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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]

Cutting tool materials are the backbone of machining and play a vital role in the manufacturing industry. Innovation in cutting tools is important for customized and demanding applications. This state-of-the-art review is focused on innovations and future research directions for cutting tools covering i) tool materials/microstructure/property relationships, ii) coatings and their effect on tool performance, iii) cutting edge and functional surface preparation and effect on tool performance, iv) tool geometry for high performance and stable machining considering rapid machining, sustainability, and circularity aspects. The vision is to identify tool material/coating/geometry/functional surface relationships for significant improvement in machining performance. This paper includes perspectives from several research groups with a detailed discussion on current advances, capabilities, and challenges in engineered design of cutting tools, materials, coatings, structures and sets a new agenda for future tooling and research directions. [ABSTRACT FROM AUTHOR]

This paper aims to quantitatively analyze the relationship between forces acting on the tool tip and tool movement during drilling operations. The study encompasses axial and lateral vibrations superimposed on the nominal tool movement, arising from rigid body motion (rotational and axial velocities). Specifically, only forces attributed to the cutting process are considered, excluding considerations of indentation forces around the chisel edge. The research adopts a generalized approach, spanning from tool measurements to establishing the force model. The investigation involves measuring cutting forces and correlating them with the varying rake and inclination angles of the drill's cutting edges. An analytical model is proposed to describe the distribution of all local force components along drill edges, considering the evolution of forces and geometry. The dynamic coefficient matrix is evaluated by using the identified cutting coefficient and tool geometry. Validation of the proposed methodology is demonstrated through drilling experiments on Ti6Al4V alloy, utilizing three solid carbide drills with distinct geometries. The proposed procedure allows complete identification of the dynamic characteristics from the measurements taken at the entrance stage of hole drilling operation. Moreover, the influence of tool geometry on cutting coefficients and dynamic coefficient matrices are discussed. • A novel method is developed to achieve minimized experimental effort to identify cutting coefficients in drilling process. • Experiments with industrially relevant tools validated the accurate predictions of transient drilling axial force and torque. • The method is extended to inversely obtain the dynamic coefficient matrix, for the first time, from experimentally measured forces. • Effects of geometry and dynamic interactions were demonstrated using three solid carbide drills with distinct geometries. [ABSTRACT FROM AUTHOR]

The automotive, aerospace and marine industries make extensive use of aluminum and its alloys to produce a wide variety of components. This prompts research work related to improving manufacturing processes using these materials. One of the main problems in this area is the durability of cutting tools. This article describes the results of tests on wear of the coated and uncoated carbide cutting tools during turning of EN AW 2007 aluminum alloy. The tests were carried out under dry conditions and at higher cutting speeds. On the face rake, the VBB indicator (average width of the flank wear) and on the rake face, the KB indicator (crater width on the rake face) were evaluated. Only for the uncoated insert, the break-in period, steady-state wear region and intensive wear were observed and the limited alue of the VBB indicator was obtained after 36 minutes of the tool life. The TiAlN+TiN coated insert, as well as TiCN achieved very short tool life periods of 16 and 24 minutes, respectively. Compared to the uncoated and the TiCN coated insert, a VBB increase of about 170% was obtained for the TiAlN+TiN coated insert after 16 minutes. In contrast, an increase in the VBB of almost 60% was obtained for the TiCN coated insert after 24 minutes, compared to the uncoated insert. Compared to the uncoated insert, an increase of 12.1% in the KB value was obtained for the TiCN coated insert, and 18.2% for the TiAlN+TiN coated insert. The main wear mechanism of the tested cutting inserts was the phenomenon of adhesion. Abrasion wear is observed on the surfaces of the TiAlN+TiN and TiCN coated inserts. The TiCN coated insert also showed coating delamination. The buildup edge (BUE) phenomenon is observed on the surfaces of the TiAlN+TiN coated and uncoated inserts. [ABSTRACT FROM AUTHOR]

Cutting edge preparation is an established approach in the field of machining technology for optimizing the performance of cutting tools. However, the potential of asymmetric geometries has not yet been sufficiently utilized for filigree micromilling tools. In this regard, the study presents investigations on the adjustment of asymmetric microgeometries through the design of the pressurized air wet abrasive jet machining (PAWAJM). The study features results regarding the design of the preparation process as well as subsequent application tests in a hard micromilling process of the hardened high-speed steel AISI M3:2. The application tests focus on the effect of the conditioned cutting edge on the process forces and the surface quality as well as the tool life. The results show that asymmetrical microgeometries with small average cutting edge rounding and a form-factor of K > 1.2 can be achieved by PAWAJM. Machining tests revealed a potential reduction of the wear development and process forces for modified tools with low cutting edge rounding and asymmetrical microgeometry. [ABSTRACT FROM AUTHOR]

Machinability is a generalized framework that attempts to quantify the response of a workpiece material to mechanical cutting, which has been developed as one of the key factors that drive the final selection of cutting parameters, tools, and coolant applications. Over the years, there are many attempts have been made to develop a standard evaluation method of machinability. However, due to the complexity of the influence factors, i.e., from work material and cutting tool to machine tool, that can affect the materials machinability, currently there is no uniquely defined quantification of machinability. As one of the outcomes from the CIRP's Collaborative Working Group on "Integrated Machining Performance for Assessment of Cutting Tools (IMPACT)", this paper conducts an extensive study to learn interacting machinability parameters to evaluate the overall machining performance. Specifically, attention is focused on recent advances made towards the determination of the machinability through tool wear, cutting force and temperature, chip form and breakability, as well as the surface integrity. Furthermore, the advanced methods that have been developed over the years to enable the improvement of machinability have been reviewed. [ABSTRACT FROM AUTHOR]

Utilization of Computer Numerical Control (CNC) machines is crucial in modern manufacturing. Nevertheless, enhancing the skills of CNC machine operators remains a challenge in education and training. In response, the solution involves designing learning materials that simulate the machining process, particularly in innovative CNC learning integrated with Augmented Reality (AR) technology. The research utilizes the Multimedia Development Life Cycle (MDLC) model, encompassing steps like concept development, design, material collection, assembly, testing, and distribution. AR devices deliver additional visual information to CNC lathe students. The research results in learning materials using augmented reality to present 3D visualizations through markers, creating object representations to train 2-axis CNC lathes. These materials, designed as 3D virtual objects, offer real-time practicum experiences to learners. Black box testing confirms the effective implementation of augmented reality in CNC lathe training, providing cost savings in practicum materials and cutting tools during repeated testing on a 2-axis CNC lathe. [ABSTRACT FROM AUTHOR]

Multiple international organizations and many governments around the world have declared climate emergency. There is a pressing need to minimize the environmental impacts of human activities including manufacturing processes. Machining by mechanical cutting is a fundamental manufacturing process and minimizing and eliminating its environmental impacts is vital. In this keynote paper, sustainability in the context of machining is identified. The resources used in machining have been categorized and the social and environmental impacts and potential methods to reduce them have been identified. The findings are critically discussed and the gaps and challenges for future research direction are highlighted. [ABSTRACT FROM AUTHOR]

• Flank face textured cutting tool found superior than plain tool for dry machining of Mg. • The dimple textures on the flank face of the cutting tool reduces its wear significantly. • Cutting speed is the most influencing factor. • Abrasive wear and discontinuous chips were obtained at low-speed machining. Magnesium alloys have many advantages as lightweight materials for engineering applications, especially in the fields of automotive and aerospace. They undergo extensive cutting or machining while making products out of them. Dry cutting, a sustainable machining method, causes more friction and adhesion at the tool-chip interface. One of the promising solutions to this problem is cutting tool surface texturing, which can reduce tool wear and friction in dry cutting and improve machining performance. This paper aims to investigate the impact of dimple textures (made on the flank face of cutting inserts) on tool wear and chip morphology in the dry machining of AZ31B magnesium alloy. The results show that the cutting speed was the most significant factor affecting tool flank wear, followed by feed rate and cutting depth. The tool wear mechanism was examined using scanning electron microscope (SEM) images and energy dispersive X-ray spectroscopy (EDS) analysis reports, which showed that at low cutting speed, the main wear mechanism was abrasion, while at high speed, it was adhesion. The chips are discontinuous at low cutting speeds, while continuous at high cutting speeds. The dimple textured flank face cutting tools facilitate the dry machining of AZ31B magnesium alloy and contribute to ecological benefits. [ABSTRACT FROM AUTHOR]

In conventional machining processes based on the chip removal mechanism, the progressive wear of the tool determines a change of the geometric characteristics of the cutting edge. Tool wear is a complex phenomenon and related tool life depends on several factors, such as cutting parameters, lubrication, and tool-workpiece relative trajectories. Tool wear progression affects the quality of the machined parts, making the tool replacement necessary even before its breakage. Moreover, in industrial practice, tool replacement cannot depend on the subjectivity of the operator, thus, the definition of an optimized strategy for cutting tool wear monitoring before tool failure is mandatory. This work compares Random Forest and Neural Network models for predicting tool wear in drilling. For the development of predictive models, tool life tests were performed by drilling through holes on AISI 9840 steel parts, with a coated tungsten carbide drill of 8 mm of diameter and by using constant cutting parameters. Flank wear of the tool was monitored. A set of statistical features computed from the vibration signals, the acoustic emission signals, the power signals and the torque signals constitute the input of the algorithms. The classification accuracy was 88% and 91% for Neural Network and Random Forest models respectively. In order to correctly define the tool replacement policy during production, the developed Random Forest model has been implemented in an industry, through production management software, achieving promising results. [ABSTRACT FROM AUTHOR]

Geometric modeling techniques presented in this study target the important problem of improving the quality of milling processes through simulation-assisted research and development. Geometric modeling capabilities include generating the tool swept volumes for each tool motion, subtracting these from a dynamically changing in-process workpiece model, and calculating the instantaneous cutter engagements. In this study, the workpiece has been represented with a series of evenly distributed vectors oriented in three directions of the Cartesian coordinate system. Thus, sampling in multiple directions, called the triple-ray rap-based method, overcomes the problems associated with z -Map-based techniques, in which sampling only along one direction misses surface portions such as sharp edges and vertical walls. In addition, since the tool-swept volumes are regarded as envelope surfaces in the vector model-based techniques, the intersection calculations have been reduced to line/surface intersections. In the tool engagement extractions, the tool removal volumes represented by the vectors have been utilized instead of the in-process workpiece to reduce memory usage and the program runtime. Later, these removal volumes were voxelized at the predetermined resolutions for performing the arc and voxel intersections. In this research, the milling tools have been modeled as the surface of revolutions. Thereby, the method has been broadened to use more than just the APT type cutters, and it can be generalized for other types of cutting tools. [ABSTRACT FROM AUTHOR]

Additively manufactured cutting tools have thus far proven unsuccessful in machining difficult-to-cut materials like titanium. To the knowledge of the authors, this paper demonstrates, for the first time, the form turning of Ti6Al4V with WC-Co tools printed using laser powder bed fusion (LPBF), without any material-related post-processing. Following an investigation into LPBF parameters to optimize WC-Co properties, numerical modelling was utilized to design and analyse said tools, which were then printed, finish-ground, and tested. This advance was facilitated by the enabling capabilities of LPBF, which elevated tool performance by incorporating features that are critical to machining titanium, such as cooling fins and streamlined internal coolant channels. [ABSTRACT FROM AUTHOR]

The work-hardening and low thermal conductivity characteristics of SS304 had always been a challenge to machine it easily with better tool life and surface finish. The type of coolant, its temperature and surface coated inserts plays a pivotal role in machining the hard materials. A number of experiments were performed with a TiCN and tungsten carbide inserts in combination with soluble/synthetic coolant at ambient temperature and at 0oC TiCN-coated cemented carbide insert with synthetic coolant at 0°C is recommended for machining as per the results obtained through this research work. It was found that TiCN-coated inserts used for machining SS304 with synthetic coolant at 0°C provide better tool life, less tool wear, improved surface finish and low heat generation. The tool life was enhanced approximately by 75%, 20% reduction in maximum temperature generation and 50% improvement in surface finish of workpiece. [ABSTRACT FROM AUTHOR]

Trochoidal milling has been developed to extend the cutting tool life as compared to conventional milling. It is widely used in the machining of slots and corners of molds and dies. There are several tool paths typically used in trochoidal milling such as true, circular, variable-feed, and variable-step trochoidal tool paths. However, these paths suffer from low material removal rates, low surface qualities, high CPU processing times, and/or the requirement of high-dynamic machine tools. Elliptical trochoidal tool path showed its capability to improve the material removal rate, but the expected low surface quality of the produced slot. In this paper, the elliptical tool path will be analyzed analytically and experimentally. The effect of elliptical tool path on material removal rate, cutting forces, walls waviness, and surface roughness have been investigated. A novel linear elliptical-based tool path has been proposed to enhance the elliptical tool path performance by improving both material removal rate and surface quality. A Performance index has been utilized to evaluate the performance of these processes. An analytical model for the local maximum chip thickness in elliptical tool path has been conducted to correlate this path with the cutting forces. The slot walls waviness has been modeled based on the cutting tool path geometry and validated experimentally with error less than 11%. The experimental results showed that the elliptical tool path improved the material removal rate by 11%, with a slight reduction in the maximum resultant cutting force by 3%. On the other hand, the walls waviness and surface roughness have been increased by 45% and 38% respectively as compared to the typical true trochoidal tool path. The introduction of linear paths at the elliptical path sides in the linear-elliptical tool path improved the performance index about 18 times by improving the material removal rate, waviness, and surface quality by 5%, 300%, and 74% respectively, without a significant effect on cutting forces. Therefore, the novel linear-elliptical paths are promising tool paths in increasing the performance of trochoidal milling due to the improved material removal rate, walls waviness, and surface quality, without a significant effect on cutting forces, which will improve the process machinability and cost-effectiveness. [ABSTRACT FROM AUTHOR]

The effect of process damping in machining is an effective influencing factor for the suppression of regenerative chatter vibrations. Although process damping is typically associated with process configurations at low cutting speeds, the use of tools with flank face chamfers is a suitable strategy to specifically increase process stability over a wide range of cutting speeds. In this contribution, damping potentials of different chamfer designs were evaluated. Using an analogy setup providing defined, high-frequency tool oscillations, fundamental interrelations of the dynamic chamfer-workpiece contact were characterized. The results illustrate the impact of specific chamfer designs on process damping and the significance of the elastic material response on the tool-workpiece interaction. [ABSTRACT FROM AUTHOR]

Namib IV (S23° 44.829', E14° 19.720') is frequently cited, as it is one of few Earlier Stone Age sites in the Sand Sea of the Namib Desert. The site was first investigated in 1978 by Myra Shackley, who described 582 artifacts on the surface of a pan as representing an Acheulean butchery site. Descriptions of the artifacts, their number, and area were inconsistently reported. Recently rediscovered, the site of Namib IV is a rare example of a tool-rich and fossil fauna-bearing pan system in the Namib Sand Sea. This project aims to investigate when, how, and under what environmental conditions hominins utilized these landscapes. This article presents the first archaeological research conducted at the site in over 40 years. Typological and technological data was collected from surface-exposed artifacts and large cutting tools (LCTs) and compared to Shackley's assemblage. Data demonstrate that her collection is representative of the Namib IV site and raise many new questions about the original research and the site. [ABSTRACT FROM AUTHOR]

Surface roughness is important for the part because it has a direct influence on its functional role. Starting from this consideration, researching the roughness of the machined surfaces of the parts is very important to be able to anticipate their behavior in operation. The roughness of the surfaces has a significant impact on the operation of the parts, being able to influence the resistance to wear, resistance to fatigue, lubrication and friction. Thus, it is very important to establish the processing conditions in order to obtain the appropriate roughness. To meet these requirements, the geometry of the cutting tool and the dynamic phenomena that accompany a machining process must be taken into account. Thus, to carry out the research, steel samples S235- EN 10025-2 - Φ 150mm were used. The experimental design of the factorial plans established that the research should carry out a number of 8 experiments consisting of the processing with the classic cutting tool T01 and the intelligent cutting tool T02 of the S235 steel samples, so that after the processing the roughness was measured for each sample separately and also within the framework of the research an analysis of the surface profiles was carried out, a series of curves were drawn for the samples studied within the framework of the research as follows: curved profile; filtered profile; Abbott-Firestone curve; Also, the obtained experimental results were processed statistically by the method of multiple regressions. [ABSTRACT FROM AUTHOR]

Mechanical machining by chipping occupies an important place among the processes for generating parts used in industry, they occupy a volume of about 70% of the total volume of produced parts and among all mechanical machining processes by chipping, the machining process by turning it is widely used to generate the surfaces of the produced parts. Starting from the premise that the modern development of the machining industry is based on principles such as: manufacturing flexibility (referring to the machine tool-tool), the quality of the surfaces obtained and the manufacturing cost price (which must be as low as possible), in order to could satisfy these principles, the cutting tool also contributes decisively, therefore it is necessary to use cutting tools with an optimal geometry during processing. The designed geometry of cutting tools refers to the constructive geometry, but during cutting operations the constructive geometry becomes a functional one. Thus, the functional geometry of the tools is the one that greatly influences the machining process of the parts and implies the quality of the obtained parts. Currently, special attention is paid to the constructive geometry of the cutting tool, without taking into account the fact that the functional geometry of the tool also depends on the following parameters: cutting speed, feed speed and dimensions of the processed piece. It should be mentioned that due to the chipping process being carried out with tools with inappropriate geometry, additional dynamic phenomena (vibrations) appear, generating negative effects on the results obtained. Thus, during the research, a classic T01 cutting tool and an intelligent T02 cutting tool were used for turning with transverse feed of S235- EN 10025-2 - Φ 150mm steel scraps (that is, it has an elastic element mounted under the cutting plate with the role to maintain the optimal functional geometry of the cutting tool in order to reduce the dynamic effects (vibrations) that accompany the cutting process. The number of processed samples was established by applying the method of factorial experiments, so that for each processed sample the vibration amplitude was measured and analyzed by applying the F.F.T. method so that the obtained results were statistically processed by multiple regression analysis methods. [ABSTRACT FROM AUTHOR]

The thermal load of the cutting tool is an important process state parameter that directly influences tool wear and thus the dimensional accuracy of the workpiece. Due to limited accessibility and sensor configuration, it is difficult to monitor tool temperature during the machining process, hence cutting parameters cannot be optimally adjusted to the thermal loads. In order to solve this problem, analytical models of tool temperature are increasingly applied in practice. So far, the available temperature models only consider dry process conditions, and the effects of convective cooling in non-continuous heat sources have not been addressed. Therefore, a new 3D temperature model for cutting tools that incorporates the cooling effect is proposed in this work. This model has a simple expression and is easy to solve. To evaluate the applicability of the model, orthogonal cutting tests were performed under both dry conditions and with high-pressure cutting fluid supply. The accuracy of the model for temperature prediction has been demonstrated by comparing the experimental and simulated temperature distributions. In addition, the thermal properties of the tool material on the temperature development were also analyzed. [ABSTRACT FROM AUTHOR]

Metal cutting is a necessary operation in any production industry. Rapid production has become a necessity as a result of recent trends in high-speed machining and automation. The demand for more sophisticated and advanced cutting tools has significantly increased in recent years. The properties of alloy metals can be improved by applying a thin film to enhance or reduce specific properties based on product needs. The effect is being able to operate the tool at a higher cutting speed, feed rate, depth of cut, and longer tool life, with a dry machining possibility for the end-user when cutting tools are appropriately coated and performing as intended using thin films. Thin coatings improve cutting tool wear resistance, oxidation resistance, friction reduction, resistance to metal fatigue, as well as thermal shock resistance. On the other hand, thin film morphology and stability are crucial challenges in cutting tool applications as thin film morphology is heavily dependent on deposition techniques. As a result, based on the available studies, this article presents a critical review of deposition coating techniques, characterisation methods, and evaluation techniques in order to prevent excessive damage and improve the mechanical properties of cutting tools. The anticipated outcomes of this review can be used as a guide to help researchers understand various coating techniques and their effects on cutting tool properties. [ABSTRACT FROM AUTHOR]

A constant concern in the field of mechanical engineering is finding the balance between the costs of machining components and the costs of replacing worn processing devices. Determining the optimal moment, to replace processing tools, involves describing their resilience, due to the stress in use, through an appropriate statistical model, which statistically reproduces the behavior under extreme demands. One such model is the Alpha distribution proposed by Drujinin in 1967. The first applications were in engineering practice, in the field of metal processing, the model best describing the behavior of the processing device to the resistance of the processed metal, the stress exerted on the cutting tool, as well as its subsequent resilience. Along with the bibliographic investigation and the presentation of the distribution's genesis from a historical point of view, this article presents the estimation of the model's main parameters, the establishment of the lower tolerance limit and a practical application. Somehow forgotten in the specialized literature, the Alpha distribution has numerous applications, exceeding the boundaries of mechanical engineering, such as the modeling of effects, but especially macroeconomic resilience processes following crises, such as the 2008 global slump or the one generated by the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

Surface integrity has become an important basis for evaluating quality of the manufacturing components. The rapid tool wear leads to manufacturing costs incensement and surface integrity deterioration. To eliminate irreparable surface damage due to tool wear, more stringent tool failure criteria than ISO standards need to be applied. This work investigated the progressive mapping of surface integrity mapping based on tool wear state and novel tool failure criterion of multi-objective surface quality optimization during turning Ti-6Al-4V. Firstly, the progressive mapping of surface integrity in the whole tool life cycle under different cutting parameters was established. Then, based on the high-quality surface as the driving goal, the tool failure criterion of multi-objective surface quality optimization was proposed by response surface methodology analysis. Experimental results indicated that tool wear was a major determinant of surface integrity, which surface topography, microstructure and mechanical properties presented a gradual change as a result of increased tool wear. According to tool failure criterion, the optimization solution with the desirability value of 0.530 were v = 170.2 m/min, f = 0.118 mm/rev and VB = 0.188 mm. The predicted results were in good agreement with the verification experiment. This work provided basic support for high quality and low manufacturing costs. [Display omitted] • Progressive surface integrity mapping in the whole tool life cycle was established. • Novel tool failure criterion for multi-objective optimization of surface quality was proposed. • Surface integrity evolved with the increase of tool wear. • The optimization solution with desirability value of 0.530 was v = 170.2 m/min, f = 0.118 mm/rev and VB = 0.188 mm. [ABSTRACT FROM AUTHOR]

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This paper presents a hybrid Smoothed Particle Hydrodynamics (SPH) – Finite Element Method (FEM) solver for metal cutting simulations on Graphics Processing Units (GPU). For the first time in chip formation simulation, the heat transfer between an SPH model of the workpiece, and a transient FEM temperature model for the cutting tool, is established. For validation, the performance of the modeled thermal contact between two numerical domains is compared with a commercial FEM software. The sensitivity of the implemented SPH-FEM contact parameters is investigated for the first time and further insights into the thermal modeling of cutting simulations are generated. Overall, the newly developed hybrid model saves the computational time on the cutting tool side in the pure SPH method and enables more efficient high-fidelity cutting simulations. By clearly defining the thermal contact at the tool-chip interface, the simulated tool surface temperature agrees well with the experimental measurements in the literature. [ABSTRACT FROM AUTHOR]

The development of cutting tools requires the knowledge of tribological phenomena at the tool – workpiece contact area. This knowledge is in dearth particularly for difficult-to-cut alloys like gamma titanium aluminide (gamma – TiAl alloys). Therefore, this article is an attempt to plug the gap and aid the development of cutting tools for gamma – TiAl alloys. To this end, friction, adhesion, and coating wear between AlTiSiN coated cemented carbide tool and Ti-48Al-2Cr-2Nb (Near lamellar), Ti-48Al-2Cr-2Nb (Duplex), and the most used titanium alloy of Ti-6Al-4V (alpha – beta) were experimentally derived. A Pin-on-Cylinder (PoC) tribometer with contact conditions corresponding to commercial machining conditions was used with dry, flood(EML), and two MQL lubricants. Additionally, the heat generated and partitioned between the pin and workpiece was quantified to assess the thermal exposure to the coatings. The results showed that Ti-6Al-4V had approximately 50% higher apparent friction coefficient than the Ti-48Al-2Cr-2Nb alloys. Interestingly, the friction coefficients of Ti-48Al-2Cr-2Nb alloys were nearly consistent across the entire test matrix. Notably, the change in the microstructure from near lamellar to duplex did not elicit any qualitative or quantitative change in the friction profile of Ti-48Al-2Cr-2Nb alloys. The contact pressure proved to be the statistically significant property influencing friction evolution inversely for Ti-6Al-4V alloy and directly for Ti-48Al-2Cr-2Nb alloys. The results showed higher probability of coating wear in dry conditions as opposed to the flood and MQL lubricants. [Display omitted] [ABSTRACT FROM AUTHOR]

Laser powder bed fusion (L-PBF) is an additive manufacturing (AM) technology which is utilised to produce parts in a layer-wise manner from a digital 3D model. Currently there is a growing interest in producing cutting tools with L-PBF. In order to successfully utilise L-PBF to produce cutting tools from hard materials like tungsten carbide cobalt, certain physical and material properties need to be achieved. However, inherent defects that are associated with the L-PBF process also need to be addressed. Material properties of the final parts and defects such as cracking, porosity, and delamination can be strongly dependent on each single laser-melted track and/or each single layer. The aim of this study was to explore various methods for L-PBF process parameter optimisation and highlight the considerations required when performing specific process optimisation on WC-12wt%Co powder with L-PBF. The effects of the process parameters such as laser power, scanning speed, and hatch spacing, on density, hardness, and cobalt content were studied. In this paper, a single-track optimisation approach was tested and the various results and considerations for applying this approach are reported. [ABSTRACT FROM AUTHOR]

We present the first techno-functional examination of backed knives from the southern African Acheulean. Our results suggest that they were opportunistically produced, although they demonstrate a unique ergonomic design that may have increased their efficiency in subsistence activities. Moreover, the frequency of backed knives at Wonderboom may be associated with possible meat harvesting at a nearby gap (Wonderboompoort) in the Magaliesberg range, which formed a bottleneck for animal herds migrating across major biome boundaries in the deep past. The Wonderboom knives might have been made on an ad hoc basis to augment butchery practices. [ABSTRACT FROM AUTHOR]

The implementation of soft computing procedures in tool wear prediction and optimization is a significant process in machining operations for sustainable manufacturing of components with quality finishing. Tool wear is one of the response parameters that leads to a high rate of production cost due to constant tool substitution during machining, mostly when machining hard metals that are difficult to machine. With these challenges, several techniques have been put in place to optimize and predict tool wear rates, including turning, milling, grinding, shaping, and drilling. This study focuses on the evaluation of existing literature that employs soft computing procedures such as ANN-GA, ANFIS, ANFIS-PSO, and ANFIS-FCM in the prediction of cutting tool wear rate during machining processes. From the different study reviews, the results show that the application of these soft computing procedures significantly improves tool life during the manufacturing process by employing the optimal machining parameters in an eco-friendly nano-lubrication environment. This study also points out the challenges currently faced with these soft computing techniques and gives a sustainable way forward as a recommendation to improve the manufacturing process. [ABSTRACT FROM AUTHOR]

The present study investigates the microstructure of monolayer TiAlSiN and bilayer AlTiN/TiAlSiN coatings deposited on WC-Co inserts through magnetron sputtering. Further, a comparative study on the tool life and wear characteristics of uncoated, monolayer and bilayer coated inserts was performed through dry turning of tempered EN-8 steel under extreme cutting conditions. The TiAlSiN coating showed a dense fine morphology whereas the AlTiN/TiAlSiN coating showed a mixed morphology with a columnar structure for the intermediate layer of AlTiN followed by a dense nanocrystalline structure for the top layer of TiAlSiN. The dry turning experiments show that the major form of wear mechanism observed during machining was crater wear. Both monolayer and bilayer coated inserts showed promising cutting performance and the bilayer coated inserts showed better tool life than the monolayer coated inserts under most of the cutting conditions. [ABSTRACT FROM AUTHOR]

The machinability studies for the Inconel 718 alloy with the coated cemented carbide cutting tool having 0.4 and 1.2 mm nose radius, varying cutting speeds (65, 81, 95 and 106 m/min) with a constant feed rate of (0.15 mm/rev) and a depth of cut (0.2 mm) were conducted. The cutting force decreases with the increase in cutting speed due to the thermal softening of the work surface at a high temperature. With the increase in nose radius a decrease in the cutting force is observed due to the increase in the cutting edge of the tool. The formation of residual stress has a profound effect on the change in the tool morphology during the machining of the alloy. Furthermore, the chip analysis in terms of chip morphology is carried out in detail. The detailed tool fracture studies are conducted and are explained for the various machining processes. [ABSTRACT FROM AUTHOR]

Computer Numerical Controlled (CNC) machines, as one of the digital fabrication technologies, can create various textures as milled surfaces. The geometrical properties of these textures depend on various parameters set by the designer. This paper focuses on CNC cutting tools, tool paths, and cut depth to understand their roles in generating different surface textures on a (12.7 × 12.7)cm2 panel surface. 3D Rhinoceros, and other plugins were used to study the texture created by two distinct CNC tools (ball and vee bits), two tool paths (plunge roughing and parallel), and various tool stepovers. The simulation studies focused on the solar radiation received by the panel surfaces and self-shadow cast by the surface texture. The results showed that each tool, tool path, and tool stepover had different effects on the panel surface solar control. Using vee-type bits increased the amount of radiation by 17% compared to the flat panel and using ball-type bits decreased it by 32%. [ABSTRACT FROM AUTHOR]

The wear behaviour of cutting tools can be significantly improved by a load-optimized design of the cutting edge microgeometry. Thereby, the knowledge of local mechanical stresses is necessary. The experimental-based modelling of mechanical stresses in the continuous cut was already investigated in previous work. In this paper, this method is adapted to the interrupted cut by considering contact lengths, process forces and process temperatures during tool entry and exit. The identified mechanical stresses and temperatures are used for a tool material specific cutting edge microgeometry design. [ABSTRACT FROM AUTHOR]

Application of additively manufacturing (AM) metals is growing rapidly; however, post-process finish machining is still required to improve dimensional accuracy and surface quality. Determining the high-strain high-temperature behavior of AM metals is critical in simulating finish machining, designing appropriate cutting tools, and predicting surface integrity. This paper investigated the machining characteristics of AM Ti-6Al-4V produced using powder bed fusion. High-strain high-temperature behavior of AM Ti-6Al-4V was determined numerically and used in simulating the process. Machining tests were performed in different directions with respect to the build orientation and chips were collected to examine the mechanic of chip formation. [ABSTRACT FROM AUTHOR]

Using cutting fluids has the potential to increase tool life and workpiece quality by reducing loads during cutting. However, cutting fluids lead to additional costs and environmental impacts. To effectively utilise cutting fluids, it is important to gain insights into their working mechanisms, in particular via direct observations of the tribology at the contact surfaces. This paper presents methods to investigate lubrication in cutting, focusing on a new approach for accessing the distribution of cutting fluids at the tool's rake face. This technique of visualising a lubricating film between chip and rake face allows to deeply understand tribological effects. [ABSTRACT FROM AUTHOR]

Conveyor belts play an essential role in mining, making belt splicing a critical operation in the maintenance process. Currently, this procedure is performed manually and can last up to 48 h, exposing operators to risks while performing the task. Additionally, the process is error prone, and the splicing quality depends directly on the maintenance team's expertise. As a first attempt to automate belt splicing preparation, the Instituto Tecnológico Vale, together with the Brazilian mining company Vale S.A., is investigating the use of a rotary rubber cutting tool attached to a robotic manipulator arm. In this work, we propose a new multistep concept for automating the traditional belt splicing process. Our proposal includes a virtual environment simulator, allowing the verification of critical components of the system prior to real-world execution: the appropriate sensor set for modeling the conveyor belt and validation of the manipulator motions to remove the rubber using the cutting tool. After virtual validation, we developed two instrumented test benches for experimental validation: a belt modeling prototype using a small-scale industrial manipulator and a customized instrumented bench with a cutting tool prototype, developed to evaluate the efforts involved in the rubber removal process. This paper focuses on rubber cutting bench design and modeling to calculate the resulting forces and moments applied to the robotic manipulator during the process. The simulated and preliminary real-world experiments have shown that the magnitude of these efforts is compatible with a robot working class with a 200 kg payload. In this sense, the proposed robotic and mechanical system design is a feasible first step to fully automating belt splicing preparation within mining environments. [ABSTRACT FROM AUTHOR]

Cutting tools can vibrate with frequencies of up to a few kHz with amplitudes ranging from a few µm to hundreds of µm. To characterize these vibrations using vision-based modal analysis methods, video of vibrating tools must be acquired at high speed and resolution. High speed acquisition will ensure modes are temporally resolved without aliasing, whereas high resolution acquisition ensures that the pixel size is small enough to resolve small motion. However, since most digital cameras trade speed for resolution, estimating small motion of high frequency modes becomes difficult. To address this issue, this paper presents new methods to estimate small motion from video of vibrating cutting tools. Two methods are illustrated on a video of a slender end mill. One is hardware-based, and the other is software-based. In the hardware-based method, we use combinations of extension tubes and a reverse ring fitted with a standard lens to achieve a pixel size of as less as 1.3 µm. In the software-based method, we leverage the capability of intensity- and phase-based motion registration methods to detect small subpixel level motion, even when the pixel size is 83 µm. In both methods we use the object's own features to detect and register motion, thus overcoming the limitation of digital image correlation schemes that need markers for target tracking. Modal parameters evaluated from motion estimated with both methods are found to agree with those extracted from twice integrated accelerations. Since methods proposed herein proffer new ways to register small oscillatory motion, we believe that our findings will further help leverage the adoption of vision-based modal analysis methods in machine tool systems as an alternative to the more traditional experimental modal analysis procedures. [ABSTRACT FROM AUTHOR]

Recently surface textured tools have gained much attention as sustainable machining techniques in enhancing the tribological characteristics at tool and workpiece interfaces. However, minimal research is conducted to inspect the influence of bio-inspired textured tool cutting performances. Therefore in the current investigation, the influence of variation in the rake and flank faced bio-inspired crescent textured tool parameters such as radius, edge distance, depth, and center distance on the cutting performance of difficult to machine martensitic AISI 420 steel has been examined. The turning operation has been conducted at a constant depth (a p) = 0.3 mm, cutting speed (v c) = 315 m/min and feed (f z) = 0.14 mm/rev. The bio-inspired crescent-shaped textured tool indicated a reduction in feed force, tangential force, chip-tool contact area, flank wear and chip reduction coefficient compared to the conventional tool. The built-up edges, chipping, and abrasion are common tool wear mechanisms noticed on the tool surface. It is noticed that out of different texture parameters, center distance of the crescent textured tool played a vital role in improving the machining performance with minimum feed force, tangential force, contact area, flank wear, and chip reduction coefficient of 49 N, 118 N, 7.96 E + 05 µm2, 103 µm and 1.695 is observed using the textured tool of center distance of 80 µm. These research findings are significant for increasing the bio-inspired textured tool applications with superior tribological characteristics. [Display omitted] • Bio-inspired crescent textured tool performed superior compared to conventional tool. • Texture parameters plays vital role in improving machining performances. • BUE, abrasion, and chipping are common tool wear mechanisms observed. • Textured tool showed lower chip reduction coefficient. [ABSTRACT FROM AUTHOR]

The paper presents the fixtures with movably mounted turning and drilling cutting tools. The fixtures were developed on the principle of oscillating tooltip similar to the principle of the ultrasonic vibration-assisted machining process. However, presented fixtures do not need an electricity source and utilize mainly forced and self-excited oscillations. In general, the tool vibrations during the cutting process are recognized as a negative phenomenon as it causes a shortening of the tool life and worsens the roughness of the machined surfaces. However, a deeper understanding of the cutting process proposes possible positive effects of tool vibration in terms of chip shapes, flank wear, chip volume coefficient, and quality of the machined surface. Experimentally obtained dependence of mentioned quantities is provided in the paper. [ABSTRACT FROM AUTHOR]

Since most of the parts in the machine building industry are made using machining processes, under these conditions it is necessary to optimize the machining processes in order to achieve the reduction of manufacturing costs and to provide an increased lifetime of the manufactured products. In this context, the development of new cutting tools with superior characteristics or better performance than the existing ones is required. The cost of cutting tools currently used in the manufacturing industry is significant and greatly influences the total manufacturing cost and therefore the final price of the product. In the turning process, the most important parameters that influence the roughness of a surface are the parameters of the cutting regime and the geometric parameters of the cutting tool. Due to the complex structure of the turning processes, a series of dynamic parameters appear that can influence the roughness of the surfaces. During machining, vibrations occur due to the lack of rigidity of the machine tools and the way the cutting tools are fixed, and due to the change in cutting conditions during the cutting process. Machining processes are generally accompanied by variations in the cutting forces determined by an improper functional geometry of the tool that can have direct influences on the machining results. The lack of an optimal functional geometry of the cutting tool causes its rapid wear with effects on the increase of cutting forces and vibrations. In order to avoid such effects, it is necessary to identify the best constructive variants of tools that allow a control of the dynamics of the machining processes by chipping. [ABSTRACT FROM AUTHOR]

The rapid development of advanced high throughput technologies and introduction of high resolution "omics" data through analysis of biological molecules has revamped medical research. Single-cell sequencing in recent years, is in fact revolutionising the field by providing a deeper, spatio-temporal analyses of individual cells within tissues and their relevance to disease. Like conventional sequencing, the single-cell approach deciphers the sequence of nucleotides in a given Deoxyribose Nucleic Acid (DNA), Ribose Nucleic Acid (RNA), Micro Ribose Nucleic Acid (miRNA), epigenetically modified DNA or chromatin DNA; however, the unit of analyses is changed to single cells rather than the entire tissue. Further, a large number of single cells analysed from a single tissue generate a unique holistic perception capturing all kinds of perturbations across different cells in the tissue that increases the precision of data. Inherently, execution of the technique generates a large amount of data, which is required to be processed in a specific manner followed by customised bioinformatic analysis to produce meaningful results. The most crucial role of single-cell sequencing technique is in elucidating the inter-cell genetic, epigenetic, transcriptomic and proteomic heterogeneity in health and disease. The current review presents a brief overview of this cutting-edge technology and its applications in medical research. [ABSTRACT FROM AUTHOR]

The increasing demand for cost-efficient, high-quality machined products has led to a requirement for cutting tools that are able to provide a long tool life even when operating under extreme cutting conditions. Hard thin-film coatings deposited on tool substrates have been at the forefront of dealing with such demands. Such coatings provide cutting tools with properties like increased hardness, wear resistance, oxidation resistance, resistance to thermo-mechanical shocks, lower friction coefficient, etc. Vapour deposition techniques are widely used to deposit these thin films. Any variation in process parameters during deposition affects the properties of a coating and hence is a crucial factor to be considered. This review paper discusses some of the commercially used deposition methods, their effects on the crystal morphology, and the thermal and mechanical properties obtained in these coatings. Finally, this paper will also cover some of the recent advancements in hybrid coating technology, nanostructured coatings, and the prospects of sustainable machining. [ABSTRACT FROM AUTHOR]

Modal parameters characterize how tools vibrate. Correct evaluation of modal parameters depends on how signals are sampled. Since tools can vibrate with frequencies of up to several kHz, respecting the Nyquist criterion requires sampling potentially at tens of kHz. This is easy enough with modern data acquisition systems. However, if/when using modal parameters to monitor condition of tools, transmitting, storing, and processing large data sets becomes difficult. Moreover, when extracting modal parameters using newer vision-based methods, it may not always be possible to acquire high resolution images at rates that avoid aliasing. This paper present solutions to address such cases by recovering modal parameters from signals sampled potentially below the Nyquist limit. No a priori knowledge of the system order is assumed, and folding properties of signals are leveraged to recover parameters from fractionally uncorrelated signals using notions of set theory. To aid recovery, we suggest formal procedures to group candidates of likely modes together and resolve the case of modes being potentially confounded. Special spatiotemporal decoupling properties inherent to modal analysis are leveraged to recover eigenvectors from potentially aliased signals. Recovery is illustrated using the eigensystem realization algorithm. Numerical experiments with systems of different orders, of signals with noise, and of systems in which likely modes can be confounded with other likely candidates are designed to test robustness of the method. Those findings guide experiments with measured accelerations and video of an end mill. Results confirm that parameters recovered using proposed methods agree with those extracted from accelerations and videos sampled properly. [ABSTRACT FROM AUTHOR]

Laser surface engineering of cutting tools is used to improve the performance of cutting processes via altering the material interaction between the tool surface and workpiece. Laser processing applied to cemented carbide cutting tools can induce various thermal and mechanical surface defects including porosity, splatter, cracks, balling, spherical pores, voids, and dissociation. Those defects could be detrimental to the integrity of the tool, therefore parametric optimization is crucial to limit and control possible post-processing defects. This study aimed to identify and classify surface defects in post laser processed carbides to better understand the relationship between parameters and resultant surface integrity. A region convolutional neural network (R-CNN) was trained for identification and classification of these surface defects using scanning electron microscopy images (SEM) as inputs. The R-CNN provided a quantitative analysis of each defect with an average accuracy of 91%. Using the data from the R-CNN matched with the laser parameters, a back propagation neural network (BPNN) was trained to act as a predictive network. The network predicts the number and proportion of defects when the tool grain size, roughness and laser parameters are entered. The accuracy of this predictive network was 96.6%. The effect of individual laser parameters on the surface integrity is estimated by this method, enabling the optimization of laser processing in cutting tools. For the first time this can be used to predict tool performance based on tool's surface integrity. [ABSTRACT FROM AUTHOR]

In high-performance machining processes, the cutting tools are an essential factor with regard to the resulting quality of the manufactured components and the efficiency of the entire production chain. For the machining of advanced materials with high hardness and brittleness, tools combining cutting and abrasive machining with high wear-resistance were developed and investigated. Focusing on honing and grinding, the development of application-adapted tools, their coating characteristics, cutting behavior and their improvements of performance are presented. The results demonstrate high wear resistance and high material removal rates in combination with significantly reduced surface roughness. [ABSTRACT FROM AUTHOR]

Milling of fibre-reinforced plastics is a challenging task. The highly abrasive fibres lead to high tool wear and coating failures, which cause increasing process forces and temperatures. Machining with a worn tool, in turn, can result in unwanted workpiece damages such as delamination or fibre protrusion. Reliable monitoring of the process must therefore be able to detect damages to the milling tool and the workpiece alike. The presented process monitoring approach measures the acoustic emission generated by the milling tool cutting edge entering the workpiece with a sensor attached to the tool holder. Specific acoustic emission frequency spectra and waveforms are emitted in the cutting zone for different tool wear states. Coating failures as well as other acoustic emission events due to workpiece damages can be robustly detected and distinguished by feature extraction and signal processing as well. The developed setup, the monitoring parameterisation techniques and signal processing algorithms as well as experimental and monitoring results are presented and discussed in this paper. [ABSTRACT FROM AUTHOR]

• Fundamental understanding of input factors for maximising cleaning rate and minimising energy requirements. • Compositional surface integrity after laser cleaning. • New specific energy consumption and processing rate model. • High laser pulse frequency as a key tool for rapid cleaning and low energy consumption in support of low carbon manufacturing. Energy consumption and performance optimisation of laser cleaning for coating removal. [Display omitted] Selective removal of coatings by lasers can facilitate the reuse of coated tools in a circular economy. In order to optimise and control the process, it is essential to study the impact of process input variables on process performance. In this paper, coating removal from tooling was carried out using a picosecond a pulsed fibre laser, in order to investigate the effects of laser pulse energy, pulse frequency, galvo scanning speed and scanning track stepover. A fractional factorial design of experiments and analysis of variance was used to optimise the process; considering cleaning rate, specific energy consumption and surface integrity as assessed by changes in surface roughness and composition of the tooling after laser cleaning. The results shows synergy between cleaning rate and specific energy with the laser pulse frequency and galvo scanning speed as the two most significant factors, while the laser pulse energy had the greatest contribution to changes in surface composition. Based on extensive experiments, the relationship between processing rate and system specific energy consumption was mathematically modelled. The paper contributes a new specific energy model for laser cleaning and provides a benchmark of the process energy requirements compared to other manufacturing processes. Additionally, the generic scientific learning from this is that the rate of energy input is a key tool for maximising cleaning rate and minimising specific energy requirements, while the intensity of energy applied, is a key metric that influences surface integrity. More complex factors, influence the surface integrity. [ABSTRACT FROM AUTHOR]