Behavior Of Machine Research Articles

Additive manufacturing: A machine learning model of process-structure-property linkages for machining behavior of Ti-6Al-4V

Prior studies in metal additive manufacturing (AM) of parts have shown that various AM methods and post-AM heat treatment result in distinctly different microstructure and machining behavior when compared with conventionally manufactured parts. There is a crucial knowledge gap in understanding this process-structure-property (PSP) linkage and its relationship to material behavior. In this study, the machinability of metallic Ti-6Al-4V AM parts was investigated to better understand this unique PSP linkage through a novel data science-based approach, specifically by developing and validating a new machine learning (ML) model for material characterization and material property, that is, machining behavior. Heterogeneous material structures of Ti-6Al-4V AM samples fabricated through laser powder bed fusion and electron beam powder bed fusion in two different build orientations and post-AM heat treatments were quantitatively characterized using scanning electron microscopy, electron backscattered diffraction, and residual stress measured through X-ray diffraction. The reduced dimensional representation of material characterization data through chord length distribution (CLD) functions, 2-point correlation functions, and principal component analysis was found to be accurate in quantifying the complexities of Ti-6Al-4V AM structures. Specific cutting energy was the response variable for the Taguchi-based experimentation using force dynamometer. A low-dimensional S-P linkage model was established to correlate material structures of metallic AM and machining properties through this novel ML model. It was found that the prediction accuracy of this new PSP linkage is extremely high (>99%, statistically significant at 95% confidence interval). Findings from this study can be seamlessly integrated with P-S models to identify AM processing conditions that will lead to desired material behaviors, such as machining behavior (this study), fatigue behavior, and corrosion resistance.

House-edge information and a volatility warning lead to reduced gambling expenditure: Potential improvements to return-to-player percentages

Cost-of-play information is one public health intervention recommended to help reduce gambling-related harm. In the UK, this information is given on electronic gambling machines in a format known as the “return-to-player”, e.g., “This game has an average percentage payout of 90%.” However, previous evidence suggests that this information could be improved by equivalently restating it in terms of the “house-edge”, e.g., “This game keeps 10% of all money bet on average.” A “volatility warning,” stating that this information applies only in the statistical long-run, has also been recommended to help gamblers understand cost-of-play information. However, there is no evidence comparing these information provisions’ effect on gamblers’ behavior. An experiment tested US gamblers’(N = 2433) incentivized behavior in an online slot machine, where this information was manipulated between-participants along with a counter showing the total amount bet. Preregistered analyses showed that participants gambled significantly less when house-edge information or a volatility warning were shown compared to standard return-to-player information, with no effect of the total amount bet counter, and no significant interaction effects. However, these significant findings had small effect sizes, suggesting that a public health approach to gambling should not rely on informational provisions only. Subject to supportive evidence from more ecologically-valid designs such as field studies, these results suggest that improved cost-of-play information could lead to reduced rates of gambling expenditure and therefore benefit a public health approach to gambling.

Cutting forces during drilling of a SiCp reinforced Al-7075 matrix composite

Abstract In this study, an Al-7075 matrix alloy reinforced and by 5, 10, and 15 wt% silicon carbides were produced as a composite material using the stir casting method. An investigation of the hardness, density, and microstructure of the matrix alloy and the composite materials was conducted. The following instruments were used for the microstructure studies: optical microscope and scanning electron microscope (SEM). The machinability behavior of the produced composite materials was investigated by using the drilling method with a three-axis computer numerical controlled (CNC) milling center. High-speed steel (HSS) and titanium nitride (TN)-coated HSS drill bits were used in the machinability tests. As drilling process cutting conditions three different feed rates (FRs) of 0.05, 0.10, and 0.15 mm·rev−1 and three different cutting velocities (CVs) 15, 20, and 25 m·min−1 were applied. The effects of cutting conditions such as FR, CV, reinforcement phase ratio, and cutting tool type on cutting forces such as thrust force (TF) and torque (TQ) in the drilling process were studied in detail. According to the experimental results, TF and TQ decreased with the increase in the CV and increased with the increase in the FR.

Commissioning measurements on an Elekta Unity MR-Linac

Magnetic resonance-guided radiotherapy technology is relatively new and commissioning publications, quality assurance (QA) protocols and commercial products are limited. This work provides guidance for implementation measurements that may be performed on the Elekta Unity MR-Linac (Elekta, Stockholm, Sweden). Adaptations of vendor supplied phantoms facilitated determination of gantry angle accuracy and linac isocentre, whereas in-house developed phantoms were used for end-to-end testing and anterior coil attenuation measurements. Third-party devices were used for measuring beam quality, reference dosimetry and during treatment plan commissioning; however, due to several challenges, variations on standard techniques were required. Gantry angle accuracy was within 0.1°, confirmed with pixel intensity profiles, and MV isocentre diameter was < 0.5 mm. Anterior coil attenuation was approximately 0.6%. Beam quality as determined by TPR20,10 was 0.705 ± 0.001, in agreement with treatment planning system (TPS) calculations, and gamma comparison against the TPS for a 22.0 × 22.0 cm2 field was above 95.0% (2.0%, 2.0 mm). Machine output was 1.000 ± 0.002 Gy per 100 MU, depth 5.0 cm. During treatment plan commissioning, sub-standard results indicated issues with machine behaviour. Once rectified, gamma comparisons were above 95.0% (2.0%, 2.0 mm). Centres which may not have access to specialized equipment can use in-house developed phantoms, or adapt those supplied by the vendor, to perform commissioning work and confirm operation of the MRL within published tolerances. The plan QA techniques used in this work can highlight issues with machine behaviour when appropriate gamma criteria are set.

Prediction on enhanced electrochemical discharge machining behaviors of zirconia‐silicon nitride using hybridDNNbased spotted hyena optimization

Prediction on enhanced electrochemical discharge machining behaviors of zirconia‐silicon nitride using hybrid<scp>DNN</scp>based spotted hyena optimization

Experimental Investigation on Machine-Induced Damages during the Milling Test of Graphene/Carbon Incorporated Thermoset Polymer Nanocomposites

The fiber laminate composites are extensively used in aerospace, aircraft, automotive components due to their high stiffness, corrosion, moisture resistance, low weight, and durability features. These fiber composites are modified with nanomaterials to acquire the desired manufacturing properties. The complex structure and anisotropic features differ from metals and their alloys. Additionally, the machining principles of fiber laminates significantly differ from conventional engineering materials. The present work investigates the machining behavior and permeates the damage generated while milling of graphene-modified carbon-fiber reinforced polymer nanocomposites (G/C@FRNC). The surface damages and defects caused in the milling samples have been examined through the high-resolution spectroscopy test. The influence of machining constraints such as cutting speed (N), feed rate (F), depth of cut (D), and graphene oxide weight % (GO) has been investigated to achieve the desired milling performances viz. material removal rate (MRR), cutting force (Fc), surface roughness (Ra), and delamination factor (Fd). The outcomes indicated that the cutting parameters and graphene nanomaterial prominently affects the milling responses. The addition of graphene improves the machinability of proposed nanocomposites with lesser defects generated. However, its higher addition can lead to the phenomenon of agglomeration that can reduce the machining efficiency. The damages and delamination generated in the machined sample are low at a higher cutting speed. This work suggests a new system to control the damage and defects to enhance the laminate samples’ quality and productivity.

Machining behaviour of AZ91E hybrid composite reinforced with granite and fly ash powders

In the present study, hybrid composites of AZ91E reinforced with granite powder and fly ash powder were fabricated by stir casting route. The reinforcing material was added in different weight fractions (2.5 and 5% each). The densities of the composites were measured between 1.74−1.8 g cm−3. The role of different weight percentages of reinforcements on the machining behavior was investigated. Increased microhardness was measured for the composites due to the presence of the reinforcing material. Higher cutting forces were measured for the composites containing higher fraction of reinforcements. With the increased cutting speed (420 to 715 rpm) the cutting forces were observed as decreased and with the increased depth of cut (0.2 and 0.4 mm), higher cutting forces were recorded. At higher fraction of reinforcements, discontinuous chips were observed for the composites. The results demonstrate the significant role of granite powder and the fly ash powder on enhancing the mechanical properties (up to 66% compared with the base alloy) but also on increasing the difficulty level in machining.

The influence of tool quality on the machining of additive manufactured and powder metallurgy titanium alloys.

This study was carried out to investigate the impact the quality of the drill bits has on the machining behavior of additive manufacturing (AM) and powder metallurgy (PM) titanium alloys. Therefore, commercially available drill bits which typically reflect two extremes of drill bit quality were selected. The performance of coated carbide twist drills, typically recommended for the drilling of wrought titanium alloys was compared with that of high-speed steel (HSS) drills. The average torque value, specific cutting energy (SCE), and tool wear were used to evaluate the drilling performance of AM and PM titanium alloys. The results of drilling tests revealed the application of the coated carbide drill resulted in lower torque and SCE values, less flank wear, and lower build-up-edge (BUE) compared with the uncoated HSS drill bits for AM fabricated titanium alloys. However, the carbide drill appeared to offer negligible improvement over the uncoated HSS drill when employed with the PM fabricated titanium alloy. In spite of the improvement in the drilling performance offered by the carbide drills for the AM titanium alloy, TiB intermetallic particles (part of the AM titanium microstructure) contributed to the damage of the coated carbide drill which would limit the drill lifetime.

SAC (Soft Actor Critic) 알고리즘을 이용한 무인항공기 경로 계획

Path planning is an essential element in the autonomous flight control of unmanned aerial vehicles, where it is important to quickly establish the path in uncertain environments and avoid collisions with the terrain and obstacles. In particular, research and development of fully autonomous flight is necessary in the case of unmanned aerial vehicles performing search, reconnaissance, and detection in terrain where human intervention is difficult. This paper proposes a path planning design method using machine learning. It has the advantages of fast calculation speed and high repeatability in a two-dimensional environment. Using the Soft Actor–Critic (SAC), an algorithm based on reinforcement learning, research into machine learning, observation status, behavior, and reward functions are required to generate global paths. Additionally, the learning and path generation results are analyzed by conducting a learning-based path planning simulation in an environment with dynamic obstacles.

The Damping Effect of Particle-Filled Hollow Sphere Structures and their Application in Machine Tool Components

High speed feed axes are a key for increasing the productivity of machine tools. It requires high acceleration and causes jerk, which excites the machine structure and negatively affects the process quality. One approach to reduce those machine vibrations are passive dampers such as particle-filled hollow spheres (PHS). PHSs dissipate vibration energy through relative motion and friction between particles among themselves and the sphere. Compounds of PHS as core of sandwich materials allow structure-integrated damping of machine tool components and for maintaining a high specific stiffness at the same time. The complex interactions within each sphere lead to nonlinear damping. As of today, precise predictions on how PHSs influence the overall machine behavior are not possible. This prognosis is essential for establishing the material in any machine structure. The paper investigates the damping properties of PHSs in a spindle box of a machine tool. The experimental and numeric analysis demonstrates the nonlinear behavior and shows the reaction of the spindle box under external excitation. The result shows that the damping of the spindle box with PHSs is frequency and amplitude dependent. The damping of PHSs is domain with increased parts of them deformed during vibration.

A method to measure the damping introduced by linear guides in large milling machines

Simulation of the dynamic behavior of a milling machine requires accurate stiffness, inertia, and damping values. Unlike the properties of stiffness and inertia, damping values are not generally available in the bibliography, which only contains reference values. In the present work, a method is proposed to measure the damping introduced by one linear guide when assembled in large-scale milling machines, unlike current available methods which measure the damping capacities of such guides. Linear guides of same size and type can introduce different damping values at different joints even in the same machine, so that these damping values depend both on the damping capacities of the guide and on the dynamic properties of the joint. This method will allow identifying linear guides that can introduce highest damping values. This identification has been done first by measuring frequency responses at the linear guides of the machine and calculating the modal vectors of that linear guides with finite element models. Secondly, energy dissipation that takes place in these guides has been represented by associating the damping of each linear guide in a discrete way. Next, the method has been validated on a real large machine by comparing estimated and measured frequency responses at tool center point. One immediate advantage of this method will be to improve the dynamic frequency responses of milling machines, and therefore, their productivity for the manufacturing processes in which chatter phenomena arise.

Analysis of groove quality and machining behavior of Zr-based metallic glass through laser grooving and electro-jet machining

Conventional machining of metallic glass is a challenge due to its amorphous nature and inherent brittleness. This work investigates the non-conventional machining of Zr-based metallic glass, Vitreloy-1, using laser processing with a Yb-fiber laser and an electro-jet milling (EJM) process. Grooves were fabricated using these techniques in Vitreloy disks of 1.5 mm thickness to study the machining behavior. The grooves formed with the laser were smooth, although there was observation of dross at the groove edges, which was selectively removed through the EJM process. On the other hand, the EJM process was found to produce dross-free grooves; however, it caused leaching of zirconium from the groove zone, which was understood from the elemental maps obtained using the scanning electron microscope. A comparison of the laser grooving and EJM grooving process was also carried out using Vickers micro-indentation. Indentations made close to the groove edge in laser grooved samples developed shear bands but the same were absent in the EJM grooved samples. Since shear banding tendency is an indicator of the inherent toughness of the metallic glass, the laser grooving technique is found more suitable for nonconventional machining of metallic glass.

Kinematic Analysis and Virtual Prototype Simulation of the Thrust Mechanism for Shield Machine

The hydraulic thrust system of the shield machine is used for driving forward and pose adjustment. It is of great significance to figure out the thrust mechanism and motion characteristics of the shield machine to ensure the safety of tunnel excavation. This study aims to develop a model to explore the influence of thrust cylinder advancement on the motions of the shield machine. Firstly, the study carried out mechanism analysis of the thrust mechanism for the shield machine and established a method to describe the position and attitude of the shield machine during the tunneling process by the homogeneous transformation matrix. Then, a new inverse kinematic model was proposed to quantify the relationship between the telescoping movements of cylinders and shield machine motions, and the Jacobian matrix was derived to solve the instantaneous kinematics analysis. Furthermore, a virtual prototype model was developed to simulate the kinematic behavior of the shield machine and validate the accuracy of the kinematic model. The model provides the basic constraint relations for the practical position control system and lays a strong foundation for the dynamic model and automatic trajectory tracking control of shield machines for future studies. Based on the proposed model, the displacement, velocity, and acceleration of cylinders that drive the shield machine to the target motions can be solved exactly. It can provide a reference for the pose control of the shield machine during the practical shield tunneling.

Analysis of methods and approaches of the electromagnetic calculation of induction machines regarding their use to solve multiphysical problems

PurposeFor the electromagnetic simulation of electrical machines, models with different ranges of values, levels of detail and accuracies are used. In this paper, numerical and two analytical models of an induction machine (IM) are analysed with respect to these aspects. The purpose of the paper is to use these analyses to discuss the suitability of the models for the simulation of various physical quantities of an IM.Design/methodology/approachAn exemplary IM is simulated using the two-dimensional numerical finite element method, an analytical harmonic wave model (HWM) and an extended HWM. The simulation results are analyzed among themselves in terms of their level of detail and accuracy. Furthermore, the results of operating map simulations are compared with measured operating maps of the exemplary machine, and the accuracy of the simulation approaches is discussed in the context of measurement deviations and uncertainties.FindingsThe difference in the accuracy of the machine models depends on the physical quantity of interest. Therefore, the choice of the simulation method depends on the nature of the problem and the expected range of results. For modeling global machine quantities, such as mean torque or losses, analytical methods such as the HWM s are sufficient in many applications because the simulation results are within the range of measurement accuracy of current measurement systems. Analytical methods are also suitable for local flux density curves under certain conditions. However, for the simulation of the influence of local physical effects on the machine behavior and of temporally highly resolved quantities in saturated operating points, the accuracy of the analytical models decreases and the use of the finite element method becomes necessary.Originality/valueIn this paper, an extension of the HWM is used to calculate the IM, which, in contrast to the HWM, models the saturation. Furthermore, the simulation results of the different electromagnetic IM models are put into the context of the uncertainty of a measurement of several identical IMs.

An Exact Solution to the Modified Winding Function for Eccentric Permanent Magnet Synchronous Machines

The Winding Function Approach has been used since 1965 to describe the inductance behavior of small air-gap electrical machines, and several works have contributed to its formulation in the presence of mechanical faults, such as eccentricity, leading to the Modified Winding Function Approach (MWFA). In order to use the MWFA, an integral over a full rotation period needs to be computed. Nevertheless, this typically requires the performance of numerical integration, and thus it is affected by integration error, requires relatively high computational effort and, at the same time, it does not easily allow for performance of the analysis of the inductance harmonics. In this work, an exact analytical solution to the MWFA equation is provided in a form that allows to highlight the harmonic content of the inductances. After a thorough mathematical derivation of the solution, a numerical investigation is proposed for verification purposes.

Investigation on machinability in turning of as-cast and T6 heat-treated Al-(3, 7, 12%)Si-0.6%Mg alloys

The machinability in turning of Al-Si-Mg alloys under as-cast and heat-treated conditions has been investigated. Three alloys with 3%, 7% and 12%Si and 0.6%Mg contents (wt%) were prepared. Unsteady solidified ingots were obtained in a vertical upward directional solidification apparatus using an instrumented cylindrical water-cooled mold. Samples extracted from the ingots were characterized by scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) examinations and by Brinell hardness tests, before and after T6 heat treatments (540 °C solutioning temperature for 10 h, water quenching at 25 °C and artificial aging at 155 °C for 5 h). Specimens in both the as-cast and heat-treated conditions were subjected to machinability tests as a function of cutting force in face turning operation using a CNC lathe machine, fixing parameters as cutting depth, feed rate, cutting speed, and cutting tool. The as-cast microstructure consists of a dendritic α-Al rich phase and an interdendritic eutectic microconstituent (α-Al + Si particles). As the alloy Si content increased, the solidification cooling rate increased, the amount and size of α-Al dendrites decreased while the amount of eutectic mixture increased. After heat treatment, Si particles were found to be more rounded and an increase in fraction of Mg2Si was observed. The hardness profile declines along the length of the as-cast ingots, however the values improved with both alloy Si content and heat treatment. The as-cast alloys showed maximum cutting force at the beginning of the process, decreasing during machining progress, whereas in the heat-treated condition the cutting forces showed values almost constant. The results suggest a more stable machinability behavior during turning of the heat-treated alloys as a consequence of a more homogenous microstructure and hardness.

AI: Coming of age?

AbstractAI has had many summers and winters. Proponents have overpromised, and there has been hype and disappointment. In recent years, however, we have watched with awe, surprise, and hope at the successes: Better than human capabilities of image-recognition; winning at Go; useful chatbots that seem to understand your needs; recommendation algorithms harvesting the wisdom of crowds. And with this success comes the spectre of danger. Machine behaviours that embed the worst of human prejudice and biases; techniques trying to exploit human weaknesses to skew elections or prompt self-harming behaviours. Are we seeing a perfect storm of social media, sensor technologies, new algorithms and edge computing? With this backdrop: is AI coming of age?

Experimental investigation on machining behavior in dry turning of nickel based super alloy-Inconel 600 and analysis of surface integrity and tool wear in dry machining

Recently, most companies are striving to reduce the cost incurred in production to enhance productivity. The machining behaviour is analyzed by considering various parameter. In general, nickel based super alloy are termed as hard materials which result in more tool failures. Inconel 600, nickel alloy, is machined using dry cutting conditions using gear lathe with cubic boron nitride (CBN) tool. The statistical technique, analysis of variance (ANOVA) was adopted to establish the correlation between the machining parameter and response parameter using CBN inserts. Linear regression equation for surface roughness (SR) were used to predict the responses. ANOVA result for SR concluded that cutting speed has 95% contribution followed by feed rate (4%) and depth of cut (1%). ANOVA result for tool wear (TR) concluded that cutting speed has 80% contribution followed by feed rate (18%) and depth of cut (2%). R- square predicted value for SR and TR are 81.3% and 89.11% respectively.

New machine behavior’s evolutionary approaches between AI learning, control and ethics promoting cooperative Human-Machine Intelligence

The technological revolution in the fields of robotics and artificial intelligence seems to indicate a future shift in our human-centered social paradigm towards a greater inclusion of artificial cognitive agents in our everyday environments. Understanding AI agents goes beyond the interpretation of a specific algorithm and requires analyzing the interactions between agents and with their surroundings. Combining AI and behavioral science is then seen in its true potential, as an ethical way to improve people's lives, where end users can feel safe when sharing personal data for transparent and relevant services.

Coupled Magnetic Field and Thermal Analysis Model for an IPMSM With Modular Three-Phase Winding Topologies for Fault-Tolerant Applications

Multi three-phase machines are frequently recommended for high current and high power applications due to their ability to minimize phase current while maintaining rated power and phase voltage. Furthermore, multi three-phase machines are also proposed because of their fault-tolerant capability to operate in partial working conditions due to their redundant structure. A partial working condition may occur when one or more three-phase winding sets go into faulty condition. This article focuses on evaluating the thermal behavior and efficiency of a multi three-phase machine comprising different modular winding topologies to investigate its normal, partial, and partially overloaded operation. The machine prototype used in the analysis is an interior permanent magnet synchronous machine (IPMSM) having six three-phase winding sets configured in modular three-phase winding arrangements. Firstly, the prototype machine’s losses, efficiency, and output torque performances are evaluated through electromagnetic finite element analysis (FEA) for the different modular three-phase winding topologies applying similar operating conditions. Then the machine’s thermal behavior is evaluated for the modular (concentrated, distributed, and combined concentrated and distributed) three-phase winding topologies through a coupled magnetic field and thermal analyses under the machine’s healthy, partial, and partially overload operations. Finally, a comparative thermal analysis is presented for the machine prototype along with experimental validations for the analyzed modular three-phase windings topologies. This research study suggests the best modular three-phase winding topology for a multi three-phase machine considering efficiency performance and mutual heat exchange phenomenon between different three-phase independent winding sets, particularly for the machine’s partial and partially over-load working conditions.