The Special Issue Machining—Recent Advances, Applications and Challenges is intended as a humble collection of some of the hottest topics in machining. The manufacturing industry is a varying and ...challenging environment where new advances emerge from one day to another. In recent years, new manufacturing procedures have retained increasing attention from the industrial and scientific community. However, machining still remains the key operation to achieve high productivity and precision for high-added value parts. Continuous research is performed, and new ideas are constantly considered. This Special Issue summarizes selected high-quality papers which were submitted, peer-reviewed, and recommended by experts. It covers some (but not only) of the following topics:
High performance operations for difficult-to-cut alloys, wrought and cast materials, light alloys, ceramics, etc.;
Cutting tools, grades, substrates and coatings. Wear damage;
Advanced cooling in machining: Minimum quantity of lubricant, dry or cryogenics;
Modelling, focused on the reduction of risks, the process outcome, and to maintain surface integrity;
Vibration problems in machines: Active and passive/predictive methods, sources, diagnosis and avoidance;
Influence of machining in new concepts of machine–tool, and machine static and dynamic behaviors;
Machinability of new composites, brittle and emerging materials;
Assisted machining processes by high-pressure, laser, US, and others;
Introduction of new analytics and decision making into machining programming.
We wish to thank the reviewers and staff from Materials for their comments, advice, suggestions and invaluable support during the development of this Special Issue.
Additive manufacturing (AM) is an attractive manufacturing technology in tooling applications. It provides unique opportunities to manufacture tools with complex shapes, containing inner channels for ...conformal cooling. In this investigation, H13, a widely used tool steel, was manufactured using a laser powder bed fusion method. Microstructure, tensile mechanical properties, hardness, and porosity of the AM H13 after stress relieve (SR), standard hardening and tempering (SR + HT), and hot isostatic pressing (SR + HIP + HT) were investigated. It was found that the microstructure of directly solidified colonies of prior austenite, which is typical for AM, disappeared after austenitizing at the hardening heat treatment. In specimens SR + HT and SR + HIP + HT, a microstructure similar to the conventional but finer was observed. Electron microscopy showed that SR and SR + HT specimens contained lack of fusion, and spherical gas porosity, which resulted in remarkable scatter in the observed elongation to break values. Application of HIP resulted in the highest strength values, higher than those observed for conventional H13 heat treated in the same way. The conclusion is that HIP promotes reduction of porosity and lack of fusion defects and can be efficiently used to improve the mechanical properties of AM H13 tool steel.
The present study illustrates the performance of three different cutting tool materials, namely: PCBN, TiN coated PCBN, and mixed aluminum ceramic (Al2O3+TiC) in the turning of medium hardened D2 ...tool steel (52 HRC). Formation of Cr–O tribofilms on the ceramic tool surface as a result of interaction with the workpiece material and environment (identified by X-ray Photoelectron Spectroscopy) leads to improvement of lubricating properties at the tool/chip interface. Obtained results revealed that the mixed alumina ceramic tool can outperform both types of PCBN under different machinability criteria.
•Mixed alumina ceramic tool gives longer tool life and lower cutting forces than PCBN.•Friction kinetics between each tool material and workpiece material control tool wear.•TiN coating on PCBN does not improve its performance.•Surface tribo-films formed on the worn surface were studied using X-ray photoelectron spectroscopy (XPS).
Tool condition monitoring and machine tool diagnostics are performed using advanced sensors and computational intelligence to predict and avoid adverse conditions for cutting tools and machinery. ...Undesirable conditions during machining cause chatter, tool wear, and tool breakage, directly affecting the tool life and consequently the surface quality, dimensional accuracy of the machined parts, and tool costs. Tool condition monitoring is, therefore, extremely important for manufacturing efficiency and economics. Acoustic emission, vibration, power, and temperature sensors monitor the stability and efficiency of the machining process, collecting large amounts of data to detect tool wear, breakage, and chatter. Studies on monitoring the vibrations and acoustic emissions from machine tools have provided information and data regarding the detection of undesirable conditions. Herein, studies on tool condition monitoring are reviewed and classified. As Industry 4.0 penetrates all manufacturing sectors, the amount of manufacturing data generated has reached the level of big data, and classical artificial intelligence analyses are no longer adequate. Nevertheless, recent advances in deep learning methods have achieved revolutionary success in numerous industries. Deep multi-layer perceptron (DMLP), long-short-term memory (LSTM), convolutional neural network (CNN), and deep reinforcement learning (DRL) are among the most preferred methods of deep learning in recent years. As data size increases, these methods have shown promising performance improvement in prediction and learning, compared to classical artificial intelligence methods. This paper summarizes tool condition monitoring first, then presents the underlying theory of some of the most recent deep learning methods, and finally, attempts to identify new opportunities in tool condition monitoring, toward the realization of Industry 4.0.
Excessive tool wear leads to the damage and eventual breakage of the tool, workpiece, and machining center. Therefore, it is crucial to monitor the condition of tools during processing so that ...appropriate actions can be taken to prevent catastrophic tool failure. This paper presents a hybrid information system based on a long short-term memory network (LSTM) for tool wear prediction. First, a stacked LSTM is used to extract the abstract and deep features contained within the multi-sensor time series. Subsequently, the temporal features extracted are combined with process information to form a new input vector. Finally, a nonlinear regression model is designed to predict tool wear based on the new input vector. The proposed method is validated on both NASA Ames milling data set and the 2010 PHM Data Challenge data set. Results show the outstanding performance of the hybrid information model in tool wear prediction, especially when the experiments are run under various operating conditions.
Tool wear and life of cutting tools are significant evaluation criteria of machining processes. However, the occurring wear mechanisms are influenced by a number of factors such as the process ...parameters, tool geometry and the material properties of the tool and workpiece. Previous research has shown a high potential for the use of adapted cutting edge microgeometries on cemented carbide cutting tools. The optimal cutting edge rounding is strongly dependent on the tool material properties. However, the influence and relation between the properties of the cemented carbide tool, the microgeometry and the resulting tool wear are not yet completely understood. In this study the tool wear is investigated by systematically varying the mechanical and thermophysical properties of the tool material, the tool microgeometry and cutting process parameters. Significant influencing variables of tool wear are identified and existing relationships quantified. Results show that the occurring wear mechanisms depend on the cutting edge microgeometry as well as the mechanical properties of the cemented carbide. During continuous machining the minimum required cutting edge rounding is a function of the cemented carbide’s fracture toughness. This knowledge allows an adaption of the cutting edge microgeometry depending on the substrate properties to reduce the tool wear and achieve a longer tool life.
Today, the AISI D6 tool steel has been employed in the manufacture of dies and molds that require high mechanical properties. Such hard material is not trivial to machining. Milling free-form ...geometries of D6 is a challenge usually faced at die and mold industries. Therefore, the current paper presents an investigation of free-form milling of hard material AISI D6 tool steel using a ball-end cemented carbide cutting tool. The influence of the toolpath direction (descendant and ascendant) and tool-workpiece surface contact were examined, and the machining forces, surface roughness, tool wear, and tool life were evaluated. The experiments were performed in two kinds of workpieces: in the first one, the milled surface was a cylindrical and in the second, the surface was inclined planes (with three different inclinations). The results indicate that the most influential factor for tool life was tool vibration. The higher the vibration, the shorter the tool life. Further, unlike milling of ordinary materials for molds and dies, the engagement of the center of the tool tip during cutting is advantageous for the machining process of hard materials because it improves cutting stability, thus reducing surface roughness and increasing tool life.
Non-productive auxiliary processes affect the single part and small badge production of milling tools. The key production process grinding is inevitably linked to the auxiliary conditioning process. ...The time demand of those process steps decreases the overall productivity of the manufacturing process. However, today the machine operator decides on conditioning cycles individually by the use of experience. Until today, there is no objective data based approach available that supports the initiation of these conditioning processes or the adaption of the grinding process itself in order to improve its process efficiency. For this purpose, a process-related topography evaluation method of the grinding wheel surface is developed within this study. For the measurement, an optical method based on laser triangulation is used. The measurement system is implemented into a common tool grinding machine tool. In addition, characteristic topography values are defined that show the wear conditions of the grinding tool. Moreover, the data is summarized in a database of wear conditions. The developed measurement method can save grinding and dressing tool resources, process times and minimizes scrap parts. In addition, an adaptation of the process and a targeted launch of auxiliary processes can be enabled. The novel characteristic-based topography measurement creates the opportunity to enhance the tool life of the grinding wheels up to 30% without losing productivity.
The use of tool sets constitutes one of the most elaborate examples of animal technology, and reports of it in nature are limited to chimpanzees and Goffin’s cockatoos. Although tool set use in ...Goffin’s was only recently discovered, we know that chimpanzees flexibly transport tool sets, depending on their need. Flexible tool set transport can be considered full evidence for identification of a genuine tool set, as the selection of the second tool is not just a response to the outcomes of the use of the first tool but implies recognizing the need for both tools before using any of them (thus, categorizing both tools together as a tool set). In three controlled experiments, we tested captive Goffin’s in tasks inspired by the termite fishing of Goualougo Triangle’s chimpanzees. Thereby, we show that some Goffin’s can innovate the use and flexibly use and transport a new tool set for immediate future use; therefore, their sequential tool use is more than the sum of its parts.
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•Captive Goffin’s cockatoos are able to innovate the flexible use of a tool set•Goffin’s can switch flexibly between transporting a tool set or individual tools•Results suggest the ability to recognize the need for a tool set•Results suggest a convergence of associative tool use between birds and primates
In this study, Osuna-Mascaró et al. test Goffin’s cockatoos in tasks inspired by the termite fishing of wild chimpanzees. Goffin’s are able to flexibly use and transport a tool set for immediate future use, suggesting the ability to recognize the need for both tools as a set for task success.
