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In machining, the tool condition has to be monitored by condition monitoring techniques to prevent damage by the use of tools and the workpiece. Cutting forces acting on the tool between zero and maximum values cause the cutting edge to crack and break. Predetection of this situation in the cutting tool is very important to prevent any negative situation that may occur. This study introduces a vibration-based intelligent tool condition monitoring technique to detect involute form cutter faults such as tool breakage at different levels during gear production on a milling machine. Machine learning algorithms such as artificial neural network, random forest, support vector machine, and K-nearest neighbor were used to detect the broken teeth and its level of breakage. According to the results obtained, it was observed that all the algorithms are successful in detecting faults in different teeth; also they have identification advantages according to different fault levels. In addition, the time and frequency domain analysis and continuous wavelet transform were used to determine the local faults. The developed machine learning-based detection performances compared the classical time and frequency domain analyses and continuous wavelet transform to prove the effectiveness and precision of the proposed methods. The results showed that all of the machine learning techniques have satisfactory performance to be used as fast and precise detection tools without complex calculations for detecting tool breakage.

The digital industrial revolution calls for smart manufacturing plants, i.e. plants that include sensors and vision systems accompanied with artificial intelligence and advanced data analytics in order to meet the required accuracy, reliability and productivity levels. In this paper, we introduce a surface analysis and classification approach based on a deep learning algorithm. The approach is intended to let machining centres recognise the adequacy of process parameters adopted for the milling operation performed, based on the phenomenological effects left on the machined surface. Indeed, the operator will be able to understand how to change process parameters to improve workpiece quality of subsequent parts by a reverse engineering procedure that reconstructs the process parameters that generated the analysed surface. A shallow convolutional neural network was proposed to work on surface image patches based on a limited training dataset of optimal and undesired cutting conditions. The architecture consists of a series of 3 stacked convolutional blocks. The performance of the proposed solution was validated through 5-fold cross-validation, measuring the mean and standard deviation of the f1-score metric. The algorithm arrived at outperformed the best state-of-the-art approach by 4.8% when considering average classification performance.

Nickel-titanium (NiTi) shape memory alloys (SMAs) undergo phase transformation between austenitic and martensitic phases in response to applied thermal or mechanical stress, resulting in unique properties and applications. However, machinability often becomes challenging due to property and temperature sensitivity attributes. The use of chilled air to influence machinability in macro-milling was investigated in this study. Other than that, differential scanning calorimetry (DSC) was used to determine the temperature of phase transformation. The results showed that milling with chilled air and minimal lubrication significantly improved machining performance by reducing tool wear and burr formation. Moreover, surface quality has also improved significantly. A notable discovery is that the machining process can change the critical conditions for phase transition, enabling new performance capability of tuning material hysteresis.

The present work presents the development of a numerical model to assess the machining performance in milling of a 15-5PH stainless steel. At first an experimental campaign was conducted using PVD coated TPUN inserts under three levels of cutting speed and feed: 100-170-240 m/min & 0.25-0.35-0.45 mm/rev. Forces were recorded using a Kistler 9257A dynamometer. For each experimental test, chips were mounted and polished to evaluate the chip thicknesses and contact lengths measured on inserts’ rake face. Regarding the numerical simulation, a 2D Arbitrary-Lagrangian-Eulerian (ALE) was then developed in the study. A tool motion was implemented to mimic the chip thickness evolution occurring during the milling process. These simulations allowed to numerically predict the chip thicknesses, contact lengths and cutting forces which were further compared to the experimental data.

Duplex stainless steels are being used on applications that require, especially, high corrosion resistance and overall good mechanical properties, such as the naval and oil-gas exploration industry. The components employed in these industries are usually obtained by machining, however, these alloys have low machinability when compared to conventional stainless steels. In this work, a study of the wear developed when milling duplex stainless-steel, LDX 2101, is going to be presented and evaluated, employing four types of milling tools with different geometries and coatings, while studying the influence of feed rate and cutting length in the wear of these tools. Tools used have been provided with two and four flutes, as well as three different coatings, namely: TiAlN, TiAlSiN and AlCrN. The cutting behavior of these tools was analyzed; data relative to the cutting forces developed during the process were obtained; and roughness measurements of the machined surfaces were executed. The tools were then submitted to scanning electron microscope (SEM) analysis, enabling the identification of the wear mechanisms that tools were subjected to when machining this material, furthermore, the early stages of these mechanisms were also identified. All this work was done with the goal of relating the machining parameters and cutting force values obtained, identifying, and discussing the wear patterns that were observed in the coating and tools after the milling tests, providing further information on the machining of these alloys., The present work was done and funded under the scope of the project ON-SURF (ANI | P2020 | POCI-01-0247-FEDER-024521, co-funded by Portugal 2020 and FEDER, through COMPETE 2020-Operational Programme for Competitiveness and Internationalisation. F.J.G. Silva also thanks INEGI-Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Indústria, due to its support. The authors would like to thanks to Dr. Rui Rocha from CEMUP (Porto, Portugal), due to his active collaboration in getting the best SEM pictures, helping with his critical analysis of some phenomena. Authors also would like to thank Ing. Ricardo Alexandre due to is extremely important role in providing all the coatings through TEandM company, and also Ing. Nuno André, for providing the substrate material and uncoated tools through the Inovatools company.

The residual stress state of the machined sub-surface influences the service quality indicators of a component, such as fatigue life, tribological properties, and distortion. During machining, the radius of the cutting edge changes due to tool wear. The cutting-edge rounding significantly affects the residual stress state in the part and the occurring process forces. This paper presents a tool wear prediction model based on in-process measured cutting forces. The effects of the cutting-edge geometry on the force behavior and the machining-induced residual stresses were examined experimentally. The resulting database was used to realize a Machine Learning algorithm to calculate the hidden value of tool wear. The predictions were validated by milling experiments using rounded cutting edges for different process parameters. The microgeometry of the cutting edge could be determined with a Root Mean Square Error of 8.94 μm.

Background Distortion arises during machining of metallic parts from two main mechanisms: 1) release of bulk residual stress (BRS) in the pre-form, and 2) permanent deformation induced by cut tools. Interaction between these mechanisms is unexplored. Objective Assess this interaction using aluminum samples that have a flat surface with variations of BRS, where that surface is subsequently milled, and we observe milling-induced residual stress (MIRS) and distortion. Methods Plate samples are cut from two kinds of large blocks, one kind stress-relieved by stretching and a second kind solution heat treated, quenched and aged. The BRS field in the plates is known from a recent series of measurements, being small in the stress relieved plates (within ±20 MPa) and large (±100 MPa) in the quenched plates, varying from tension to compression over the surface that is milled. MIRS is measured following milling using hole-drilling. Distortions of thin wafers cut at the milled surfaces are used to elucidate BRS/MIRS interactions. A finite element (FE) model and a strength of materials model are each used to assess consistency between wafer distortion and measured MIRS. Results Milling in samples with high BRS magnitude changes the directions of MIRS and distortion relative to the milling direction, with the direction of maximum curvature rotating toward or away from the milling direction depending on the sign and direction of BRS. High magnitude BRS was also found to increase the wafer peak arc height, nearly doubling the amount found in low BRS samples. Conclusion Measured residual stress and observed wafer distortion both show interactions between MIRS and BRS. Stress analysis models show that the differences in measured MIRS are consistent with the differences in observed distortion.

Using cutting fluids is considered in industrial applications and academia due to their increased influence over many aspects such as machinability, sustainability and manufacturing costs. This paper addresses the machinability perspective by examining indicators such as roughness, cutting temperature, tool wear and chip morphology during the milling of mold steel. A special type of steel is Nimaxm which is a difficult-to-cut material because of its high strength, toughness, hardness and wear resistance. Since mold steels have the reverse geometry of the components produced by this technology, their surface quality and dimensional accuracy are highly important. Therefore, two different strategies, i.e., dry and minimum quantity lubrication (MQL), were chosen to conduct an in-depth analysis of the milling performance during cutting at different cutting speeds, feed rates and cutting depths. Without exception, MQL technology showed a better performance than the dry condition in obtaining better surface roughnesses under different cutting parameters. Despite that only a small improvement was achieved in terms of cutting temperature, MQL was found to be successful in protecting the cutting tool from excessive amounts of wear and chips. This paper is anticipated to be a guide for manufacturers and researchers in the area of mold steels by presenting an analysis of the capabilities of sustainable machining methods.

This study presents the development of niobium carbide cermets bound to nickel and Ni-12Al (wt%). The use of Ni-12Al (wt%) and Ni aims to replace strategic elements such as cobalt (Co) utilized in tungsten carbide-based cermets. Cermets of different compositions were processed by conventional powder metallurgy. Microstructural analysis with semi-quantitative chemical analysis by EDX, Vickers microhardness and density measurement were performed to evaluate the influence of high energy milling application and sintering temperature on the properties of these cermets. A milling time of 20 min in a planetary mill and sintering temperatures of 1420 ºC or 1450 ºC resulted in homogeneous microstructures, densities close to 90% and hardness of around 1000 HV1, showing a potential for use of this material in cutting tools.

In some cases, industrial practice requires the production of walls or parts with a thickness of less than one millimeter from a metal workpiece. Such parts or walls can be made by milling using disc cutters. This machining method can lead to the generation of residual stresses that determine the appearance of a form deviation characterized by bending the part or the thin wall. To evaluate the suitability of a metallic material for the manufacturing of thin walls by milling with disc cutters, different factors capable of exerting influence on the deviation generated by the residual deformation of the walls were taken into account. A test sample and an experimental research program were designed for the purpose of obtaining an empirical mathematical model. The empirical mathematical model highlights the magnitude of the influence exerted by different input factors on the disc cutter milling process regarding the size of the deviation from the form, and the correct position of the wall or thin part, in the case of a test sample workpiece made of an aluminum alloy. Input factors considered were cutting speed, feed rate, cutter thickness, wall or part thickness, thin wall length, and height. To rank the input factors whose increase leads to an increase in shape deviation, the values of the exponents attached to the factors in question in the empirical mathematical model of the power-type function were taken into account. It was found that the values of the exponents are in the order 0.782 > 0.319 > 0.169 for wall height, feed rate, and wall width, respectively. It was thus established that the strongest influence on the residual deformation of the thin wall is exerted by its height.

Manufacturing high precision and high performance parts in aerospace, automotive and medical industries often requires machining of difficult-to-cut materials such as titanium, nickel and hardened alloyed steel alloys. Low productivity and environmental damage are major problems in cutting these materials, which vitally require optimized cooling strategies. High-pressure cutting fluid supply (HP CF) and cryogenic cooling lubrication (CRYO CL) are two of the most effective cooling lubrication approaches to increase tool life, productivity and avoid scrap production. The scientific and knowledge-based application of HP CF and CRYO CL had a pivotal role in improving the machining of difficult-to-cut materials, specifically in milling processes. In this context, the quantification of the cooling and lubrication effect of HP CF and CRYO CL is essential in order to adapt to the fluctuating heat generation at the cutting zone. The novel concept of a soft sensor for the quantification of the cooling and lubrication effect in the milling process is presented in this paper. This soft sensor integrates force measurements and transient temperature data from the process with the help of a mechanical model as well as an inverse temperature model. These models elevate the measured force and temperature signals to heat flows and power in the thermodynamic domain enabling an energy balancing in the real milling application. A telemetry system was used to measure the transient temperature in the milling tool with embedded thermocouples when milling 42CrMo4 and Ti-6Al-4 V in αβ and β conditions. This way the separated cooling versus lubrication effect of high-pressure cutting fluid supply and a single channel cryogenic cooling lubrication based on carbon dioxide (CO2) and oil is investigated and compared with dry machining at various cutting parameters and proceeding tool wear.

The article deals with the rationalization of the production of shaped inserts for casting rotors. The theoretical part describes the characteristics of shaped inserts for rotor casting, die casting technology, analysis of the existing technology of production of shaped inserts. The main part of the article is focused on the proposed technological process of production, comparison of existing and proposed process. The article concludes with a technical and economic benefit of the proposed solution and evaluation of the work. Rationalization of production has its justification in the development of the company and thus improve competitiveness in the market. These interventions in production offer the possibility of using new technologies that are beneficial both from an economic point of view and to improve working conditions. The article focuses on the description of the existing technology, its evaluation and subsequent processing of a new technological process. Web of Science 2021 4809 4803

The accurate evaluation of the instantaneous undeformed chip thickness (IUCT) plays a crucial role in the modeling of milling processes. However, the vibrations of the tool–workpiece system can make conventional IUCT models either inaccurate or not applicable. This paper introduces the concept of surface function to describe the milled surface, through which the IUCT can be readily computed. The evolution of this surface function is governed by a partial differential equation (PDE) in the form of a balance law, and the material removal process is characterized by discontinuous conditions at the cutters. A finite volume algorithm is adopted to solve the proposed PDE with discontinuous conditions at the cutters. Through a case study of the asymmetric cutting process, the surface function method demonstrates two main advantages over conventional methods: (i) a detailed description of IUCT evolution considering the influence of the initial shape of the workpiece and (ii) a general framework to accurately compute the IUCT. This method shows a promising potential for computing the IUCT in numerical simulations of chattering phenomenon in the milling process.

This article deals with the issue of online chatter detection during milling. The aim is to achieve a verification of the reliability and robustness of selected methods for the detection of chatter that can be evaluated on the machine tool in real time by using the accelerometer signal. In the introductory part of the paper, an overview of the current state of the art in the field of chatter detection is summarized. Entropic methods have been selected that evaluate the presence of chatter from the qualitative behavior of the signal rather than from the magnitude of its amplitude, because the latter can be affected by the transmission of vibrations to the accelerometer position. Another criterion for selection was the potential for practical implementation in a real-time evaluation of the accelerometer signal, which is nowadays quite commonly installed on machine tools. The robustness of the methods was tested with respect to tool compliance, which affects both chatter occurrence and vibration transfer to the accelerometer location. Therefore, the study was carried out on a slender milling tool with two different overhangs and on a rigid roughing tool. The reference stability assessment for each measurement was based on samples of the machined surface. The signals obtained from the accelerometer were then post-processed and used to calculate the chatter indicators. In this way, it was possible to compare different methods in terms of their ability to achieve reliable in-process detection of chatter and in terms of the computational complexity of the indicator.

In order to improve efficiency when manufacturing gas turbine components, alternative machining techniques need to be explored. In this work, abrasive water jet (AWJ) machining by milling has been investigated as an alternative to traditional milling. Various test campaigns have been conducted to show different aspects of using AWJ milling for the machining of superalloys, such as alloy 718. The test campaigns span from studies of individual AWJ-milled tracks, multi-pass tracks, and the machining of larger components and features with complex geometry. In regard to material removal rates, these studies show that AWJ milling is able to compete with traditional semi/finish milling but may not reach as high an MRR as rough milling when machining in alloy 718. However, AWJ milling requires post-processing which decreases the total MRR. It has been shown that a strong advantage with AWJ milling is to manufacture difficult geometries such as narrow radii, holes, or sharp transitions with kept material removal rates and low impact on the surface integrity of the cut surface. Additionally, abrasive water jet machining (AWJM) offers a range of machining possibilities as it can alter between cutting through and milling. The surface integrity of the AWJM surface is also advantageous as it introduces compressive residual stress but may require post-processing to meet similar surface roughness levels as traditional milling and to remove unwanted AWJM particles from the machined surface.

Acoustic emission-based monitoring of the milling process holds the potential to detect undesired damages of fibre-reinforced plastic workpieces, such as delamination or matrix cracking. In addition, abrasive tool wear, tool breakage, or coating failures can be detected. As measurements of the acoustic emission are impacted by attenuation, dispersion, and reflection as it propagates from source to sensor, the waveforms, amplitudes, and frequency content of a wave packet differ depending on the propagation length in the workpiece. Since the distance between acoustic emission sources and a stationary sensor attached to the workpiece changes continually in circumferential milling, the extraction of meaningful information from the raw measurement data is challenging and requires appropriate signal processing and frequency-dependent amplification. In this paper, practical and robust approaches, namely experimentally identified transfer functions and frequency gain parameter tables for attenuation modelling, which in reverse enable the reconstruction of frequency spectra emitted at the acoustic emission source, are presented and discussed. From the results, it is concluded that linear signal processing can largely compensate for the influence of attenuation, dispersion, and reflection on the frequency spectra and can therefore enable acoustic emission based process monitoring.

Актуальность исследования обусловлена тем, что одним из важнейших факторов безотказной работы нефтегазового оборудования являются требования к коррозионной стойкости. Свойства титановых сплавов: высокая коррозионная стойкость в агрессивных средах, высокая прочность в сочетании с малой плотностью, позволяют получать изделия с большой прочностью и малой массой при работе в условиях агрессивных сред. Однако применение титановых сплавов при изготовлении деталей, работающих в условиях агрессивной среды, в том числе для нефтегазового оборудования, ограниченно вследствие неудовлетворительной обрабатываемости резанием, что обусловлено малой теплопроводностью таких сплавов, а также склонностью к интенсивным вибрациям. Объект: производительность и экономическая эффективность от применения фрез при изготовлении детали типа «корпус» из титанового сплава. Цель: разработка рациональных режимов механообработки и геометрии инструмента для фрезерования корпусных элементов из титановых сплавов. Рациональные режимы и геометрия фрезы должны обеспечивать максимальную стойкость инструмента, качество механообработки, производительность и экономическую эффективность. Методы: проведение производственных испытаний фрез с разной геометрией их режущих кромок методом многофакторного эксперимента с использованием вибродиагностического комплекса для определения зон с минимальным уровнем вибрации при механообработке детали типа «корпус» из титанового сплава. Результаты. Разработаны рекомендации по снижению вибрации при фрезеровании корпусных элементов из титановых сплавов. Методика позволяет в условиях производства, в стадии отладки технологического процесса, определить рациональные режимы резания по критериям наибольшей производительности и максимальной стойкости инструмента. The relevance of the research is caused by the fact that one of the most important factors in the failure-free operation of oil and gas equipment is the corrosion resistance requirements. Titanium alloys properties like high corrosion resistance in corrosive environments and high strength combined with low density make it possible to obtain products with high strength and low weight when operating in corrosive environments. However, titanium alloys usage in the manufacture of details that operate in an aggressive environment, including for oil and gas equipment, is limited due to both low machinability and low thermal conductivity, as well as the technological system predisposition to intense fluctuations. Object: productivity and economic efficiency from using mills for manufacturing hull details like «case» type from titanium alloy. The main aim of the research is a development of rational machining modes and tool geometry for milling hull elements from titanium alloys. That can ensure maximum tool life, machining quality, productivity and economic efficiency. Methods: production tests of mills with different geometry of cutting edges by the multifactor experiment method using a vibro-diagnostic complex for determine the minimum vibration level zones during machining of the "case" type part from titanium alloy. Results. The authors have developed the recommendations to reducing vibration during milling hull elements from titanium alloys. This method allows finding the rational cutting conditions according to both the highest productivity and maximum tool life criteria in production conditions during the stage of debugging the technological process.

In nanofluid minimum quantity lubrication (NMQL) milling of aviation aluminum alloy, it is the bottleneck problem to adjust the position parameters (target distance, incidence angle, and elevation angle) of the nozzle to improve the surface roughness of milling, which has large and uncontrollable errors. In this paper, the influence law of milling cutter speed, helical angle, and cavity shape on the flow field around the milling cutter was studied, and the optimal nozzle profile parameters were obtained. Using 7050 aluminum alloy as the workpiece material, the milling experiment of the NMQL cavity was conducted by utilizing cottonseed oil-based Al2O3 nanofluid. Results show that the high velocity of the surrounding air flow field and the strong gas barrier could be attributed to high rotating velocities of the milling cutter. The incidence angle of the nozzle was consistent with the helical angle of the milling cutter, the target distance was appropriate at 25–30 mm, and the elevation angle was suitable at 60°–65°. The range and variance analyses of the signal-to-noise ratio of milling force and roughness were performed, and the chip morphology was observed and analyzed. The results show that the optimal combination of nozzle position parameters was the target distance of 30 mm, the incidence angle of 35°, and the elevation angle of 60°. Among these parameters, target distance had the largest impact on cutting performance with a contribution rate of more than 55%, followed by incidence angle and elevation contribution rate. Analysis by orthogonal experiment revealed that the nozzle position parameters were appropriate, and Ra (0.087 μm) was reduced by 30.4% from the maximum value (0.125 μm). Moreover, Rsm (0.05 mm) was minimum, which was 36% lower than that of the seventh group (Rsm = 0.078 mm).

In-situ ceramics particle reinforced aluminum matrix composites are favored in the aerospace industry due to excellent properties. However, the hard ceramic particles as the reinforcement phase bring challenges to machining. To study the effect of in-situ TiB2 particles on machinability and surface integrity of TiB2/2024 composite and TiB2/7075 composite, milling experiments were performed, and compared with conventional 2024 and 7075 aluminum alloys. In-situ TiB2 particles clustered at the grain boundaries and dispersed inside the matrix alloy grains hinder the dislocation movement of the matrix alloy. Therefore, the milling force and temperature of the composites are higher than those of the aluminum alloys due to the increase of the strength and the decrease of the plasticity. In the milling of composites, abrasive wear is the main wear form of carbide tools, due to the scratching of hard nano-TiB2 particles. The composites containing in-situ TiB2 particles have machining defects such as smearing, micro-scratches, micro-pits and tail on the machined surface. However, in-situ TiB2 particles impede the plastic deformation of the composites, which greatly reduces cutting edge marks on the machined surface. Therefore, under the same milling parameters, the surface roughness of TiB2/2024 composite and TiB2/7075 composite is much less than that of 2024 and 7075 aluminum alloy respectively. Under the milling conditions of this experiment, the machined subsurface has no metamorphic layer, and the microhardness of the machined surface is almost the same as that of the material. Besides, compared with 2024 and 7075 aluminum alloy, machined surfaces of TiB2/2024 composite and TiB2/7075 composite both show tensile residual stress or low magnitude of compressive residual stress.

The working gap (Wg) between a tooltip and a substrate surface is a critical process parameter affecting the quality metrics and precision of microstructures fabricated using an electrochemical discharge machining (ECDM) process. Despite the extensive investigation carried out on ECDM processes for the last several years, only a few researchers have explicitly explained the technique used to establish the Wg. In the present work, the authors propose a simple, cost-effective technique using a commercially available metallic feeler gauge and a multimeter to precisely establish a Wg in an ECDM process. A systematic experimental investigation was carried out using the proposed method to study the influence of Wg on the quality metrics such as the depth, width, edge linearity, heat-affected zone, and surface finish of fabricated microstructures on a glass substrate. Experimental results revealed that even a 2 µm difference in Wg significantly influenced the quality and quantity metrics of an ECDM process. It was observed that no machining occurred beyond a Wg of 25 µm even when a TTR as low as 0.5 mm/min and an applied voltage greater than 44 V were used. A micro-channel with improved quality metrics was obtained using a tool travel rate (TTR) of 1 mm/min with an applied voltage of 33 V and a Wg of 2 µm while using 30% NaOH as an electrolyte. The proposed method would be helpful for researchers to fabricate precise micro-channels on glass substrates using ECDM processes.

Developing high-efficiency lubricant additives and high-performance green cutting fluids has universal significance for maximizing processing efficiency, lowering manufacturing cost, and more importantly reducing environmental concerns caused by the use of conventional mineral oil-based cutting fluids. In this study, a nanocomposite is synthesized by filling sulfurized isobutylene (T321) into acid-treated carbon nanotubes (CNTs) with a liquid-phase wet chemical method. The milling performance of a nanocutting fluid containing CNTs@T321 composites is assessed using a micro-lubrication technology in terms of cutting temperature, cutting force, tool wear, and surface roughness. The composite nanofluid performs better than an individual CNT nanofluid regarding milling performance, with 12%, 20%, and 15% reductions in the cutting force, machining temperature, and surface roughness, respectively. The addition of CNTs@T321 nanocomposites improves the thermal conductivity and wetting performance of the nanofluid, as well as produces a complex lubricating film by releasing T321 during machining. The synergistic effect improves the cutting state at the tool–chip interface, thereby resulting in improved machining performance.

Solid ceramic end mills for machining heat resistant super alloys (HRSA) have the potential to generate higher material removal rates, up to one order of magnitude, with respect to standard carbide tools. The machining operations in aerospace industry, where large removals are required to obtain tiny and slender parts like turbine blades, is a cost-intensive task that can benefit of the adoption of ceramic solid end mills. However, these tools show a quite limited tool life, especially when used with interrupted tool engagement strategies. Moreover, they might induce heat-related problems in the workpiece material surface integrity. This paper investigates the cutting and the tool wear during milling Inconel 718 with solid ø12 mm cutting end tool made by SiAlON. The wear mechanisms are studied together with their effects on process signals as cutting forces and power, measured via external and CNC integrated sensors. The carried experimental campaign allowed to find out that tool clogging and edge chipping were the primary cutting phenomena leading the tool wear. Cutting strategy (downmilling or upmilling) produced different results in terms of tool wear sensitivity and process outputs whereas upmilling configuration showed the best results in terms of cutting signals stability and surface integrity. At the same time, cutting speed was found to increase the cutting power more in upmilling than downmilling cutting. The analysis of the forces and power demonstrated that the typical tool wear mechanisms can be traced by signal monitoring due to their high impact on cutting processes. This fact shows the good potential of signal monitoring for a better tool life evaluation.

International audience; The machining of Nomex honeycomb structures represents a technical and scientific barrier for aeronautical applications. The difficulties encountered during the machining of this type of material are linked to the low density of Nomex paper, and to the low thickness of the walls forming the honeycomb cells of this type of structure. In this work, a finite element calculation code “ABAQUS`- EXPLICIT” was used to optimize and analyze the machining by milling of Nomex honeycomb structures. The main objective of this work is to study the influence of the machining conditions on the cutting forces, and the morphology of the chips.

Robotic machining is an alternative to manufacturing processes that combines the technologies of a high-performance machine tool with the flexibility of a 6-axis jointed arm robot. With their large working area, industrial robots are of particular interest for processing large-volume components and large structures, like aircraft components. An influencing variable, which is particularly relevant for milling processes with industrial robots are the cutting force F and the resulting dimensional deviation D. Milling tests of titanium alloys were carried out with an industrial robot and the results compared with a conventional machine tool. Due to the low thermal conductivity and high chemical reactivity of the Ti-6Al-4V alloy, heat is generated and increases the temperature in the contact region of the cutting tool/work piece. That has an impact on the cutting tool wear and increases the cutting force F, and consequently, the dimensional deviation D and the machined surface quality. The aim of the investigations is to find a suitable parameter selection and machining strategy for machining titanium alloys with minimal deviation D and an appropriate surface finish.

Statistical studies of the surface distribution of milled workpieces and the possibility of their use for operation-based tests and machine tool evaluation are presented. In the first part of the paper, the assumptions and scope of statistical research were defined and the method of obtaining data on machined surfaces directly from machining programs was described. In the following part of the article, the results of research consisting in determining the probability of machining operations in the working space of a numerically controlled milling machine are presented on the example of machining programs designed for implementation on the DMC 1035V Ecoline vertical machining center. Knowledge of the load distribution in the working space of a milling machine associated with the machining process can be used to design and manufacture test pieces reflecting the machining tasks performed on the milling machine and to develop appropriate acceptance and evaluation procedures.

This paper describes a hybrid manufacturing approach for silicon carbide (SiC) freeform surfaces using binder jet additive manufacturing (BJAM) to print the preform and machining to obtain the design geometry. Although additive manufacturing (AM) techniques such as BJAM allow for the fabrication of complex geometries, additional machining or grinding is often required to achieve the desired surface finish and shape. Hybrid manufacturing has been shown to provide an effective solution. However, hybrid manufacturing also has its own challenges, depending on the combination of processes. For example, when the subtractive and additive manufacturing steps are performed sequentially on separate systems, it is necessary to define a common coordinate system for part transfer. This can be difficult because AM preforms do not inherently contain features that can serve as datums. Additionally, it is important to confirm that the intended final geometry is contained within the AM preform. The approach described here addresses these challenges by using structured light scanning to create a stock model for machining. Results show that a freeform surface was machined with approximately 70 µm of maximum deviation from that which was planned.

The paper presents the microstructural characterization of the chip roots in high-speed steels and ceramic Ti3SiC2. The process of chip formation and the obtaining of adequate samples were carried out using the quick-stop method. The tests were carried out during the milling process; the “quick stop” method was carried out in order to obtain samples of the chip roots. This method was developed in-house by the authors. The chip roots were microscopically studied by means of a light microscope (LM) and a scanning electron microscope (SEM). Before the actual analysis, preparation was performed based on the standard metallographic technique. The analysis of the high-speed steels samples showed that, for the used cutting conditions, a discontinuous chip with a built-up edge (BUE) was formed. During the processing of the Ti3SiC2 ceramic, a significant difference was manifested in the chip formation process and a powder-like chip was produced. After utilizing a careful cutting process, a chip pattern was observed, from which it is evident that chip breakage during ceramic processing occurs without prior plastic deformation. In addition, the cutting force Fc was also measured during the milling process of the high-speed steels and the ceramic, and it was correlated with the cutting speed, feed per tooth and depth of cut.

Aluminum alloy is the main structural material of aircraft, launch vehicle, spaceship, and space station and is processed by milling. However, tool wear and vibration are the bottlenecks in the milling process of aviation aluminum alloy. The machining accuracy and surface quality of aluminum alloy milling depend on the cutting parameters, material mechanical properties, machine tools, and other parameters. In particular, milling force is the crucial factor to determine material removal and workpiece surface integrity. However, establishing the prediction model of milling force is important and difficult because milling force is the result of multiparameter coupling of process system. The research progress of cutting force model is reviewed from three modeling methods: empirical model, finite element simulation, and instantaneous milling force model. The problems of cutting force modeling are also determined. In view of these problems, the future work direction is proposed in the following four aspects: (1) high-speed milling is adopted for the thin-walled structure of large aviation with large cutting depth, which easily produces high residual stress. The residual stress should be analyzed under this particular condition. (2) Multiple factors (e.g., eccentric swing milling parameters, lubrication conditions, tools, tool and workpiece deformation, and size effect) should be considered comprehensively when modeling instantaneous milling forces, especially for micro milling and complex surface machining. (3) The database of milling force model, including the corresponding workpiece materials, working condition, cutting tools (geometric figures and coatings), and other parameters, should be established. (4) The effect of chatter on the prediction accuracy of milling force cannot be ignored in thin-walled workpiece milling. (5) The cutting force of aviation aluminum alloy milling under the condition of minimum quantity lubrication (mql) and nanofluid mql should be predicted.

In the machining of complicated surfaces, the cutters with large length/diameter ratios are used widely and the deformation of the machining system is one of the principal error sources. During the process planning stage, the cutting direction angle, the cutter lead and tilt angles are usually optimized to minimize the force induced error. It may lead to a low machining efficiency for bullnose end mills, as the material removal rates are different largely for different machining angles. In this paper, the influence mechanism of the machining angles on the force induced error is studied based on the models of the instantaneous cutting force when the cutter flute traveling through the cutting contact point and the stiffness of the machining system. In order to evaluate the machining angles, the force induced error/efficiency indicator (FEI) is defined as the division of the force induced error and the equal volume sphere of the removed material. FEI is dimensionless, with the lower FEI, the lower force induced error and the higher machining efficiency. For optimal selection of the machining angles, the critical FEI is calculated with the constraint of force induced error and the desired material removal rate, and the critical FEI separate the set of the machining angles into two subsets. After the feed rate scheduling process, the machining angles in the optimal subset would have higher machining accuracy and efficiency, while the machining angles in the other subset have lower machining accuracy and efficiency. Through the machining experiment of five axis machining and freeform surface machining, the effectiveness and superiority of the proposed FEI method is verified with a bullnose end mill, which can improve the machining efficiency with the constraint of force induced error.

The use of aluminium in automotive and aerospace parts as well as low-pressure moulds are widely popular in the manufacturing industry. The good machinability of its alloy is one of the many reasons why aluminium is a default choice. In this study, aluminium 6061 alloy was chosen. However, studies were done on the cutting path strategies in machining especially for convex curved shape and their effects on the surface finish of the workpiece were not very informative. Five cutting strategies were involved and compared – parallel, morphed spiral, spiral, radial and circle. As industries are moving towards minimising the carbon footprint of their manufacturing processes, this study provided a good opportunity to include the investigation of the energy consumption of the cutting path strategy as well. Essentially, this study was aimed to investigate the effect of cutting path strategies on the workpiece's surface roughness, and the energy consumption of the machining process as well as to establish the optimum cutting parameters for the best cutting path strategy. Overall, the parallel cutting path strategy was found to be the most suitable cutting strategy to be used for convexly curved surface machining.

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2030 Mechanical components applied in ore crushing, the drilling of oil wells, and soil plowing need to be manufactured from materials with high resistance to abrasive wear, erosion, and corrosion. Typical materials applied under these severe conditions are cold work tool steels, high-speed steels and high-Cr white cast iron (HCWCI), which present a challenge in machining. In milling, the cutting fluid can easily access the cutting region due to interrupted cutting. In this context, coated cemented carbides associated with lubricooling techniques may be an alternative to improve the process feasibility. The aim of this study was to evaluate the effects of different coated cemented carbide grades and lubri-cooling techniques on the tool life and surface residual stress of the milled surface of HCWCI. Therefore, two coated cemented carbide grades associated with two lubri-cooling techniques (flood emulsion and liquid nitrogen—LN2) were applied in milling tests. The results demonstrated the feasibility of using the coated cemented carbide as a tool material in the milling of HCWCI (cutting time longer than 15 min). Furthermore, LN2 increased, by at least a factor of 2, the tool life when compared with flood emulsion. Regarding the milled surface, values above 500 MPa were obtained for the compressive residual stresses with the use of the worn cutting edges and the application of LN2

In the manufacturing process, the surface roughness acts as one of the vital response to define the machined product quality.This manuscript platforms on the modeling of surface roughness(Ra) during milling of Multiwall Carbon Nanotube (MWCNT) reinforced polymer nanocomposites using an artificial neural network (ANN). ANN developed as a cost-effective approximation module that is competent of self-learning and pliable to complicated data variables. Taguchi based L27 orthogonal design was perfectly utilized to perform the machining operation. The consequence of process parameters, i.e., MWCNT (wt.%), Spindle speed (N), Feed rate(F), and depth of cut (D) have been investigated to attain the minimal Ra of the machined samples.The ANOVA study shows that Feed rate(F) has the most significant (55.25%) parameters for Ra followed by Spindle speed (N), MWCNT weight percentage (wt.%), and depth of cut(D). The Feed forward back propagation network is used for the ANN model with TRAINLM and LEARNGDM functions used as training and learning algorithms.The selection of an adequate model based on the correlation coefficient (R2 ), mean squared error (MSE), and the average percentage error (APE) was achieved. The designated model has high accuracy with R2 > 99%, MSE < 0.2%, and APE < 3%,.Further,the plot between experiment value and predicted value shows the adequacy and feasibility of the proposed ANN model in the machining environment.

When tool wears during machining, cost of the process increases. Rapid tool wear leads to even further contributions to process cost and hence must be taken well care of. Among the many forms of tool wear, notch wear is one that has a big effect on the tool change decision. When the tool contacts the workpiece, a high amount of impact is created where depth of cut is. With continuous machining operations such as turning, the impact may not be as important; however, with interrupted machining operations such as milling, repetitive impact between tool and workpiece occurs at every rotation. Therefore, notch wear can propagate rapidly when milling at a constant depth. When that happens, machine operator would be required to discard the tool and replace it with a fresh one. However, this may not have to be the case, if the depth of cut is varied throughout the milling process (variable-depth milling). Although different patterns of varying the depth of cut can be determined, the easiest route of continuously varying the depth of cut in increasing or decreasing direction should be as effective as any other. While varying the depth of cut, the direction of the variation is also found to have an effect on the end results. In this work, first the theoretical difference between end milling and variable-depth milling is discussed. Afterwards, benefit of using “true variable-depth milling” is explained. Then, machining experiments to quantify such benefits is detailed and the results are presented. It was found that when the same machining conditions were used to end-mill, variable-depth mill, and true variable-depth mill a workpiece, impact of notch wear can be minimized by continuously varying depth of cut in the right direction.

The manufacturing process of blade-integrated disks (blisks) represents one of the most challenging tasks in turbomachinery manufacturing. The requirement is to machine complex, thin-walled blade geometries with high aspect ratios made of difficult-to-cut materials. In addition, extremely tight tolerances are required, since the smallest deviations can lead to a reduction in efficiency of the blisk in the later use. Nowadays, the ramp-up phase for the manufacturing of a new blisk is time and cost-intensive. To find a suitable manufacturing process that meets the required tolerances of the blisk, many experimental tests with different process parameters and strategies are necessary. The used approach is often trial and error, which offers limited testing opportunities, is time-consuming and waste of resources. Therefore, the objective of this paper is to develop a knowledge-based process design optimization in blisk manufacturing. For this purpose, this paper picks up the results from our previous work. Based on these results, an experimental validation of the two process design tasks “number of blocks” and “block transition” is conducted. As part of the validation, the results of machining tests on a demonstrator blisk made of Inconel 718 are presented and discussed.

Proceedings of ASME Turbo Expo 2021: Turbomachinery Technical Conference and Exposition : June 7-11, 2021, virtual, online. - Volume 7: Industrial and cogeneration, manufacturing materials and metallurgy ASME Turbo Expo 2021, online, 7 Jun 2021 - 11 Jun 2021; New York, N.Y. : The American Society of Mechanical Engineers GT2021-59562, V007T17A012, 1-9 (2021). doi:10.1115/GT2021-59562, Published by The American Society of Mechanical Engineers, New York, N.Y.

In this project the objective is to understand how to design a braiding machine capable of automated production of Omnifibre in a research environment. Automated production of Omnifibre is the key issue for the researchers as they want to increase the weaveabilty of the fibers and make it more suitable for use in active textiles. To achieve the necessary knowledge when designing a braiding machine, an extensive literature study was performed which focused on braids, braiding machines, and CNC manufacturing. An Interview with a researcher and with a manufacturing expert was conducted. Simulations of different braiding machine configurations were performed in TexMind braiding machine configurator. Solidworks was used to estimate the size of the braiding machine. A large amount of the machine’s parts were manufactured on a CNC mill and lathe to test manufacturability and to aid in designing optimal subsystems. The result is a proposed design for a braiding machine in the form of a 3-D model and a partially completed prototype used for testing and design evaluation. The conclusion is that Omnifibre is much like other ultra-fine braided threads, and the research on its applicability has a big impact on the braiding machine’s design, especially on flexibility in thread material and braiding patterns.

Porcelain tile manufacturing is an energy-intensive industry that is in dire need of increasing productivity, minimizing costs, and reducing CO2 emissions, while keeping the product quality intact to remain competitive in today’s environment. In this contribution, alternative processing parameters for the porcelain tile production sequence were proposed based on simulation-based process optimization. Flowsheet simulations in the Dyssol framework were used to study the impact of the milling and firing process parameters on the electrical and thermal energy consumption, final product quality, and productivity of the entire processing sequence. For this purpose, a new model of gas flow consumption in the sintering stage was proposed and implemented. During optimization, the primary condition was to maintain the product quality by keeping the final open porosity of the tile within the specified industrial range. The proposed simulation methodology proved to be effective in predicting the influence of the processing parameters on the intermediate and final products of the manufacturing sequence, as well as in estimating the production costs for the Brazilian and Spanish economic conditions. This approach has shown great potential to promote digitalization and establish digital twins in ceramic tile manufacturing for further in-line process control., Porcelain tile manufacturing is an energy-intensive industry that is in dire need of increasing productivity, minimizing costs, and reducing CO2 emissions, while keeping the product quality intact to remain competitive in today’s environment. In this contribution, alternative processing parameters for the porcelain tile production sequence were proposed based on simulation-based process optimization. Flowsheet simulations in the Dyssol framework were used to study the impact of the milling and firing process parameters on the electrical and thermal energy consumption, final product quality, and productivity of the entire processing sequence. For this purpose, a new model of gas flow consumption in the sintering stage was proposed and implemented. During optimization, the primary condition was to maintain the product quality by keeping the final open porosity of the tile within the specified industrial range. The proposed simulation methodology proved to be effective in predicting the influence of the processing parameters on the intermediate and final products of the manufacturing sequence, as well as in estimating the production costs for the Brazilian and Spanish economic conditions. This approach has shown great potential to promote digitalization and establish digital twins in ceramic tile manufacturing for further in-line process control.

Degraded or defect machine components and consumables negatively impact manufacturing quality and productivity. Diagnosing and predicting the wear or degradation status of critical machine components or parts are therefore of general interest. To tackle this challenge, data-driven approaches based on supervised machine learning principles have demonstrated promising results. However, supervised learning models capable of degradation identification require large quantities of data. In practice, run-to-failure data in large amounts is usually not available and expensive to obtain. To overcome this issue, this study proposes an unsupervised learning approach for degradation prognostics of machine tool components and consumables. It uses time series of multi-sensor signal data, which are transformed into a feature representation. The features consist of various characterizations of the time series, allowing to make different signal measurements comparable, and cluster them according to their feature values. The herewith obtained density-based clustering model is used to diagnose and predict the degradation states of components and parts in unknown conditions. The novelty in the proposed approach lies within the identification of continuous component and part degradation states based on unsupervised learning principles. The proposal is verified and demonstrated on an exemplary data set containing a small sample of run-to-failure multi-sensor signals of milling inserts and their corresponding wear state. By the application of the proposed procedure on the exemplary data set, we demonstrate that an unsupervised clustering approach is capable of separating wear data such that meaningful and accurate estimations of the part condition are possible. The advantages are its ability to cope with scarce data sets, its limited engineering and hyperparameter tuning effort, and its straightforward implementation to a multitude of degradation and wear diagnostics scenarios., The International Journal of Advanced Manufacturing Technology, 117 (7), ISSN:0268-3768, ISSN:1433-3015

The simulation of material machining using finite element models is a powerful tool for the optimization of simulated processes and tools, as well as for the determination of cutting process characteristics that are difficult or practically impossible to determine by experiment. The paper presents results of the numerical simulation of the titanium alloy Ti10V2Fe3Al (Ti-1023). The behavior of the machined material was modeled with the Johnson–Cook constitutive equation, and its damage mechanism was modeled using the Cockcroft and Latham model. The parameters of the constitutive equation for machined material behavior and damage were determined using a DOE sensitivity analysis during orthogonal cutting. The values of the cutting force components, as well as the minimum and maximum chip thicknesses, were used as target functions for the DOE analysis. The generalized values of the constitutive equation parameters and the fracture stress values determined by the DOE analysis were calculated as the set intersection of individual multitude values of these parameters. The simulation results of the studied cutting processes showed an acceptable agreement with the experimental data when the cutting speed and tool feed changed significantly. The deviation in the simulated values of the cutting forces from their measured values ranged from about 10% to about 20%.

As an important artificial implant material, the corrosion resistance of NiTi shape memory alloy is closely related to the machined surface quality. In this paper, the multiple analysis methods concerning potentiodynamic polarization, impedance spectrum and corrosion morphology are used to analyze the corrosion resistance of the alloy. The potentiodynamic polarization and impedance spectrum test results show that the conductivity and corrosion current density of electrochemical polishing surface decrease, and the polarization resistance and corrosion potential increase compared with milling. After electrochemical polishing, the surface roughness of the milling sample is decreased, and the NiTi alloy of austenite phase is transformed into TiO2, which improves the corrosion resistance of the alloy. In addition, there are pitting corrosion, hole corrosion and crevice corrosion morphology on the milling surface, while the pitting corrosion and hole corrosion exist on the electrochemical polishing surface. The corrosion morphology verified the analysis of potentiodynamic polarization and impedance spectrum. The multiple analysis method proposed in this paper can be used as a more accurate evaluation method for the corrosion resistance of alloy surface, avoiding the error of analysis results caused by the impedance spectrum equivalent circuit and potentiodynamic polarization following Tafel relationship.