to be fully utilized, extending the total tool life. In addition, the measured largest defect values between the worn cutting edge and the nominal outline of the round cutting insert indicate the location of notching-type wear. [ABSTRACT FROM AUTHOR]

Due to the polycrystalline cubic boron nitride tool has the characteristics of high hardness, brittleness, etc., it is easy to break the tool or produce defects in the laser cutting process, which affects the cutting performance of the tool. Traditional defect detection methods can no longer meet the needs of modern manufacturing. Aiming at the problems of low accuracy and poor real-time detection of surface defects on laser-cutting polycrystalline cubic boron nitride tools, this study proposes the surface defect detection model of laser cutting polycrystalline cubic boron nitride tool based on asymptotic fusion strategy, which fills the gap in the field. In the backbone network, the C3SE module is constructed by modeling the correlation between feature channels to improve the model's focus on key features in order to enhance the feature extraction and processing capability of the backbone network; In the neck network, adaptive spatial fusion operation and direct interaction of non-adjacent layers are utilized for multi-scale information fusion, and the asymptotic feature pyramid network for object detection (AFPN) is used instead of the FPN structure to improve the detection performance; In the head network, a soft suppression mechanism is introduced to reduce the overlapping frame score using a decay function, thus improving the detection accuracy. The experimental results based on the self-constructed laser-cutting polycrystalline cubic boron nitride tool surface defects dataset show that the average accuracy of the AFFS-YOLO model is improved by 5.6% compared with that of the YOLOv5 model, reaching 86.1%, and the detection effect is better than that of the original network and other classical target detection networks. [ABSTRACT FROM AUTHOR]

This paper focuses primarily on the wear behavior observed in AISI4340 steel when machining with a multi-layered coated carbide tool. Numerical and experimental examination is processed out to predict the wear performance of AISI 4340 steel along with its cutting force and temperature. In this process, four layers of different coated material are bonded together to form a multi-layered coated carbide tool. The coated thickness is assessed with the assistance of a Scanning Electron Microscope (SEM). Experimental analysis takes place with a heavy duty lathe machine equipped with an infrared thermometer and force dynamometer. Simulation is performed using DEFORM-2D software to simulate cutting forces and interface temperature, and the output results obtained have been compared with the experimental work. With the help of the SEM image, maximum crater wear depth is evaluated and analyzed. Feed plays a crucial role in increasing the chip interface temperature and cutting force. For varied feed rates, the cutting tool edge radius, depth of cut, and cutting speed are taken as the input parameters. The proposed 2D finite element model provides effective parameter values for reducing wear. Results measured indicate that the output parameter values of interface temperature and cutting force obtained from simulation and experimental investigation match each other with high accuracy. Simulation results for temperature distribution around the tool tip show that a maximum temperature of 654 °C is formed at the feed rate of 0.4 mm/rev, leading to high heat flux. For the feed rate of 0.3 and 0.2 mm/rev, there is not much deviation in heat flux around the tool tip. The maximum temperature around the tool tip is near 527 °C for both 0.3 and 0.2 mm/rev. Simulation results show that the lowest tool wear of 0.001 23 mm was obtained for a feed rate of 0.2 mm/rev, followed by 0.004 25 (0.1 mm/rev), 0.005 09 mm (0.4 mm/rev), and 0.007 14 mm/rev. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to examine the cutting performance of a coated carbide tool during the boring of 1Cr17Ni2 martensitic stainless steel, with a focus on how the tool's structural parameters, particularly the nose radius, affect the wear patterns, wear volume and lifetime of the cutting tool, and related mechanisms. Design/methodology/approach: A full factorial boring experiment with three factors at two levels was conducted to analyze systematically the impact of cutting parameters on the tool wear behavior. The evolution of tool wear over the machining time was recorded, and the influences of the cutting parameters and nose radius on wear behavior of the tool were examined. Findings: The results show that higher cutting parameters lead to significant wear or plastic deformation at the tool nose. When the cutting depth is less than the nose radius, the tool wear tends to be minimized. Larger nose radius tools have weaker chip-breaking but greater strength and wear resistance. Higher cutting parameters reduce wear for the tools with larger nose radius, maintaining their integrity. Wear mechanisms are primarily abrasive, adhesive and diffusion wear. Furthermore, the full-factorial analysis of variance revealed that for the tool with rε = 0.4 mm and 0.8 mm, the factors contributing the most to tool wear were cutting speed (38.76%) and cutting depth (86.43%), respectively. Originality/value: This study is of great significance for selection of cutting tools and cutting parameters for boring 1Cr17Ni2 martensitic stainless-steel parts. Peer review: The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-07-2024-0266/ [ABSTRACT FROM AUTHOR]

Wire-arc directed energy deposition (DED) offers promise for large-scale metal component production, yet challenges persist in achieving consistent microstructure and mechanical properties. This paper investigates the effect of machining-induced deformation and grain refinement on microstructure evolution in mild steel structures printed using hybrid wire-arc DED, which integrates interlayer machining steps into the wire-arc DED process. The study demonstrates that machining with radiused-edge cutting tools induces fragmentation of ferritic/bainitic grains, leading to dispersed and refined grain colonies, that, when subjected to reheating and remelting cycles during subsequent layer depositions, lead to a more refined overall microstructure compared to the wire-arc DED process. Comparative analyses revealed a statistically significant 19.5% mean reduction in grain size and 8.5% increment in microhardness of the resulting hybrid wire-arc DED structure. The work points to interlayer machining as a promising strategy for in situ enhancement of the microstructure and mechanical properties in DED processes. [ABSTRACT FROM AUTHOR]

By producing micro-textures with different geometric parameters on the tool surface, the cutting performance of the tool can be effectively improved. Scientists have carried out the design and development of microstructures on the surface of tools based on the study of the performance of microstructured tools. Based on this, this theory first summarizes the production methods of surface microstructures, which are divided into photothermal energy composite processing, electrothermal energy composite processing, and mechanical energy processing according to the different energies. The effects of microtexturing on tool wear, tool strength, and tool life are then examined. Then, the geometric design of surface microtexturing tools from simple texturing to heterogeneous texturing is reviewed, and the mechanism of microtexturing tools is analyzed. Finally, the development direction of tools with surface micro-texture is given to provide guidance for the optimized design of the micro-texture of tool surfaces. [ABSTRACT FROM AUTHOR]

Deep learning has been increasingly used in health management and maintenance decision-making for rotating machinery. However, some challenges must be addressed to make this technology more effective. For example, the collected data is assumed to follow the same feature distribution, and sufficient labeled training data are available. Unfortunately, domain shifts occur inevitably in real-world scenarios due to different working conditions, and acquiring sufficient labeled samples is time-consuming and expensive in complex environments. This study proposes a novel domain adaptive framework called deep Multiscale Conditional Adversarial Networks (MCAN) for machinery fault diagnosis to address these shortcomings. The MCAN model comprises two key components. Constructed by a novel multiscale module with an attention mechanism, the first component is a shared feature generator that captures rich features at different internal perceptual scales, and the attention mechanism determines the weights assigned to each scale, enhancing the model's dynamic adjustment and self-adaptation capabilities. The second component consists of two domain classifiers based on Bidirectional Long Short-Term Memory (BiLSTM) leveraging spatiotemporal features at various levels to achieve domain adaptation in the output space. The deep domain classifier also captures the cross-covariance dependencies between feature representations and classifier predictions, thereby improving the predictions' discriminability. The proposed method has been evaluated using two publicly available fault diagnosis datasets and one condition monitoring experiment. The results of cross-domain transfer tasks demonstrated that the proposed method outperformed several state-of-the-art methods in terms of transferability and stability. This result is a significant step forward in deep learning for health management and maintenance decision-making for rotating machinery, and it has the potential to revolutionize its future application. • A novel Multiscale Conditional Adversarial Networks (MCAN) is proposed. • An adaptive attention mechanism network is built to extract features from raw signals. • The cross-covariance matrix of deep features and output labels can improve domain alignment. • MCAN excels in cross-domain diagnosis and monitoring of bearings and cutting tools. [ABSTRACT FROM AUTHOR]

Laser-assisted turning (LAT) involves locally heating a rotating workpiece using a focused laser beam before the removal of material. A key aspect in optimising productivity with laser-assisted turning is understanding the thermal relationship between laser heating, the improved material removal rate, and machinability. Consequently, in this paper, a thermal heating and laser-assisted turning finite element model and experiments were conducted to assess the machinability of an Al/SiC p MMC workpiece, considering the circumferential location of the laser beam from the cutting point. The results confirm that laser power and cutting velocity influence the temperature profile from the laser spot to the tool point and the heat-affected depth. Positioning the cutting tool closer to the laser spot effectively reduces the Von Mises stress during cutting at higher cutting temperatures. At the same time, the experiment indicates an increased risk of directly heating the tool, which can affect the integrity of the cutting tool. The work further reveals that at specified cutting velocities, lower specific cutting energy improves the tool condition and surface quality of the machined parts. Based on a range of material removal rates and laser-specific energy density, a new criterion for optimal laser-tool circumferential distance was determined. Establishing this distance can act as a guide for the laser-assisted turning of Al/SiC p metal matrix composites and potentially other materials. [ABSTRACT FROM AUTHOR]

The turning process is a widely used machining process, and its productivity has a significant impact on the cost and profit in industrial enterprises. Currently, it is difficult to effectively determine the optimum process parameters under complex conditions. To address this issue, a classification-based parameter optimization approach of the turning process is proposed in this paper, which aims to provide feasible optimization suggestions of process parameters and consists of a classification model and several optimization strategies. Specifically, the classification model is used to separate the whole complex process into different substages to reduce difficulties of the further optimization, and it achieves high accuracy and strong anti-interference in the identification of substages by integrating the advantages of an encoder-decoder framework, attention mechanism, and major voting. Additionally, during the optimization process of each substage, Dynamic Time Warping (DTW) and K-Nearest Neighbor (KNN) are utilized to eliminate the negative impact of cutting tool wear status on optimization results at first. Then, the envelope curve strategy and boxplot method succeed in the adaptive calculation of a parameter threshold and the detection of optimizable items. According to these optimization strategies, the proposed approach performs well in the provision of effective optimization suggestions. Ultimately, the proposed approach is verified by a bearing production line. Experimental results demonstrate that the proposed approach achieves a significant productivity improvement of 23.43% in the studied production line. [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]

In turning, tool wear and cutting vibration are inevitable, which have great influence on surface quality. Analyzing the influence mechanism of tool wear and cutting vibration on surface quality is important to achieve the accurate prediction of surface roughness before machining and improve machining quality. In this paper, a turning vibration experiment is conducted to reveal that the diameter of shafts is an important factor affecting the vibration amplitude and frequency. In addition, based on machining parameters, tool wear and workpiece diameter, this empirical model, the response surface method and a support vector machine are used to model and predict surface roughness. The fitting accuracy, prediction accuracy and generalization performance of the proposed methods are compared in detail. The results show that the response surface modeling method has the highest fitting accuracy, but the exponential empirical modeling method has the highest prediction accuracy and best generalization performance. Additionally, the prediction results indicate that the surface roughness increases with the increase in tool wear and decreases with the increase in workpiece diameter. [ABSTRACT FROM AUTHOR]

Simultaneous machining and coating (SMaC) is a novel hybrid technology developed by the Fraunhofer Institute for Laser Technology ILT that combines additive manufacturing through extreme high-speed laser material deposition (EHLA) with a simultaneously engaged turning process. In the present work, the parallelization of the two subprocesses is successfully demonstrated. For the first time, systematic investigations into the influence of residual heat from the deposition process on the machining process and the properties of the resulting coating, respectively, are conducted. The study specifically examines geometric deviations, surface roughness, and tool wear. One of the main parameters affecting the residual heat introduced into the turning process is the distance between the tool center points of the EHLA deposition head and the turning tool Δz. This parameter is identified as a primary factor influencing the dimensional accuracy of the coating geometry. The results show that SMaC not only offers potential for increasing the productivity of the process chain but also has a positive effect on the service life of the cutting tools involved, potentially improving the workability of hard coating materials. Improvements in terms of the attainable surface roughness are also observed. These investigations provide a basis for research into further aspects of the SMaC process, such as adaptive tool path control methods to enhance dimensional accuracy and the influence of induced compressive stresses in processing highly brittle coating materials. [ABSTRACT FROM AUTHOR]

Tiered umbrella or in Thai called Chat means a high decoration or decoration of honor, a type of umbrella that is stacked up in layers along a single axis. At present, in Thailand, the tiered umbrellas are seen in three important places including (1) on the top of the pagoda of various temples, (2) inside the ordination hall of temples, and (3) inside the Grand Palace for the king and the royal family. In the past, a tiered umbrella was made from brass because its color was similar to gold. Constructing each set of tiered umbrellas requires a skilled technician and takes a lot of time. At present, laser cutting of metals has been widely used in the production section of the industry. This is due to the advantages of laser cutting that include narrow kerf width, smooth cutting edges, high cutting speed, reduced material waste, no tool wear, and easy automation and manipulation even for complex shapes. In this work, an example for the construction of seven-tiered umbrellas from stainless steel sheets using a high-power CO2 laser was reported. The results show that the total working time for the construction of a seven-tiered umbrella is about 113 h, which is much less time compared to 3–6 months taken by craftsmen. Therefore, this method can preserve the construction of tiered umbrellas in Thailand even though craftsmen are scarce at present. [ABSTRACT FROM AUTHOR]

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Tool geometry has a significant impact on cutting mechanics and key machining parameters such as tool life, workpiece surface quality, specific cutting energy, and dynamic stability of the cutting process. In the turning process, where the cutting tool remains in a fixed position, it is possible to develop a mechanism to adjust the tool angles during machining. This research introduces a new tool-holder mechanism for the lathe that can adjust the side inclination and front inclination angles. The simultaneous control of these angles allows for precise adjustment of the normal rake and clearance angles of the tool. Since these angles greatly affect all machining parameters, this mechanism can enhance the quality of the machining process. By implementing an active chatter control system using the proposed mechanism, the controller can reduce the tool’s clearance angle to increase process damping and prevent chatter. The mechanism enables adjustment of the normal rake and clearance angles by up to 8 degrees. Test results demonstrate that utilizing this mechanism and the provided chatter suppression/control technique can effectively prevent chatter at higher machining speeds and improve machining stability. The proposed mechanism has potential applications in advanced CNC lathes with open architecture for precise and optimal adjustment of machining parameters. [ABSTRACT FROM AUTHOR]

In recent years, the exponential growth of the machining industry and its needs has driven the development of new manufacturing technologies, more advanced cutting tool types, and new types of coatings to extend tool lifespan. New coating solutions have been studied and implemented for machining tools, which provide a low friction coefficient and lubrication, thus increasing tool lifespan. Following this line of reasoning, it is relevant to develop scientific work aimed at studying the behavior of cutting tools coated with thin films that promote low friction and high lubrication, as is the case with DLC (diamond-like carbon) coatings. These coatings promote good resistance to oxidation and allow high machining speeds, properties also exhibited by TiAlN (titanium aluminum nitride) coatings. In fact, there is a gap in the literature studying the performance of cemented carbide tools provided with multilayered coatings in milling operations of Cu–Be alloys, commonly used in inserts of plastic injection molds. This study's objective was to investigate the effect of a multilayer coating (TiAlN/DLC) on end-milling tools to analyze their cutting performance when milling a Cu–Be alloy known commercially as AMPCOLOY®83. The quality of the machined surface was evaluated, and the wear of the cutting tool was studied. A comparative analysis of milling parameters with respect to their effect on the condition of the surface after machining and the resulting wear on the tools, using coated and uncoated tools and different machining parameters, allowed us to verify a better quality of the machined surface and wear quantified in approximately half when used coated tools. [ABSTRACT FROM AUTHOR]

This review paper examines the techniques and factors involved in pipe wall processing, with a focus on the essential technologies utilized in this field. The study revealed crucial elements, such as ASTM A350-LF2 Class 1 carbon steel, renowned for its exceptional mechanical qualities and ability to withstand low temperatures. An exhaustive analysis has been conducted on the chemical makeup of this steel to comprehend its capacity to adjust and endure in various operational environments. The study focused on examining several particle separation processes, including as turning, milling, drilling, and grinding, in order to determine the exact equipment and criteria needed for each technique. The cooling and lubricating process received particular emphasis, with thorough investigation of several agents, including CASTROL HYSOL T15, and their impact on surface quality and tool longevity. The utilization of these compounds has been discovered to substantially decrease tool temperature and enhance machining quality. Upon closer examination of the processing techniques specified in section A-A of the tube wall, it was determined that advanced procedures such as floating plug drawing and micro-sized spiral tube hydroforming were discovered. These techniques allow the attainment of superior surface quality and precise dimensions, which are crucial for guaranteeing the structural integrity of the pipe. Cutting tools, processing equipment, and coolants and lubricants are essential components in the manufacturing of pipe walls. Nanoparticulate cooling and lubrication systems, which are advanced technologies, have demonstrated their effectiveness in minimizing friction and heat during machining. As a result, these systems enhance productivity and prolong the lifespan of tools. According to the article, the essential components for attaining high-quality manufacture of pipe walls are cutting tools, processing equipment, and coolants and lubricants. Additional study is advised to enhance processing parameters, create ecofriendly coolants and lubricants, and utilize artificial intelligence for predictive modeling and optimization of processing. This establishes the groundwork for future research and innovation in the pipe wall production business, with the objective of attaining enhanced efficiency and sustainability in production processes. [ABSTRACT FROM AUTHOR]

The blisks are complex thin-walled parts with specific structures that have narrow channels and a large degree of bowed-twisted blades. These parts are typically machined using 5-axis machining. However, conventional feedrate scheduling of the tool tip can cause flutter and reduced machining accuracy when dealing with very small radii of curvature and dramatic changes in the tool axis vector. This is because there is a significant difference in moving speed between the tool tip and cutting contact points. To address this issue, we establish an optimization model for feedrate under constraints such as process-allowed cutting speed and machine tool drive along the toolpath. For sections of short toolpaths in the regions of leading and trailing edges with drastic changes in curvature and tool orientations, we schedule a constant feedrate for the tool contact point. For other sections of the toolpath, we construct time-optimal acceleration and deceleration velocity curves using parallel computing technology, ensuring no abrupt changes in acceleration or acceleration velocity at boundary points. Additionally, we smooth the feedrate profile curves for the entire toolpath using the parallel bidirectional scanning method. This approach improves both the efficiency of feedrate scheduling and cutting stability within the regions corresponding to the leading and trailing edges of blisks. [ABSTRACT FROM AUTHOR]

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

Double-arc milling cutter can effectively enhance the workpiece surface quality and is appropriate for finish machining complex surface. This article examines the effects of tool structure factor, two vertical milling orientations, workpiece inclination angle, cutting speed, and feed per tooth on the cutting force in order to thoroughly explore the cutting performance of double-arc milling cutter. Instantaneous effective cutting speed and radius models are established for various cutting orientations and conditions using the parameterized model of double-arc milling cutter. Additionally, a method for characterizing the tool structure factor of double-arc milling cutter is proposed. Three double-arc milling cutters with different structure factor and single factor experiments for milling concave and convex surfaces are designed. The impact of tool structure factor, workpiece inclination angle, cutting orientations, and cutting parameters on cutting force is thoroughly analyzed. Theoretical support is provided for the optimization of tool parameters, cutting orientations, and cutting parameters prior to surface machining. [ABSTRACT FROM AUTHOR]

Although rare-earth magnesium (Mg-RE) alloys are widely used in various industries, they show much poorer machinability for shaping into desired dimensions than conventional magnesium ones. The most critical issues associated with cutting Mg-RE alloys are high risk of chip ignition and short tool life dominating the chip removal process. The present paper aims to address the tool performances on the machinability of Mg-RE alloys under dry cutting. Four types of tools covering uncoated and diamond-coated ones were examined, and a special focus was devoted to explore the effects of various tool parameters on the milling responses of Mg-RE alloys as well as the underlying wear mechanisms. The experiments reveal that the cutting tools with larger rake, clearance, and helix angles can achieve high-quality milling of Mg-RE alloys at controllable cutting temperatures. The cutting parameters can be maintained at a certain level, such as the cutting speed of 120–240 m/min and the feed per tooth of 0.1–0.2 mm/z, to meet the requirements of safe milling of Mg-RE alloys without ignition risk. [ABSTRACT FROM AUTHOR]

In the hard turning process of AISI M2, due to its high hardness and high strength, the tool wear is serious. Tool wear seriously restricts the economic feasibility of hard turning and the machining quality of workpiece. Therefore, it is very necessary to take optimization measures of cutting parameters to reduce tool wear. In this research, 15 groups of hard turning experiments were carried out based on BBD. The relative wear of tool flank in hard turning per unit material volume was taken as the optimization objective, and the prediction model of relative wear of tool flank was established. The research results were as follows: (1) the wear forms of CBN tool were crater wear of tool rake, abrasive wear of tool flank and cutting edge wear; (2) the correlation coefficient R2 of the prediction model was 0.9922, and the adjusted correlation coefficient R adj 2 was 0.9843; and (3) the contribution of feed rate to the relative wear of tool flank was 48.83%, and that of depth of cut was 22.05%. A = 81.17 m/min, B = 0.15 mm/rev and C = 0.2 mm were the optimal cutting parameters. This research is helpful to reduce the tool wear in hard turning and improve the economic feasibility of hard turning precision machining. [ABSTRACT FROM AUTHOR]

This study establishes an empirical model for a four-flute cylindrical helical end mill, utilizing orthogonal cutting tests on a Ti-6Al-4V block as the machining workpiece. The reliability of the model was confirmed through a titanium alloy side milling experiment. Results demonstrate that the empirical index model for predicting the main cutting force error falls within the range of 4.19 %–10.0 %, providing an effective tool for cutting force prediction. The specific influence distribution trends of cutting parameters, including milling speed, feed per tooth, and depth of cut, on the cutting force through two-step milling of profile walled surface of titanium alloy were analyzed. The results reveal that the milling force in the first step exhibits a discernible upward trend with the increase of feed per tooth and radial depth of cut. Among the cutting parameters employed in the first step, the cutting speed exerts the most significant influence on the cutting force in the second step. [ABSTRACT FROM AUTHOR]

The demand for enhancing tool performance has increased as the use of difficult-to-cut materials increases. The edge-honing process is one of the methods to enhance the tool performance by adjusting the radius of the cutting-edge. This study used a finite element analysis program to compare the cutting force, cutting temperature, and chip curl radius, assuming a cutting-edge radius of 5, 10, 15 and 20 µm. In addition, the cutting force, cutting temperature, surface roughness of the workpiece, and tool wear were confirmed through machining experiments. The experimental results indicated that the edge-honing process adversely affects the uncoated tool while positively affecting the coated tool by suppressing tool wear. Finite element analysis and machining experiments confirmed that the edge-honing process positively affects tool life and coating. [ABSTRACT FROM AUTHOR]

Helical grinding is crucial for manufacturing small holes in hard-to-machine composite ceramics. This study introduces a geometric model of undeformed chips to analyze the cutting characteristics of abrasive grains on both the bottom and side edges of the tool. It reveals for the first time that the distribution of cutting grains—pure bottom-edge, pure side-edge, and mixed-edge—is influenced by the tool diameter and eccentricity. A novel calculation method for the distribution range (Dp) of pure bottom-edge grains is proposed, demonstrating that using a tool diameter at or below two-thirds of the target hole diameter effectively eliminates pure bottom-edge grains, improving chip evacuation, reducing chip adhesion, and optimizing cutting performance. Experimental validation on small holes in SiCp/Al composites (65% volume fraction) confirmed these findings and provides practical guidance for optimizing cutting parameters and tool design. [ABSTRACT FROM AUTHOR]

Cf/SiC composites are widely utilized in the aerospace industry due to their excellent properties. However, Cf/SiC composites are notoriously challenging to machine. The substantial cutting force and severe tool wear during machining often result in poor surface quality and low machining efficiency. This paper presented a corrugated helical PCD (polycrystalline diamond) tool, featuring a helical structure and an arc array micro-groove on the primary cutting edge, and these micro-groove structures are staggered, facilitating continuous material removal during the machining of Cf/SiC composites. The study investigated the milling force variations of the corrugated helical PCD tool when machining Cf/SiC composites under different milling parameters. A comparative study was conducted on the milling force, surface quality, and tool wear of corrugated helical PCD tool and commercial PCD tools. The experiment revealed that the milling force initially decreases and then increases with rising spindle speed and increases with higher feed rates per tooth, milling depth, and width. The newly designed tool exhibited lower milling force, superior machining surface quality, and extended tool life, approximately 0.7 times that of commercial PCD tools. The cutting performance of the corrugated helical PCD tool proved superior. Additionally, it was confirmed that the primary wear mechanism for the corrugated helical PCD tool cutting Cf/SiC composites was abrasive wear. [ABSTRACT FROM AUTHOR]

Diamond cutting with a controllable depth of cut at the subnanometric scale is desired for next-generation electronics and optics. However, due to the limits of positioning accuracy of the current machine tools, diamond cutting at subnanometric scale depths remains in realm of molecular dynamic (MD) simulations instead of engineering realization. Cutting force feedback and control is regarded as a potential method to improve the positioning accuracy of machine tools. In this study, an ultra-precision force feedback loop with the resolution down to submillinewton is employed and integrated on an ultra-precision machine tool to enable the capability of cutting at subnanometric scale depth. By this way, the relationship between the cutting force and such small depth of cut needs to be well studied. MD simulations are conducted in this study to analyze the mechanism of material removal and influence of the crystallographic effect on the actual cutting depth and force caused by varied cutting directions at subnanometric to nanometric scale depth in diamond turning. Then, the crystallographic effect of silicon with the depth of cut from subnanometric to nanometric scale is compensated experimentally for accurate cutting at such an extremely small scale. Controllable diamond cutting of structured surfaces with actual depths and amplitudes ranging from several angstroms to a few nanometers on silicon is successfully realized. [Display omitted] • A force feedback loop is integrated on an ultra-precision machine tool to enable the cutting with subnanometric scale depth. • The crystallographic effect of silicon is compensated for accurate cutting with subnanometric to nanometric scale depth. • Structured surfaces with subnanometric to nanometric scale height features on silicon are successfully realized. [ABSTRACT FROM AUTHOR]

This study focuses on the fabrication and characterisation of Al 2 O 3 -SiC w -rGO composites sintered by spark plasma sintering (SPS) technique. The research is mainly focused on understanding the impact of varying graphene content (0.5, 1.0 and 1.5 vol %) on nanomechanical properties and scratch resistance. Among the compositions investigated, the composite containing 0.5 vol% graphene showed superior mechanical properties. Specifically, it exhibited a hardness of ∼30 GPa, a fracture toughness of 10.5 MPa m1/2 and a flexural strength of ∼920 MPa. In addition, this composite showed remarkable scratch resistance compared to composites with a higher or lower graphene content. In addition to mechanical properties, the fabricated composites also exhibited high electrical conductivity. This characteristic is especially advantageous for electrical discharge machining (EDM) processes. The high electrical conductivity enables efficient machining of complex shapes by EDM, thereby reducing machining costs while ensuring accuracy and efficiency. [ABSTRACT FROM AUTHOR]

The aim of this paper was to develop and verify a method for evaluating the high-performance milling of Inconel 718 alloy under accelerated tool wear conditions. The method considered parameters such as cutting-force components, total machine power consumption, cutting-edge wear, and material removal rate. The study compared high-feed milling and plunge milling, using sets of cutting parameters that are appropriate for both techniques. The results indicate that high-feed milling was more efficient, achieving higher material removal rates and lower tool wear. On the other hand, plunge milling was characterized by a lower axial force component (Fz), which can positively affect machining accuracy. The paper highlights that the proposed evaluation method can also be applied to other hard-to-machine materials, and plunge milling offers a competitive alternative for roughing operations in the milling of Inconel 718 alloy. [ABSTRACT FROM AUTHOR]

This research analyzes HSS tool wear in turning AFNOR 07-05-04-04-02 steel with variations in machine speed (RPM) and feed depth. Steel, as an iron-based alloy, is known for its superior strength and corrosion resistance, while HSS chisels are used in the machining industry for their wear resistance and ability to maintain sharpness at high temperatures. The results showed that increasing RPM caused greater tool wear, with the highest difference in tool weight at RPM 900 and 1200, reaching 1.0 grams, compared to 0.752 grams at RPM 700. Surface roughness also increased with higher RPM; at 1200 RPM the average value of Ra reaches 4.390565 µm, while at 700 RPM it is only 2.944778 µm. These findings indicate that greater tool wear contributes to increased surface roughness of the workpiece. Variations in Ra, Rz, Rq, and Rt values indicate that different cutting parameters significantly influence the surface quality. This research is expected to provide valuable information for the machinery industry and support the development of materials science and increased productivity in manufacturing. [ABSTRACT FROM AUTHOR]

The tool's life statistics module in CNC machining centers typically associates tool's usage time with the program's running duration, leading to the tool idle time being logged as a loss in tool life. This often triggers premature tool replacements. To enhance scheduling accuracy across multiple machining centers, we leverage spindle current variations to discern between tool loads and idle periods. Initially, real-time data from the machining center was gathered, and we employed the three-parameter Weibull Distribution method, using 1.351 (A) as the threshold to distinguish between idle and loaded tool states. Subsequently, we proposed a refined method to calculate the tool's available time, enabling a more precise estimation of its remaining operational lifespan. We further devised a scheduling approach for multiple CNC machining centers based on the tool's availability time. Ultimately, empirical trials exhibited a 10% increase in average cutting tool utilization efficiency and a 12.5% enhancement in machining center productivity. [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]

Bandsaw blades are typical band-shaped cutting tools that are characterized by their low stiffness and micro-level cutting depth, resulting in distinct wear mechanisms compared to rigid cutting tools. In this study, the wear curve and wear mechanisms of the bandsaw tooth during the bandsawing of Cr12MoV cold-working steel were investigated. The tool life was divided into two stages: a rapid wear stage (Stage I) and a homogeneous wear stage (Stage II). In Stage I, the wear was dominated by chipping, although multiple wear mechanisms were found due to their relatively low manufacturing accuracy compared to rigid cutting tools, which resulted in remarkable differences in the cutting depth of each tooth. In Stage II, abrasive and adhesive wear were the primary wear mechanisms instead of chipping, which was related to the microstructure of Cr12MoV. Furthermore, methods for increasing bandsaw performance were proposed, based on the tooth wear mechanisms. [ABSTRACT FROM AUTHOR]