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New Generation Ball Mills have started to be preferred in milling systems regarding energy efficiency in recent years. In this article, modernization studies have been carried out to ensure that the current new generation ball mill (NGBM) operates on a chaotic basis. In experimental studies, chaotic signals loaded on the PLC device moved the milling chamber chaotically on horizontal or circular axes. While the grinding chamber is moving at constant speeds in both the horizontal and circular axis in the current NGBM, the improved New Generation Ball Mill (INGBM) has gained the ability to move at constant or chaotic speeds in both horizontal and vertical axes. In this study, the milling chamber of INGBM has a constant frequency speed in the horizontal and circular axes in the first scenario, a chaotic system in the horizontal axis, and a constant frequency speed in the circular axis in the second scenario. In the third scenario, it was ensured that it was moved at constant frequency speed in the horizontal axis and with the chaotic system in the circular axis. Experimental studies were carried out on the milling of SiC powder, which was chosen as an example in all scenarios. Sieve Analysis method and Scanning Electron Microscope (SEM) analysis methods were used when examining the ground powders. For both methods, the best results were obtained in the horizontal axis constant frequency speed (35 Hz) and circular axis chaotic (23-27 Hz, Lorenz system) operating scenario. It is seen that INGBM is 42% better in the powder size criterion and 3.44% better in the energy efficiency criterion.

This paper considers the coverage path planning (CPP) problem for marine surveys, where the survey vehicles’ movements are confined in the irregular polygon search area. So this is a sort of milling problem with the minimum number of turns in order for improvement of the acquired sonar image quality. For this purpose, this paper proposes a novel method called CbSPSA (calculation based shortest path search algorithm). Especially in the irregular corner area, this algorithm can easily calculate a kind of shortest path for its full coverage of this irregular area. For any given polygon, it can always be partitioned into convex polygon(s). In this paper, we only consider the case where these divided convex polygons are all connected one by one. In this case, the shortest path with minimum turns in each convex polygon can be easily searched by CbSPSA. And further by simply linking all of these pieces, the total coverage path for any given polygon area can be constructed. On the other hand, for a given polygon, usually there are several different cases of partition. Among the searched coverage paths for each of these different partitions, the final optimal coverage path is determined through a predefined criteria. Numerical simulation and analyses are carried out to demonstrate the effectiveness of the proposed method.

The trochoidal toolpath is generated based on skeleton. However, several different skeletons can be extracted from one pocket. To improve the efficiency of trochoidal rough milling, a cutter selection method basing the optimal skeleton is proposed. Firstly, for a pocket, preliminary skeleton curves and nodes are extracted according to the principle of medial axis transformation. A skeleton extraction method is given that the skeleton is a combination of skeleton curves generated by randomly connecting the preliminary skeleton curves under nodes constraint. A set of skeletons can be obtained by repeatedly extracting skeleton. Furthermore, an optimization model based on the shortest machining time is established, and then the optimization model is solved by the Genetic Algorithm to determine the optimal tool combination and skeleton. The developed approach is validated in trochoidal milling a pocket for cutter selection. The experimental results show that the method can significantly improve the processing efficiency.

In laminectomy, the laminas above the spinal nerves need to be removed by milling. This process is very dangerous because of the special lesion, and surgeons usually control the milling process by sensing the surgical status. However, in robot-assisted laminectomy, safety monitoring will be difficult because the surgeon is not directly involved. Based on the human tactile perception mechanism, this article proposes a surgical status perception method using the acceleration sensor and force sensor installed on the robot. The Sinc-convolutional layer is introduced to process high-frequency vibration signals, and the obtained features are processed together with the averaged force signals using a 1-D convolutional network. The proposed method classifies the surgical status into five categories, and outputs the burr clogging probability. Experiments on animal bones show the effectiveness of the proposed model. In addition, it has also been proved that the fusion of the two tactile signals can significantly improve the status recognition accuracy under changing milling parameters. [ABSTRACT FROM AUTHOR]

The low-temperature phase (LTP) of MnBi is considered a viable alternative to rare earth permanent magnets. However, the synthesis of a single-phase LTP-MnBi with a specific crystallographic form is difficult because slight changes in process parameters can produce considerable variations in the crystallographic forms of the compound. In this work, a high-energy ball milling and subsequent heat treatment technique were employed to prepare highly pure LTP-MnBi. A purity of ~96 wt% of LTP-MnBi was achieved by two-stage milling and tailoring the heat treatment schedule. The effects of the heat treatment and the ball milling conditions on the magnetic performances of the material were investigated by analyzing the phase purity and the grain sizes of the sample. This high-purity LTP-MnBi exhibits the highest saturation magnetization of 63.47 emu/g, and its coercivity was measured to be 5.53 kOe. [ABSTRACT FROM AUTHOR]

Magnetic fluid seals (MFSs) have been a popular sealing method, with unique advantages compared to traditional mechanical seals, such as zero leakage, long lifetime, and low resistance torque. However, restricted by the properties of carrier fluids, MFSs cannot work under extremely high or low temperatures. To ensure stability, the pressure capability per stage is also limited. Recently, a novel sealing method using nano-micro magnetic powders has been presented to solve the problems, and leakage rates turn out to be a main focus. Here, we realize the leakage rate control by lubricant coatings on magnetic nanoparticles. Fe3O4 nanoparticles coated with solid lubricants are prepared by the high-energy ball milling method. Effects of different types of lubricants and ball milling parameters on the leakage rate are studied by magnetic powder sealing experiments. Permeability of magnetic powders is estimated from the experimental data. Furthermore, the flow field distribution of a real magnetic powder seal (MPS) is simulated. [ABSTRACT FROM AUTHOR]

A milling cutter is one of the most important parts of machine tools. Its working status significantly influences the precision of workpiece. Due to the complex wear mechanism, the single sensor may be difficult to acquire the complete degradation information of milling cutters. Therefore, in this article, a feature learning based method is proposed to automatically extract features from multisource data and predict the remaining useful life of cutting tools in real time. First, a statistic-based method is constructed to detect and delete the outliers hidden in the monitoring data. Second, the clean data are input into a multiscale convolutional attention network (MSAN) to learn features and fuse multisource data. At last, the fused data are used to predict the remaining useful life of cutting tools in a regression layer. Compared with traditional tool life prediction methods, the proposed method is able to fuse multisource data through an attention feature learning model to conduct the life prediction of tools. Additionally, the data cleaning and model optimization methods are also proposed to promote engineering practicability. To validate the effectiveness of such method, the life testing experiments on milling cutters are conducted to obtain run-to-failure data. In those experiments, multisensor monitor data are acquired, which are used to conduct validation experiments testing the effectiveness of the proposed method. The results indicate the superiority of the proposed method in remaining useful life prediction milling cutters. [ABSTRACT FROM AUTHOR]

The flexible robot has more advantages over the traditional machine tools in machining complex workpieces like the 3D-printed part which has less residual material for removal. In robot machining, the geometric smoothness of moving joints is vital for enhancing efficiency and accuracy and the tool orientation should be limited in certain regions considering the interfering requirements. As the robot has six DoFs at least, redundant DoFs are observed for robot surface machining, which can be employed to optimize the smooth machining process under the tool orientation requirements. In this paper, the tool posture differential vector along the tool-tip path curve is optimized firstly. The whole trajectory is numerically integrated by the optimized differential vector subsequently. In each step, the minimum 2-norm of the joints’ differential vector along the tool path curve is set as part of the optimization objective to ensure the minimal change of joints. Furthermore, a state-related optimization objective for the differential vector is established to keep the tool orientation away from the boundary of the feasible region. Combining with the two objectives, the tool posture differential vector along the tool-tip path is optimized and the whole machining process is obtained by the numerical integration method. As a case study, the joint trajectories for an inclined butterfly curve are planned by the algorithm and machined by the UR-5 robot with the ROS controller. In addition, a comparative experiment is also provided to verify the effectiveness and optimality of the proposed method. [ABSTRACT FROM AUTHOR]

This paper aims to improve the performance of the robot-assisted bone milling operation. Based on a standard spinal surgery procedure, we established a dynamic bone milling model, which indicates that the cutting depth can be monitored based on the amplitudes of some specific harmonics of the milling sound pressure signal. The nominal frequency of these harmonics is an integer multiple of the spindle rotation frequency of the surgical milling tool. Therefore, we accurately extracted the absolute amplitude and frequency of the harmonics with nominal frequencies. We used the total harmonic amplitude to monitor the cutting depth and decrease the harmonic amplitude estimation error according to the absolute frequency of the first harmonic. A spine surgical robot carried out the bone milling experiment on artificial bone materials to verify. The results show that we can monitor the bone cutting depth with an accuracy of ±0.1 mm within the depth [0.1–1.2 mm] based on the auditory sense of the robot. The proposed method can improve the accuracy when a spine surgical robot performs the bone milling operation and make robot-assisted milling operation more accessible to inexperienced doctors via feedbacking the bone cutting depth in real-time. [ABSTRACT FROM AUTHOR]

One of the bottlenecks in flexible flank polishing is the nonuniform overcuts problem caused by the difficulties of the polishing tool to conform to variable curvatures of the freeform surface along the polishing path. Consequently, it will significantly reduce the quality of finished surfaces and the service life of polishing tools. To solve the problem, a novel path generation method is proposed in this article, which not only gets the uniform overcut at a single cutter location, but also keeps its uniformity over an entire polishing path. First, a tool orientation model is built on the freeform surface by analyzing the process of flexible flank polishing. Then, a novel indicator of overcut uniformity is proposed with the developed Dupin indicatrix, and the tool orientation is determined by maximizing the indicator. Next, based on Taylor expansion, a polishing path generation method is presented with the consideration of overcut uniformity. Finally, the proposed method is verified and analyzed relative to a comparison method by both virtual simulations and physical experiments. These results present a good consistency with each other and together provide strong support for the correctness, feasibility, and efficiency of the proposed method, which further contributes to surface quality and polishing tool's service life. [ABSTRACT FROM AUTHOR]

This article reports a slow-wave structure (SWS) working at 1 THz which can be fabricated through nano-computer numerical control (nano-CNC) technology for the first time. First, a 1 THz deformed quasi sine waveguide (D-QSWG) SWS has been designed and simulated in this article. To reduce the metal loss of input and output waveguide, a coupler which transit the waveguide to over mode rectangular waveguide has been designed. The simulation result shows that input and output waveguides with this coupler have lower metal loss than that of WR1 rectangular waveguide. To fabricate the designed D-QSWG SWS, tungsten steel endmills have been used. The fabricated SWS has the surface roughness around 58–74 nm, the corresponding effective conductivity is around $2\times 10^{{7}}$ –1.85 $\times 10^{{7}}$ S/m. And the cold test results show that the insertion loss of the fabricated model is less than 30 dB while the reflection loss is less than −15 dB in the frequency range of 0.998–1.016 THz, which has a good consistency with the simulated results. The beam-wave interaction simulation results based on the cold test results show that the designed D-QSWG traveling wave tube (TWT) has the output power of 300 mW, and the 3 dB bandwidth is around 3 GHz. [ABSTRACT FROM AUTHOR]

Spin-transfer torque (STT) magnetic random access memory (MRAM) is gaining commercial traction in low-density embedded and standalone memories, but the available market opportunities would grow exponentially if STT-MRAM could approach dynamic random access memory (DRAM) bit density. Of course, achieving DRAM density will require, among other things, demonstrating the ability to pattern MRAM bits at an extremely tight pitch. Here, an experimental demonstration of fabrication and electrical testing of a STT-MRAM bit array are reported. By optimizing the hard mask and ion beam etching (IBE) processes, MRAM bit arrays with a full pitch down to 50 nm are fabricated, in which the bits are individually tested using a novel bottom-point-contact method. [ABSTRACT FROM AUTHOR]

Machining conditions of real-time identification tools is a key and trending issue for the industry. This paper focuses on identifying whether machining is performed as well as the chatter conditions generated during re-machining processes. Identifying whether or not machining conditions are met allows users to ensure the normal operation of machining equipment and identify situations that do not match the current conditional, so that they can take early action and further save on operational costs for machining. The objective of this paper is to identify the milling machining conditions, and the identified conditions will be categorized into whether cutting is required as well as whether chatter is observed. In order to identify these three conditions, sound and vibration signals are captured by sensors inside the milling machine, and the process of identification is subsequently analyzed and conditions established. In this paper, in order to produce a valid model, the extracted machining signal is characterized as a training model by the properties of Approximate Entropy and Short-Time Fourier Transform, and the k-fold cross-validation criteria is utilized to present the identification results. Finally, In this study, the model recognition rate of support vector machine with approximate entropy was 91.4%. The recognition rate of the convolutional neural network with short time span Fourier transform was 95.5%. Finally, the reduced network architecture can significantly reduce the training time and maintain the recognition rate at 93.6%. [ABSTRACT FROM AUTHOR]

MnBi low-temperature phase (LTP) has excellent magnetic intrinsic properties and attractive characteristics as a permanent magnet material. It is necessary to synthesize fine particles of MnBi-LTP with a size close to that of its single magnetic domain ($\approx 500$ nm) to improve the magnetic anisotropic characteristics. Although the room-temperature ball milling process has been reported as a common method to reduce MnBi particle size, it has an inevitable limitation in reducing the powder size due to the low milling energy, as well as the powder agglomeration by the cold welding phenomenon. In this study, we synthesized fine particles of MnBi-LTP by the cryo-milling process at a temperature of 77 K. Phase analysis and magnetic properties were examined as a function of the amount of stearic acid for the cryo-milled powders. As a result, it was found that stearic acid as a surfactant plays an important role in suppressing the decomposition of the magnetic phase that occurs during the cryo-milling process. Consequently, high-purity fine MnBi-LTP particles, with (BH)max of 9.25 MGOe, were obtained through this method. Thus, this indicates that the cryo-milling process has the potential to synthesize fine MnBi-LTP particles with superior magnetic properties. [ABSTRACT FROM AUTHOR]

Industrial robot provides a promising alternative in freeform surface milling. However, due to its low stiffness, it is difficult to guarantee the machining quality. While existing research considers mainly the influence of robot posture on stiffness, the workpiece setup's influence is equally important. In this article, to ensure the overall workpiece's robot stiffness meets the requirement of stiffness threshold in robotic milling, a method for simultaneously optimizing the robot posture and the workpiece setup is proposed. First, to evaluate the robot stiffness during machining, this article presents a new stiffness index considering the robot's rotational deformation. And then, an optimization model is established to optimize both the robot redundancy and the workpiece setup, considering the constraints of joint limitation, singularity-free and collision-free. Moreover, for complex freeform surfaces, to obtain the minimum number of posture changes of the robot and workpiece under the premise of meeting the limit of stiffness threshold, this article constructs a minimum set covering problem, which is solved by a clustering algorithm and a greedy algorithm. Finally, simulations and experimental studies are conducted to validate the effectiveness of the proposed robot stiffness index and the proposed optimization method, showing that the robot stiffness is improved during a milling process of the entire workpiece. [ABSTRACT FROM AUTHOR]

This work presents the design of an additively manufactured W-band bandpass filter and a subtractively manufactured W-band diplexer to demonstrate the use of admittance inverter sequences for the ease of manufacture at millimeter-wave frequencies. Contrary to typical impedance inverters (E-plane and H-plane irises), the use of admittance inverters (E-plane and H-plane stubs) allows for larger dimensions to be specified and ultimately does not impede the general waveguide path. The proposed bandpass filter is designed with all E-plane stubs, while the diplexer is designed with one branch using both E-plane and H-plane stubs as an arbitrary sequence, and the second branch using all H-plane irises. The additively manufactured bandpass filter is fabricated using the most elementary-level stereolithography (SLA)-based methods, demonstrating that a hobbyist-type SLA printer and metallization method can procure exceptional results for millimeter-wave filter designs. The subtractively manufactured diplexer is fabricated using high-precision computer numerical control (CNC) milling to highlight the use of arbitrary inverter sequences in a more complex and robust design profile, while the dispersive transmission zeros that are caused by over-moding of the inverter stubs are used to demonstrate unique isolation characteristics in the upper W-band region. The design concepts, fabrication profiles, simulations, and measurements which are presented in this work highlight a viable option for overcoming miniaturized dimensions in millimeter and submillimeter-wave applications. [ABSTRACT FROM AUTHOR]

The occurrence of chatter in the machining process accelerates tool wear and breakage, reduces the service life of tools and machine tools and the surface accuracy of workpieces. Therefore, how to quickly and accurately detect chatter and adjust process parameters to prevent chatter has become a research hotspot today. This article proposes a new method to detect the machining state in the milling process by using the sensor signal sensitive feature data set and the Mahalanobis-Taguchi System. First, a method for extracting the comprehensive characteristics of nonlinear time-domain signals in the cutting process is proposed. This method can realize the dimensionality reduction of the time-domain data features. Then, time-frequency domain methods such as variable mode decomposition energy entropy, multi-scale power spectrum entropy and multi-scale displacement entropy are used to process the processed signals collected by multiple sensors to obtain the characteristic data set related to flutter. Take the feature data set as the measurement scale to participate in the construction of the Mahalanobis-Taguchi System classifier. Using the experimental data of milling titanium alloy thin-walled parts with end mills, the Mahalanobis space of cutting chatter was constructed, and the chatter detection system was verified. It is found that this method can accurately detect the cutting processing state. The research results can lay the foundation for advancing the industrialization of intelligent cutting processing. [ABSTRACT FROM AUTHOR]

A rectangular waveguide bandpass filter for $Q$ -band with simple fabrication is proposed in this letter. The design is based on the use of the first passband replica of commensurate-line stepped-impedance structures and achieves the suppression of their inherent low-pass response. In order to do it, the filter is implemented by rectangular waveguide sections with different widths and heights that can be analytically calculated. The technique is validated by a ninth-order Chebyshev filter with passband between 40 and 43 GHz and fabrication yield equal to 84% for a manufacturing error of $\pm 20~\mu \text{m}$. The measured results of the prototype fabricated with computer numerical control (CNC) milling are in good agreement with the simulated ones. [ABSTRACT FROM AUTHOR]

This article presents precision silicon micromachined waveguide calibration standards for use with terahertz vector network analyzers. This enables the creation of precise, highly repeatable, and traceable terahertz waveguide standards, surpassing the limits of current metrology techniques. A single silicon-on-insulator wafer with the appropriate device and handle layer thicknesses is used to implement a wide range of calibration and verification standards. The design of the standards is discussed from mechanical, electrical, and end-user perspectives. Silicon is shown to be the most promising material for the realization of precision metrology standards. We outline the potential to scale the presented design to at least 2.6 THz. Eight types of WM-570 standard, totaling 15 prototypes, are fabricated and characterized between 325 and 500 GHz. Despite some fabrication anomalies, all devices offer excellent performance. The best micromachined standards offer a return loss in excess of 40 dB, an insertion loss of below 0.1 dB, and a phase error of less than 1°. The standards are utilized in both one- and two-port calibrations, including the multiline through-reflect-line algorithm. These are benchmarked against calibrations performed using conventional metallic standards, with a high degree of agreement observed between error-corrected measurements of a range of test devices. [ABSTRACT FROM AUTHOR]

This article puts forward a high repetition rate and high-voltage resonant pulse generator for plasma-assisted milling. This circuit uses only one semiconductor switch with an antiparallel diode and works in the resonant mode with the help of a resonant inductor, a resonant capacitor, and a pulse transformer to generate high-voltage pulses. An equivalent circuit of the proposed topology considering parasitic elements is established. Based on the equivalent circuit, the working principle of the pulse generator is analyzed in detail. In order to verify the theoretical analysis and circuit operation, a laboratory prototype with a 150-V dc input is implemented. The pulse repetition rate can be adjusted from 5.32 to 18.90 kHz, and the peak output voltage correspondingly varies between 8.84 and 11.7 kV. The pulse generator is used to drive a dielectric barrier discharge plasma-assisted milling chamber. Experimental results show that the pulse generator can work stably. [ABSTRACT FROM AUTHOR]

High-precision remaining wall thickness is desirable in the mirror milling of large thin-walled parts. However, the workpiece deformation caused by sheet forming, clamping, and self-gravity makes it difficult to control the thickness if the original tool path generated from the designed CAD model is used directly. In order to solve this problem, the deformed workpiece surface is supposed to be reconstructed, and the original tool path should then be adjusted. In this article, based on a self-developed multiprobe ultrasonic measurement system, an autonomous profile tracking approach, mainly including adaptive sampling point prediction, boundary processing, and feature point extraction, is proposed to scan the deformed surface. The sampling point prediction algorithm calculates the position and orientation simultaneously for the next sampling point. In particular, a current-measurement-output-based orientation prediction algorithm is proposed to guarantee the autonomy of the profile tracking, and a reference-measurement-point-based orientation prediction algorithm is proposed to improve the prediction accuracy. The boundary processing algorithm controls the scanning direction and ensures that the sampling process is implemented inside the measurement boundary. The online feature point extraction algorithm reduces the redundant points for the following surface reconstruction. Practical experiments on freeform surfaces with/without complex boundaries verified the feasibility and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Recent advances in artificial intelligence (AI) technology have led to increasing interest in the development of AI-based tool condition monitoring (TCM) methods. However, achieving good performance using these methods relies heavily on large training samples, which are both expensive and difficult to obtain in practical TCM applications. This article addresses this issue by employing a much smaller training sample composed of a non-exhaustive sampling of experimentally measured cutting force signals in conjunction with a novel data augmentation method that combines numerical simulation with a generative adversarial network (GAN). First, cutting force signal samples not present in the experimental dataset are obtained by numerical simulation using a finite element method simulated based on the Johnson–Cook model. Second, the GAN is employed to synthesize additional samples that are similar to both the simulated samples and the experimentally measured samples. The synthesized samples are combined with the measured and simulated samples to produce an appropriately large dataset necessary for the effective training of an AI classifier. The proposed sample augmentation method is applied in milling TCM experiments, and the classification accuracies obtained with several AI classifiers trained with the augmented dataset were all close to or equal to 100%. [ABSTRACT FROM AUTHOR]

Often, the condition of a machine tool is detected indirectly in the reduced quality of manufactured parts upon visual inspection. Reliable and efficient machine tool condition monitoring is indispensable for manufacturing. Furthermore, issues affecting machine tools are closely related to pathologies associated with many other industrial electromechanical systems. An instrumentation and measurement solution for tool condition monitoring is presented in this article. A signal processing algorithm and instrumentation hardware are proposed to avoid intrusive sensor installations or modifications of the machine under test. The cyclostationary properties of machine vibration signals drive fault-detection approaches in the proposed sensing hardware and signal processing chain. A sample of end mills from an industrial facility is used to validate the tool condition monitoring system. [ABSTRACT FROM AUTHOR]

This article deals with investigations of slot reflectarray antennas constituted by composite panels and optimized for milling manufacturing. It is shown that a certain combination of the unit-cell geometry parameters may lead to the gain degradation. Analysis of the unit cell shows that this results from the parallel-plate modes excitation. The Floquet circle diagram is used to define conditions for the excitation of these modes. Examples of field plots in the unit cell are given. Theoretical data have been verified by experimental investigations. Presented results allow us to choose proper geometry parameters of the unit cell for slot reflectarray antennas at the initial stage of the development. Some slot reflectarray antennas prototypes are considered as well. [ABSTRACT FROM AUTHOR]

Air annealing has been found to increase both Tc and Jc of FeSe1-xTex single crystals. However, there are indications that this effect might be limited to the surface of the crystals. In this work, we report on the changes in the surface structure and composition, Tc, and Jc of air-annealed FeSe0.35Te0.65 single crystals. Using XPS depth-profiling and cross-sectional STEM, we found that both the formation of an iron oxide layer and the resulting reduction of interstitial iron in the bulk are confined to exposed surfaces of the single crystals. This is linked to the largest improvement in the superconducting transition width and critical current density close to the surface of the sample. [ABSTRACT FROM AUTHOR]

The 1144 family of Iron Based Superconductors (IBSCs) is characterized by critical currents among the highest for single crystalline IBSCs. The synthesis of polycrystalline compounds is usually carried out through high temperature (T > 900 °C) processes. These methods, justified by a supposed thermodynamic instability of the 1144 phase at low temperature, are complicated by the presence of highly volatile elements and require fast heating and cooling steps. Here, it is shown how a High Energy Ball Milling (HEBM) treatment is effective to promote the reaction among the starting elements, thus favoring the synthesis of the 1144 phase at lower temperature. The evolution of the powders has been assessed for different milling times, observing the consumption of the starting reactants and the formation of crystalline pnictide phases. Different thermal treatments have been coupled to the HEBM treatment, allowing the study of the effect of time and temperature of the thermal step on the materials properties. It has been observed how the formation of the superconducting phase occurs on the HEBM samples at 500 °C and 600 °C. Critical temperatures comparable with data reported in the literature were obtained. Granularity phenomena and critical current density of sintered samples are highly dependent on the processing variables. [ABSTRACT FROM AUTHOR]

Bone milling is one of the most widely used and high-risk procedures in various types of surgeries, and it is important to be noted that the experienced surgeon can perform such an operation safely. The objective of this article is to enhance the safety of the robot-assisted milling operation with the inspiration of human haptic perception. The emergence, coding and perception of the human haptic are introduced. Following this, a single axis accelerometer that measures the vibration of the surgical power tool is mounted in the robot arm, and the recorded acceleration signal is encoded as parallel stream of binary data. The data are subsequently inputted to the Hopfield network so as to identify the milling state. Inspired by human inference procedure, the fuzzy logic controller is introduced to control the robot to track the desired state when performing bone milling operations. A real-time implementation of the proposed method on a digital signal processing is also described. The experimental results in milling porcine spines prove that the robot accurately discriminates different milling states even when the additive noise is serious, and the safe motion control of the robot is also realized. [ABSTRACT FROM AUTHOR]

This article presents different physical arrangements of filters using conical posts as the basic element of design. The proposed resonator is similar to that of the classical combline filter, however, in this case, a conical post (truncated cone) is exploited. A hollowed enclosure is positioned on top of a rectangular metallic cavity for housing the upper part of the conical resonating post. Considering that the post upper radius is smaller than the post lower radius, an enclosure having the same dimensions as the resonating post can be taken. This results in a housing that can also work as an additional resonator for another cavity. As a result, cavities can be piled in a vertical arrangement and the conical post of each cavity is also used for housing the post of the cavity below it. Mixed vertically and/or horizontally arrangements are also feasible. More compact structures can be achieved with the possibility to obtain different footprints while maintaining similar unloaded $Q$ -factors than conventional combline filters. The structure also has the advantage of having a wider spurious-free range than the classical combline filter configuration (cylindrical post inside a rectangular cavity). Enhanced responses with higher rejections are also possible thanks to the introduction of transmission zeros. Several different filter configurations are presented in this article: 3-order filter and 4-order filter. The design procedure is explained for both of them. A 4-order filter has been manufactured using additive manufacturing techniques and measured in order to validate the proposed structure. [ABSTRACT FROM AUTHOR]

Chatter is a kind of self-excited vibration which will destroy the manufacturing process badly. The detection or identification of chatter is attracting considerable interest for several years. In this article, a chatter identification method called reinforced k-nearest neighbors is proposed to realize both chatter identification and model self-learning. We conducted large amounts of experiments on a computer numerical control milling machine with different types of sensors in high-speed milling processes, where chatter occurs frequently. Signals from different sensors are compared and features are extracted by statistical methods. Then, a dimensional reduction method t-distributed stochastic neighbor embedding is used for extracting sensitive information and visualization. Finally, the proposed reinforced k-nearest neighbors is used for chatter identification under different cutting conditions and the experiment results show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In the milling process, large tool diameter can get higher rigid and machining efficiency. To improve machining efficiency for 2 1/2-axis part, an image skeleton-based method is proposed in this paper. First, a rasterization-based method for converting the part section graphics into an image for image analysis with high accuracy is developed. Second, the Euclidean distance field is calculated for the image to get the initial skeleton; then to get the accurate skeleton of the image, a partial differential equation-based method is employed to refine the initial skeleton. After that, an objective function based on the residual area of the material is established, which is solved by the genetic algorithm to obtain the optimal tool combination for a given number of tools. Finally, the developed approach is validated in the milling of a port part for tool selection. Results show that the selected toolset can remove most of the material effectively. Furthermore, analysis results show that the increase of tool types will increase the available cutting area ratio, but it will decrease the growth.

Machinery is one of the major fields that impact the growth of the country. Computer numerical control (CNC) plays a vital role in manufacturing machining parts. Each product manufactured from CNC has its performance index requirements based on its usage. The performance indexes, such as surface roughness and geometric tolerances, are important for any CNC machined product. The performance index values are affected by several controllable and uncontrollable parameters, among which the controllable parameters can be tuned to get the desired performance index values. Hence, in this article, we proposed an intelligent prediction model to predict the performance index values, such as surface roughness and geometric tolerances, considering the controllable machining parameters as the input for the model. The experimental results show that the performance index can be predicted effectively with various CNC machining parameters. Therefore, the model can be useful for the manufacturers for achieving the desired performance index values. [ABSTRACT FROM AUTHOR]

We have used a neon focused-ion-beam to fabricate both nanoscale Nb Dayem bridges and NbN phase-slip nanowires located at the short-circuited end of quarter-wavelength coplanar waveguide resonators. The Dayem bridge devices show flux-tunability and intrinsic quality factor exceeding 10 000 at 300 mK up to local fields of at least 60 mT. The NbN nanowires show signatures of incoherent quantum tunneling of flux at 300 mK. [ABSTRACT FROM AUTHOR]

Security-critical applications on integrated circuits (ICs) are threatened by probing attacks that extract sensitive information assisted with focused ion beam (FIB)-based circuit edit. Existing countermeasures, such as active shield, analog shield, and t-private circuit, have proven to be inefficient and provide limited resistance against probing attacks without taking FIB capabilities into consideration. In this article, we propose an FIB-aware anti-probing physical design flow, which considers FIB capabilities and utilizes computer-aided design (CAD) tools, to automatically reduce the probing attack vulnerability of an IC’s security-critical nets with minimal extra design effort. The floor-planning and routing of the design are constrained by incorporating three new steps in the conventional physical design flow, so that security-critical nets are protected by internal shield nets with low overhead. Results show that the proposed technique can reduce the vulnerable area exposed to probing on security-critical nets by 100% with all critical nets fully protected for both advanced encryption standard (AES) and data encryption standard (DES) modules. The timing, area, and power overheads are less than 3% per module, which would be negligible in a system-on-chip (SoC) design. [ABSTRACT FROM AUTHOR]

The empirical wavelet transform (EWT) has shown its effectiveness in some applications. However, when noisy and nonstationary signals are analyzed, some local maxima may appear and be retained in the peak sequence mistakenly, so improper segmentation in the frequency domain will occur. In our research, the morphological EWT (MEWT) method is proposed based on morphological filters (MFs) and the 1-D Otsu method to mitigate the boundary segmentation drawback of the EWT, and it can be applied in chatter detection because of its good performance in finding the optimal chatter frequency band. First, the local maxima distribution plane is calculated using MFs. Then, the 1-D Otsu method processes the distribution plane and then achieves the optimal threshold for MFs. For MEWT’s better application in chatter detection, an automatic selection of the parameter $K$ using kurtosis is proposed and it breaks away from the previous empirical selection. Finally, since it is known that energy will transfer to chatter frequency bands when chatter occurs in the milling, the energy entropy of each subsignal used is to detect chatter frequency bands and choose the optimal chatter monitor indicator. The relevant simulation and experimental signals have been analyzed for verifying the validity of the MEWT and the novel chatter detection method with strong sensitivity to chatter. [ABSTRACT FROM AUTHOR]

M-type hexagonal ferrite powder was prepared by the molten salt flux method calcined at a relatively low temperature (850 °C) with a product yield of 99.87%. The synthesized sample was then milled for 3 h by high-energy ball milling in toluene suspension to obtain ultrafine nanoparticles. The structural, morphological, and magnetic properties of the particles were investigated to observe the effect of milling on the molten salt synthesized powder. The analyses reveal the presence of barium hexaferrite (BaFe12O19) as the main phase with less impurities. Average crystallite size, determined by X-ray diffraction (XRD), decreased from 81 ± 20 nm to 52 ± 5 nm after ball milling. The Fourier transform infrared (FTIR) spectra ensure the tetrahedral and octahedral positions in barium hexaferrite structure with an increase in the intensity of absorption bands after milling. The electron paramagnetic resonance (EPR) signal shows a broad line that demonstrates a decrease in the amplitude of the milled sample. Furthermore, remanence measured by vibrating sample magnetometer (VSM) increases from 8.5 to 25 emu/g. A 72% increase in coercivity and 84% increase in magnetic saturation is observed for the milled samples compared to that of pure BaFe12O19 (unmilled). The variations of the magnetic properties are thus attributed to the reduction in crystalline size and lattice parameters after milling. [ABSTRACT FROM AUTHOR]

This paper presents an active control method, consisting of an adaptive sliding-mode controller (ASMC) and a displacement field reconstruction (DFR) method, for chatter suppression in turning of thin-walled workpieces (such as compressor disks and casings in aircraft engines) where low workpiece stiffness renders machining with potential regenerative chatter. Due to the presence of multi-modal dynamics, variant modal parameters, and measurement difficulties, active chatter control of thin plate turning has been challenging. Unlike existing controls based on a lumped-parameter single degree-of-freedom cutting model, a distributed-parameter dynamic model of a rotating thin plate with multiple vibration modes is used to analyze the machining stability with the designed controller. Moreover, model parameters of the plate are not needed to construct the controller. The DFR is employed to capture the plate dynamic behavior for feedback to the ASMC during turning, overcoming the long existing difficulties to measure plate vibration at the cutting point. A fast tool servo is utilized in the control implementation. Theoretical analyses, numerical simulations, and experimental evaluation on a lathe demonstrate that chatter in thin plate turning can be effectively attenuated with the proposed active control method. [ABSTRACT FROM AUTHOR]

Goal: In the context of robot-assisted laminectomy surgery, an analytical force model is introduced to guarantee procedural safety. The aim of the method is to intraoperatively monitor the cutting depth via modeling the milling status. Methods: The theoretical dynamic model for the surgical milling process is based on the flute geometry of the ball-end milling tool. A particle swarm optimization algorithm is exploited to calibrate the model using the local average force, and to validate it using the denoised dynamic force. A wear detection method based on the fast Fourier transform is proposed to determine the quality of the tool geometry and to avoid using worn tools, which may lead to imprecise and unsafe operations. Results: Milling experiments were performed on machined fresh bovine femur bones. The experimental results thus obtained from the mechanical model are in good accordance with the numerical model. The proposed method can monitor the current cutting depth with an accuracy of ±0.1 mm in regions located within the depth [0.8–1.2 mm], and ±0.2 mm within [1.2–1.6 mm]. Conclusion: The proposed model can successfully estimate the milling force and the cutting depth intraoperatively in experimental conditions. Significance: This approach has the potential to improve the safety of laminectomy operations in humans, and make it more accessible to younger surgeons by lowering the required manual skills threshold. Note to Practitioners—The motivation behind this paper is driven by current safety issues existing in robot-assisted bone-cutting surgery, such as laminectomy. The main contribution of the present work is an algorithm to monitor the current cutting depth. Compared to traditional systems, the key characteristics of the introduced model are: real-time (it can be used intraoperatively); precision and safety (prediction error up to ±0.2 mm in target regions); and ease of use (no other image guidance or tracking system is required). The approach can successfully predict the current milling status and is sensitive to changes in force conditions, which is especially crucial to detect the contact point between the ball-end milling tool and the target bone. In summary, the proposed approach addresses the challenge of improving the safety of robot-assisted surgery via monitoring of the cutting depth. Experimental results on a fresh bovine femur demonstrate promising performances. The present implementation specifically targets bone milling procedures, yet it can easily be extended to a wide range of other similar clinical or industrial applications. Applicability is supported by the fact that the proposed algorithm can be implemented as a plug-in module and integrated into already existing image-guided robotic surgery platforms. [ABSTRACT FROM AUTHOR]

Flake-shaped FeSi-based metallic amorphous alloy particles, having an aspect ratio as high as 175:1, were prepared by ball-milling gas-atomized amorphous powders of an effective diameter of 20 µm. The starting powder has a saturation magnetic flux density Bs of 1.5 T and a coercivity Hc of 94 A/m. The aspect ratio of the flakes, as well as their magnetic properties, were controlled by milling process parameters, such as duration, speed, and the type, mass, and diameter of the milling balls. To minimize the oxidation of the charge, the powders were handled in an argon gas-purged glove box, milled in toluene, and subsequently dried in vacuo. Subsequently, soft magnetodielectric composites were prepared by suspending and aligning the FeSi-based powders in paraffin wax or epoxy resin. The composites were then pressed into toroids for measurements of their high-frequency complex permeability by a vector network analyzer. The influence of the flakes’ aspect ratio and volume loading fraction on the permeability of the composites were investigated. Results indicate that the composite permeability increases with the flakes’ aspect ratio. For example, for a given loading factor of 30 vol.%, the composite permeability at 0.1 GHz nearly tripled and approached the value of 10 by increasing the aspect ratio of the FeSi-based inclusions from 1 (spheres) to greater than 175:1 (flakes). [ABSTRACT FROM AUTHOR]

This paper presents a three-degree-of-freedom (3-DOF) ultrasonic vibration tool holder for milling and drilling operations. The 3-DOF vibrations are generated by a novel actuator that contains three groups of piezoelectric rings actuating in X-, Y-, and Z-directions at the natural frequencies of the structure. The vibrations in XY plane are excited at the frequency but with slightly different amplitudes to produce an elliptical locus for intermittent tool-workpiece contact, which assists milling process, and the vibrations along Z-axis are used in drilling operations. The 3-DOF ultrasonic vibration actuator excites the structure's natural frequencies, which are above 16 kHz with amplitudes up to 20–25  $\mu$ m. A control system has been developed for tracking the resonance frequencies during cutting from the phase of actuator's impedance. Preliminary cutting tests show that the cutting forces are reduced by over 30% with the ultrasonic vibration assisted milling and drilling operations. [ABSTRACT FROM AUTHOR]

The microstructure and magnetic properties of bulk crystalline- and ball-milled RCo5 intermetallics synthesized via time-staged high-energy ball milling (HEBM) process are presented. The presence of CaCu5 type of crystal phase was confirmed in all investigated specimens but for the prolonged milling the emergence of amorphous phase was also detected. The impact of the milling stage on the final crystallites/particles size and shape is evident. The significant influence of HEBM on the enhancement of the coercivity, magnetic anisotropy, and maximum energy product was found. The noticeable dependence of magnetic properties on rare earth type and pulverization time was observed. [ABSTRACT FROM AUTHOR]

This paper reports the preparation of manganese monoboride (Mn50B50) nanocrystals by high-energy dry milling of as-cast bulk ingots. The ingot was fabricated by using an arc-melting technique. The as-made sample exhibits an orthorhombic structure with a saturation magnetization of 130 emu/g and a magnetic transition at 566 K. The effects of milling conditions on the structural and magnetic properties of Mn50B50were investigated in detail. Fully stoichiometric Mn50B50nanocrystals were produced with an average crystal size ranging from 23 to 11 nm after 2–7 h of dry milling. The as-milled MnB nanocrystals were found to exhibit soft magnetic behavior at room temperature with near-zero coercivity; saturation magnetization decreased to 85 emu/g with increased milling time because of a disordered spin configuration on the surface. High-saturation magnetization and chemical stability, and a low-cost manufacturing process make nanocrystal Mn50B50a promising candidate for technological applications such as magnetic hyperthermia, magnetic data storage, and magnetic imaging. [ABSTRACT FROM AUTHOR]

Two types of re-substituted (FeCo)2B-type alloys with stoichiometric (Fe0.675Co0.3Re0.025)2B and 1.5 at% boron-excess compositions were prepared by suction casting and subsequent mechanical milling and annealing. Phase evolution in the (FeCo)2B-type alloys in the course of mechanical milling and annealing was investigated. Single-phase re-substituted (FeCo)2B-type material was prepared from stoichiometric (Fe0.675Co0.3Re0.025)2B by the combination of suction casting and mechanical milling. The two alloys had the same phase constitution of (Fe, Co)2B-type and amorphous phases in heavily milled state. However, the heavily milled alloys had different phase constitution after annealing; the stoichiometric alloy consisted of single (Fe, Co)2B-type phase, while the boron-excess alloy consisted of two-phase mixture of (Fe, Co)2B-type and (Fe, Co)B-type phases. The two heavily milled alloys had similar coercivity of around 1 kOe after full annealing. [ABSTRACT FROM AUTHOR]

In this letter, additive manufacturing technologies have been evaluated for waveguide antenna array prototyping at Ku band. Direct metal laser sintering (DMLS) and stereolithography have been assessed in terms of manufacturing limitations, electrical performance, accuracy, cost and weight, compared with traditional manufacturing methods. This assessment is performed on a corporate-fed waveguide array antenna for end-user digital broadcast satellite communications at Ku band. The objective is to manufacture this intricate multilayer structure as a single block, in order to prevent contact and leakage issues in the interface between antenna layers. This monolithic implementation is unfeasible with conventional milling in aluminum, renowned in the literature for its reliability in waveguide antenna implementation. A prototype has been machined with such technique as a reference for experimental results. A single block fabrication has been possible by DMLS, presenting a similar performance to the reference prototype. Experimental results, including impedance matching, realized the gain and axial ratio have been performed on the antenna prototypes. A 14.7% effective bandwidth has been obtained for the DMLS antenna. [ABSTRACT FROM AUTHOR]

This letter focuses on comparing manufacturing features of three-dimensional (3-D) printing techniques versus conventional computer numerical control (CNC) milling in the context of gap waveguide technology. To this end, a single-layer array antenna has been designed as a demonstrator. The antenna under test, intended for Ka-band, is composed of 8 $\times$ 8 radiators fed by a gap-waveguide (GW) corporate network. Two identical prototypes have been manufactured, but each applying a different fabrication technique, i.e., 3-D printing and CNC milling. The experimental results of both antennas are presented, under the same conditions and measurement facilities. The conclusions drawn in this letter provide a valuable assessment of 3-D-printing viability for GW arrays against the conventional milling technique. [ABSTRACT FROM AUTHOR]

Chatter is a typical kind of unstable dynamics often encountered in machining processes, which often results in overcut and rapid tool wear. Hence, chatter phenomenon worsens the surface quality and reduces productivity in milling systems as well. Recent years have witnessed a surging industrial demand of high quality and high efficiency machining. Specifically, for low radial immersion milling situation, large depth of cuts is inevitably needed so as to increase the machining efficiency. To fulfill such a task, this paper develops a robust active control method to mitigate the chatter dynamics of low radial immersion milling processes. The present approach increases the axial depth of cuts, and the improvement is inversely proportional to the radial immersion ratio. Finally, case studies are conducted to show the substantially enlarged stable region in the stability lobe diagram (SLD) spanned by spindle rotational speed and axial depth of cut. Thus, the method can be expected to improve the efficiency of milling processes. Note to Practitioners—This paper seeks to mitigate machining chatters that worsen the workpiece surface quality in high-speed machining processes. To overcome such unexpected effects, traditional passive schemes simply adjust the rotational speed and cutting depth, which do not seek assistance from external power sources. Hence, neither the damping nor stiffness of the system can be changed, and a high maximal material removal rate (MMRR) is arduous to obtain. By contrast, this paper develops a robust active control method to mitigate the chatter dynamics for low radial immersion milling. In the design stage of the milling spindle, two active magnetic bearings (AMBs) are embedded in the tool house as control actuators, which produce extra force to counteract the chatters. In real milling processes, the chatters are detected by the associated inductive displacement sensors around the AMBs, and an uncertainty model is accordingly established with low radial immersion. With the detected vibration displacements, robust active control signals are calculated online, and then fed into the power amplifiers to drive the two AMBs. By this means, a closed-loop active control system is thus established for milling processes, which substantially enlarges the stable region of the SLD spanned by rotational speed and cutting depth. As a result, the proposed active control scheme can be expected to increase the MMRR and, hence, to enhance the productivity of milling processes. [ABSTRACT FROM AUTHOR]

The fast development of flip-chip (FC) devices has helped to keep ICs on pace for Moore’s law. FC devices have many buried interfaces, the structures of which all need to be investigated in order to optimize them. It is extremely difficult to examine molecular structures of buried interfaces in samples with multiple layers due to the lack of appropriate analytical tools. In this paper, real FC-on-leadframe devices, manufactured by Texas Instruments Incorporated, were investigated using the intrinsically interface-sensitive technique and sum-frequency generation (SFG) vibrational spectroscopy. By milling down the Si wafer, we can probe the polyimide (PI)/mold compound (MC) interface. By milling down further, we can examine the air/MC and the MC/leadframe (LF) interfaces. Methylene and methyl groups were detected from each of the three interfaces, and the orientation of methyl groups was determined at each interface. It was calculated that at the PI/MC interface, the methyl group tilt angle was 20° (from the surface normal). For the air/MC interface, the tilt angle was 43.5°, and for the LF/MC interface, the tilt angle was measured to be 45°. The deduced different methyl orientations at the two buried solid/solid interfaces can be interpreted by the interfacial interactions. The PI surface is more hydrophobic than the LF surface; therefore, it has more favorable interactions with the hydrophobic methyl groups, leading to a more “standing up” (smaller tilt angle) position for the methyl groups at the PI/MC interface. In this paper, SFG was successfully applied to study the buried interfaces in real devices. The SFG method used in this paper is general and can be applied to other real-world, complicated thick systems. [ABSTRACT FROM AUTHOR]

Nuclear fusion energy is perhaps one of the most demanding challenges that the scientific community is facing. Unfortunately, the plasma is affected by microturbulence, which is still not fully understood, but which can degrade plasma confinement. The 0.346-THz backward-wave oscillator (BWO) is the enabling device for a high-k plasma collective scattering diagnostic that will provide unprecedented insight on turbulence thereby contributing to the realization of fully operational fusion reactors. This paper describes the final fabrication phase of the 0.346-THz BWO for the collective scattering diagnostic jointly performed in an international project, involving three leading institutions in vacuum electronics. The advancements in technology will open the route to new families of terahertz vacuum electron devices to enable new terahertz applications and provide industry with new advanced processes. [ABSTRACT FROM AUTHOR]

Direct-write laser grayscale lithography has been used to facilitate a single-step patterning technique for multilayer lead zirconate titanate (PZT) thin films. A 2.55- \mu \textm -thick photoresist was patterned with a direct-write laser. The intensity of the laser was varied to create both tiered and sloped structures that are subsequently transferred into multilayer PZT(52/48) stacks using a single Ar ion-mill etch. Traditional processing requires a separate photolithography step and an ion mill etch for each layer of the substrate, which can be costly and time consuming. The novel process allows access to buried electrode layers in the multilayer stack in a single photolithography step. The grayscale process was demonstrated on three 150-mm diameter Si substrates configured with a 0.5- \mu \textm -thick SiO2 elastic layer, a base electrode of Pt/TiO2, and a stack of four PZT(52/48) thin films of either 0.25- \mu \textm thickness per layer or 0.50- \mu \textm thickness per layer, and using either Pt or IrO2 electrodes above and below each layer. Stacked capacitor structures were patterned and results will be reported on the ferroelectric and electromechanical properties using various wiring configurations and compared to comparable single layer PZT configurations. [ABSTRACT FROM AUTHOR]

Physiological studies in humans proved that the central nervous system automatically integrates the information from different sensory systems. Inspired by the integration mechanism, this study aims to yield accurate perception of the surgical field during milling operation. The dynamic model of the surgical milling process is developed theoretically, and the model considers the influence of the unbalance in the rotating machine and the time-variant cutting force. On the basis of the theoretical analysis, the monitoring of the milling process can be realized to determine the state of the operation. An accelerometer and a microphone are used to measure the acceleration of the milling device and the sound pressure generated during bone milling separately, and then the correlation coefficient between the harmonics in the two signals is fed into the artificial neural network. The output of the artificial neural network is used to determine whether the milling device is cutting the cortical bone, the cancellous bone, the muscle or nothing (i.e., idle running). The experimental results in in vitro porcine spines show that the proposed method is very sensitive to the phenomenon of tissue wrapping in the surgical field, and it can identify the predetermined states correctly. [ABSTRACT FROM PUBLISHER]