Behavior Of Machine Research Articles

Cloud-based thermal error compensation with a federated learning approach

Thermal error compensation is one of the most research-oriented topics in manufacturing with rising importance in the industry. This paper presents an innovative Industry 4.0 application of thermal error compensation for precision engineering. A federated learning-based thermal error compensation approach running in the cloud is applied to two machine tools, one located at ETH Zürich, and another one at TU Wien. Although environmental conditions and thermal error behaviour of both machines differ, the implemented knowledge transfer across machines is a viable compensation strategy, albeit with limited precision. A detailed comparison of the two machines of the same type under the same load conditions shows foreseeable similarities in behaviour, but also clear differences due to the different configurations and lifetime status. The cloud-based compensation reduced the crucial thermal errors in the best case of both machine tools by more than 80% under critical conditions.

Neuroscience and Network Dynamics Toward Brain-Inspired Intelligence.

This article surveys the interdisciplinary research of neuroscience, network science, and dynamic systems, with emphasis on the emergence of brain-inspired intelligence. To replicate brain intelligence, a practical way is to reconstruct cortical networks with dynamic activities that nourish the brain functions, instead of using only artificial computing networks. The survey provides a complex network and spatiotemporal dynamics (abbr. network dynamics) perspective for understanding the brain and cortical networks and, furthermore, develops integrated approaches of neuroscience and network dynamics toward building brain-inspired intelligence with learning and resilience functions. Presented are fundamental concepts and principles of complex networks, neuroscience, and hybrid dynamic systems, as well as relevant studies about the brain and intelligence. Other promising research directions, such as brain science, data science, quantum information science, and machine behavior are also briefly discussed toward future applications.

Machining of high temperature heat resistant super alloys- a concise review on cooling aspects

Analyzing and comprehending cutting process mechanisms is a crucial step in creating a cost-effective, long-lasting, and safe machining process.In modern manufacturing, it is very challenging to achieve a high surface finish product with high dimensional accuracy. To reduce the high production cost as well as for the sustainable manufacturing selection of both cutting tool materials and cutting environments is necessary. Nowadays high-temperature alloys are in very demand in industries like power generation, gas turbines, and chemical processing. Superalloys are recognised as a significant problem in a high-temperature work environment with the sophisticated material technology in space and aviation industries. At the time of machining of these superalloys, a high amount of heat developed at the cutting area which affects the microstructure of the work specimen and also the cutting inserts. To minimize that excess heat, researchers and manufacturing industries are adopting different cooling lubrication techniques. When the lubricant penetrated the cutting region, the temperature is reduced since cooling effect. Several studies focus on the optimization of individual performance features in the machining processes and in recent past, Super-alloys and cutting materials like ceramic, carbide, and hybrid tools are gaining popularity. Since the application of the superalloy in various sectors is ever- increasing, therefore it is necessary to evaluate a machining behavior during the experimental investigation. In this contemporary review, the effects of various cooling and lubrication strategy on machining outputs will be discussed considering the sustainable and greenway of manufacturing.

Investigation on the machinability of TiN nano particulate reinforced magnesium matrix composite

In the present work, the machinability of magnesium matrix nanocomposite was investigated. The nanocomposite consists of pure Mg as matrix and TiN Nano particulate as reinforcement. The composite was fabricated through powder metallurgy process for three different compositions such as 1.5, 2.5 and 5% by weight of TiN Nano particulates. Machinability behavior of the nanocomposite was studied through milling process with process parameters, feed rate of 5, 10 and 15 mm/min, depth of cut of 0.15, 0.3 and 0.45 mm and spindle speed of end mill remain constant of about 2000 rpm. The performance measures considered in this study are cutting forces, material removal rate, surface roughness and tool tip temperature. The milling process was carried out at room temperature for normal atmospheric conditions. Poly crystalline diamond (PCD) coated solid carbide flat type end mill was used in the study. L27 orthogonal array was used to conduct the experiments. The results from the study revealed the fact that the performance measures like cutting force, tool tip temperature and surface roughness are significantly influenced by TiN Nano particulate in the composite, whereas the material removal rate is greatly influenced by the machining parameter feed rate. High hardness, heat resistance and excellent wear resistance of TiN Nano particulate resulted in the influence of the performance measures. Main effect plots and interaction plots were generated for the performance measures which was further followed by ANOVA and second order polynomial regression equation to test the level of significance with least error.

Magnetic field effects on electrochemical dissolution behavior and surface quality of electrochemical machining of Ti-48Al-2Cr-2Nb alloy

Magnetic field effects on electrochemical dissolution behavior and surface quality of electrochemical machining of Ti-48Al-2Cr-2Nb alloy

Designing lawful machine behaviour: Roboticists’ legal concerns

Regulatory requirements weighing on roboticists are becoming heavier, and at the same time, the activity of producing robots is theorized as creating new types of legal risks. Roboticists become responsible not only for compliance to a set of regulatory objectives, but they also become responsible for giving machines an ability to make decisions in uncertain environments. All of this gives roboticists’ legal literacy a newfound importance, and reveals the lack of data on that population from a socio-legal angle. While we have some knowledge of lawyers’ and policy makers’ concerns for robots, we do not know how roboticists understand their relationship to law and regulation, or the legal value they attribute to various engineering processes. This article offers a preliminary exploration of that population and of their legal concerns, through interviews of ten engineers from Danish robotics companies. The analysis shows that they perceive legal concerns as dependant and integrated into their concerns for safety, which are themselves inferior to functionality and economy concerns. The article further highlights differences in understanding and perception of various legal matters by our informants, and from our practitioner perspective. Hopefully, highlighting these differences will by itself help close the gap between the two professions.

Interactive Effects of Problem-Gambling Severity, Gender and Alcohol Consumption on Electronic Gaming Machine Behaviour

While comorbidity of problematic alcohol and gambling use is well established, much less is known about the way in which alcohol consumption while gambling interacts with problem-gambling severity and other individual differences. We hypothesised three factors that would interact with alcohol consumption while gambling on electronic gaming machines (EGMs) to influence four behavioural gambling measures: preferred number of lines bet, average duration of play, average spend per session and preferred electronic gaming machine denomination. The latter is a measure of gambler’s preference for the monetary denomination in which EGM bets are placed (e.g. 1 cent, 2 cents, 5 cents, 10 cents, 20 cents, $1), with higher denomination EGMs being higher risk since bets can be placed in larger amounts and money can be lost more rapidly. The three hypothesised interacting factors were problem-gambling severity, presence/absence of alcohol use disorder and biological gender. A total of 1557 male and female participants completed a questionnaire, measuring their problem-gambling status, problem alcohol status, consumption of alcohol at the gambling venue, preferred EGM denomination, preferred number of lines bet, average duration of play and average spend per session. We found the anticipated gender-differential spending effect with males spending more than females, but we also found a surprising reverse differential spending effect for problem gamblers such that females spent more than males. We also found that alcohol consumption while gambling was generally associated with a preference for higher denomination machines and that those players without alcohol problems who drank at the venue preferred to bet on more lines, suggesting a double-max strategy amongst gamblers who drank at the venue. Finally, for non-problem and low-risk gamblers, concurrent alcohol consumption was related to preference for higher denomination EGMs in female players, but not for male players. These findings are discussed in the context of the physiological and psychological effects of alcohol.

Electrolytic-dielectrics: A route to zero recast electrical discharge machining

Electrical discharge machining (EDM) is a widely used manufacturing process for machining hard or high melting point metals. A characteristic feature of this process is a brittle, porous and rough recast layer on machined surfaces, which undermines integrity and limits its applications. Previous attempts to remove the recast have increased process steps and complexity, and in the case of EDM ECM hybrid processes have failed to understand or explain process mechanisms and have not proposed methods to control removal mechanisms to produce tailored surfaces. Here, we introduce tailored electrolytic-dielectrics that eliminate the defective recast layer, while maintaining machining rate. By adding selected electrolytes to a conventional deionised water dielectric in a standard EDM machine, material removal mechanisms can be altered and controlled in a simultaneous electrical discharge and electrochemical process, producing discrete surface morphologies through passive oxidation, aggressive pitting, and electro-polishing. These bespoke dielectrics alter fundamental machining behaviour to alternate between conventional EDM discharging and electrochemical dissolution. For the first time, it is shown that machining rate can be maintained while reducing, and eliminating, the defective EDM recast layer, which would otherwise need removal, in a single step process that combines the accuracy of EDM with the surface finish of ECM with the potential to produce high integrity surfaces with high throughput. The mechanisms behind this unique machining process are described through fundamental waveform and discharge analysis, which revealed discrete pulse types and their significance to the process, the importance of pulse ratio balance, the time-varying nature of the process, and the significance of high-voltage regions to electrochemical removal. Key process parameters are determined, such as EDM: ECM pulse ratio balance, electrolytic-dielectric conductivity, salt type, machining/exposure time, and electrode/servo advance, which are crucial to producing tailored surfaces. A model is devised to describe the overall balance between discharge based and dissolution based removal. Through this model, the point during machining at which complete recast layer removal occurs is predicted and validated through experimental analysis. This adapted EDM process has significant potential to be used for producing recast-free features by using an easily modified dielectric.

Numerical modeling and simulation of machining of 3D printed CFRP composite

Carbon Fiber Reinforced Polymer (CFRP) composites are gaining popularity in recent years for their high specific strength and superior performance under extreme conditions. Additive manufacturing (AM) or 3D printing of CFRP composites has added a new dimension to the existing research of CFRP composites. However, one of the caveats of 3D printed CFRP composites is that the dimensional accuracy and the surface finish achieved fail to meet the standard tolerance requirement. To achieve the desired accuracy further post-process machining is required. However, machining an anisotropic material such as 3D printed CFRP composites impose challenges. This study aims at investigating the machining behavior and post-processing capability of 3D printed CFRP using numerical modeling and simulation using ABAQUS/Explicit, a commercially available powerful finite element analysis (FEA) software package. Influence of machining parameters, such as feed and depth of cut (DOC) and 3D printing parameter, such as percentage of overlap between adjacent passes have been studied. The post-processing capability or machining behavior of 3D printed CFRP has been evaluated by dependent parameters, such as, cutting forces, strain, chip and burr formation, and the resultant surface topology. With the use of proper damage parameters, such as, ductile and shear damage and Johnson-Cook criterion for plasticity, a 3D model was developed in the FEA. Eight layers were stacked with the orientation of 45°-135°-45°-135°. The layers were joined using cohesive properties. Damage in the cohesive bonds was also defined using the quadratic damage criterion to model delamination. To capture the changes in elemental level, linear tetrahedral elements C3D4T, were used. A reference point on the bottom layer was used to capture the history of cutting forces. The cutting and thrust forces increased with the increase of DOC and feed. The rigidity, shape of the flutes and print direction influenced chip formation. Finally, the proposed model was used to observe the quality of surface finish.

The effect of interstitial fluid on the machining behaviour of cortical bone

Bone machining research is usually conducted ex-vivo with standard laboratory equipment, implying mostly that the cutting process takes place in dry state. While these studies are useful for understanding the bone cutting process, they cannot represent the real clinical cutting condition due to the disregard of internal irrigation (i.e., interstitial fluid and blood within the tissue’s vascular porosities). As bone possesses ca. 20 % water, internal irrigation can influence the bone’s properties (e.g., shear strength, friction coefficient) and alter the cutting mechanism and surface deformation (e.g., crack formation, smearing). Hence, to study the ex-vivo bone cutting process in an internally irrigated state, a novel machining and pumping setup is proposed here, which enables a scenario closer to a surgical condition than the traditional dry machining method. Cutting tests demonstrated that portions of bone near the fluid-filled porosities possess shear strength and friction coefficient gradients due to the bone’s permeability. This resulted in machining forces and necrosis up to 52 % and 55 % lower than in dry bone, respectively. A cutting forces model was developed considering the internal irrigation condition and the randomness and anisotropy of the tissue. Moreover, it was found that internal irrigation can change the chip formation mechanism and induce minimised surface morphological damage due to the minimised friction between the tool and the cutting surface in near-porosity sites. This research highlights the importance of conducting bone machining research with the consideration of internal irrigation, an imperative aspect to more realistically mimic surgical scenarios in a laboratory environment.

Development of a Multi-Station Creep Machine for Adhesive Joint Testing

Abstract Adhesive joints have unique advantages when compared to conventional mechanical joints. Adhesives can undergo creep deformation at room temperature (cold flow) as well as at low stress (well below the yield point of the material), which can lead to considerable reduction in the life expectancy of the bonded structures. Therefore, performing creep tests to determine a material’s expected behavior under certain operational or environmental conditions is of crucial importance. Available commercial creep machines are often designed to test a wide variety of materials and, thus, present suboptimal features for testing specimens with specific characteristics, as is the case of adhesive joints. In this article, a new multi-station creep test machine is proposed and its main subsystems are described, namely the mechanical structure, the pneumatic servo-controlled actuation, the data acquisition, and the command software. The machine is able to run tests at a constant load that can be set from 100 up to 2,800 N, at intervals of 5 N, and a maximum displacement of 250 mm. The three stations can accommodate single lap joints or bulk specimens and allow for totally independent and simultaneous tests, at temperatures ranging from −100°C up to 200°C. The measurement resolution for load and displacement is 0.025 N and 0.025 mm, respectively. Experimental results of creep tests are presented, and the multi-station creep machine behavior is validated by comparison to a reference equipment. The creep machine reveals good performance, with force and displacement repeatability below close to 6 N and 0.25 mm, respectively.

Effects of Addition of Glass Fibers and SiC Particles on the Mechanical and Machinability Behaviours of Areca Fine Fiber-Reinforced Phenol Formaldehyde Composite

In the present experimental study the effects of addition of Glass Fibers (GFs) and Silicon Carbide (SiC) particles on the mechanical and machinability behaviors of Areca Fine Fiber (AFF)-reinforced Phenol Formaldehyde (PF) composites were evaluated in three stages. Composites were prepared by hand lay-up technique at room temperature. From the first stage, it is observed that the 20AFF/20GF/PF hybrid composites give better mechanical properties than the other hybrid composites followed by the 10AFF/30GF/PF hybrid composite. The results of second stage revealed that the AFF/GF/SiC/PF hybrid composites exhibited the highest values of mechanical properties after addition of the 6% of SiC particles. From third stage, it is observed that the cutting speed is most significant process parameter during drilling of the 20AFF/20GF/6SiC/PF hybrid composite, followed by feed rate.

Dynamics and control of vibratory finishing machine with translational motion of lapping-polishing plates

The lapping and polishing operations are of the most important ones considering the finishing treatment of machine parts. These operations can be performed by numerous methods, among which the vibration-driven ones are of the most widespread. The present paper is focused on studying the dynamic behavior of the vibratory finishing machine providing the single-sided lapping and polishing of flat surfaces of cylindrical and prismatic parts. The major scientific novelty of this research consists in an improved control technique of generating the translational oscillations of the lapping (polishing) plates by means of implementing the double-magnet excitation system. In order to investigate the machine’s double-mass vibratory system dynamics, the corresponding mathematical model is developed using the Lagrange-d’Alembert principle. The numerical modeling is carried out with the help of the Mathematica software and presents the time dependencies of the lapping (polishing) plates kinematic parameters. The simplified experimental prototype of the vibratory lapping machine is developed and tested under different operational conditions. The proposed design ideas and obtained theoretical and experimental results can be effectively used by the designers of lapping and polishing equipment, as well as by the technologists implementing new techniques of finishing treatment.

An Automated Machine Learning Approach for Real-Time Fault Detection and Diagnosis.

This work presents a novel Automated Machine Learning (AutoML) approach for Real-Time Fault Detection and Diagnosis (RT-FDD). The approach’s particular characteristics are: it uses only data that are commonly available in industrial automation systems; it automates all ML processes without human intervention; a non-ML expert can deploy it; and it considers the behavior of cyclic sequential machines, combining discrete timed events and continuous variables as features. The capacity for fault detection is analyzed in two case studies, using data from a 3D machine simulation system with faulty and non-faulty conditions. The enhancement of the RT-FDD performance when the proposed approach is applied is proved with the Feature Importance, Confusion Matrix, and F1 Score analysis, reaching mean values of 85% and 100% in each case study. Finally, considering that faults are rare events, the sensitivity of the models to the number of faulty samples is analyzed.

Synchronizing a synchronverter to an unbalanced power grid using sequence component decomposition

Abstract The synchronverter is a device used in some microgrids to perform self-synchronization and represent the behavior of a synchronous machine. However, the original control has been proposed for balanced networks, which is not present in all distribution systems. In unbalanced networks, the negative sequence may appear and generate a double frequency oscillation when delivering power or a non-symmetrical current from the inverter; thus, it must compensate unbalanced load. Therefore, this article shows that a synchronverter can be synchronized using the positive sequence even when there are voltage unbalances. The proposed strategy was simulated in the Simulink-Matlab© software, considering an unbalanced power grid with a single inverter and a load. The results confirm the effectiveness of this strategy, as the synchronverter can follow the grid frequency and the wave shape amplitude after starting the frequency droop control.

A Cognitive Routing Framework for Reliable Communication in IoT for Industry 5.0

Industry 5.0 requires intelligent self-organi- zed, self-managed, and self-monitoring applications with ability to analyze and predict the human as well as machine behaviors across interconnected devices. Tackling dynamic network behavior is a unique challenge for Internet of Things applications in Industry 5.0. Knowledge-defined networks (KDN) bridge this gap by extending software-defined networking architecture with knowledge plane, which learns the network dynamics to avoid suboptimal decisions. Cognitive routing leverages the sixth-generation (6G) self-organized networks with self-learning feature. This article presents a self-organized cognitive routing framework for a KDN which uses link-reliability as a routing metric. It reduces end-to-end latency by choosing the most reliable path with minimal probability of route-flapping. The proposed framework precalculates all possible paths between every pair of nodes and ensures self-healing with a constant-time convergence. An experimental test-bed has been developed to benchmark the proposed framework against the industry-stranded link-state and distance-vector routing algorithms SPF and DUAL, respectively.

Identifying Centrifugal Pump Effectiveness Through Utilizing OEE Measures as a Basis Towards Optimum Process Stability

The present global competitive within the petroleum industry obliges companies to improve production performance continually. In this paper, Overall Equipment Effectiveness (OEE) used as improvement driver tools that measure various types of production losses and indicate the area of process improvement. The study approach attempts to measure the effectiveness of the centrifugal oil pump during one year of operating based on the historical data acquired. Then used this gained data of the OEE metrics in order to predict the pump effectiveness over the three years. Monte Carlo simulation method used to prognosis the machine behavior patterns in the future and estimating the effectiveness of the pump system. Also, it supports management for clear understanding to draw their maintenance strategy in advance and identifies the opportunities to reduce wastages of time and resources. Further, the results show how individual OEE factors influence the overall productivity and efficiency of the oil pump. This identification will contribute not just to improve the maintenance plan but also will protect the equipment from early deterioration and achieve process stability. OEE is a globally recognized best practice measure to systematically improve processes for higher efficiencies and better productivity, ultimately leading to lower manufacturing costs and higher profitability.

Analysing the Effects of High-Intensive Dry Mixing on the Calendering Process and Cell Performance of NMC622 Based Cathodes

A reliable design of production processes for the manufacturing of lithium-ion battery electrodes requires a deep understanding of the interdependency of processes, the resulting electrode microstructure and the influence on the cell performance indicators, like energy density, cycle life and aging. In the present study, the focus lays on the calendering process during which the electrode coating is compacted with the aim of adjusting uniform electrode properties such as mechanical, electrical and electrochemical behavior. Compaction of the electrode coating affects the pore structure and therefore has a crucial influence on the electrical and electrochemical behavior of the cell. Consequently, process and machine parameters have to be adapted in order to generate electrode structures optimized for a desired application. To meet this target, an in-depth understanding of how the calendering process affects the electrode structure beyond the simple reduction of porosity and further how the calendering process itself is affected by the preceding process steps like dry or wet mixing is mandatory.Thus, the focus of the presented work is to investigate the interdependency between the dry mixing process step and the subsequent calendering process by correlating powder properties adjusted via the dry mixing with the machine behavior during the calendering as well as the resulting coating density. The impact of the calendering process on the electrode microstructure and its correlation with electrode properties by developing process-product-property functions, regarding the above mentioned criteria, is an additional focus of the presented study.Therefore, powder mixtures of NMC622 with carbon black were created under varying the dry mixing intensity and thus adjusting the carbon black agglomerate size. The created powder mixtures were comprehensively characterized, e.g. particle size distribution and powder conductivity, and then used to build up electrodes which afterwards were compacted to different coating densities. The correlation between the powder properties and the calendering behavior shows a higher compaction resistance with decreasing carbon black agglomerate size. Whereas reducing the carbon black agglomerate size leads to lower electrical resistivity and therefore strongly impacts the C-rate capability.

Power-Electronics-Based Mission Profile Emulation and Test for Electric Machine Drive System—Concepts, Features, and Challenges

In the last decade, significant progress has been made in electrification, especially in the applications of electrical vehicles, renewable energies, and industry automations, which imposed much more complicated working conditions to electric machines as well as the drive converters. More advanced features, such as the control strategies, functionality, stability, and reliability of machine drive systems, need to be characterized and validated. Thus, there is an emerging need to accurately recreate the behaviors of electric machine drive systems from more aspects for comprehensive tests. This article aims to foster and investigate the mission profile emulation technologies for the testing of electric machine drive systems. The key factors of the system to be emulated are first clarified, and then different testing concepts are summarized and compared, including dynamometer test, controller hardware-in-the-loop simulation, power hardware-in-the-loop simulation, and power-electronics-based emulation. The features of power-electronics-based emulation, which is considered as a promising trend, will be further discussed with respect to the degrees of coupling with the drive converter, electric machine models, and control structures. Finally, challenges in the field of mission profile emulation for electric machine drive systems are discussed.

High Speed UART Implementation Using VHDL

Abstract: The Universal Asynchronous Receiver and Transmitter (UART) could be a custom designed circuit that allows serial communication between a laptop and a computer peripheral. The complex nature of combined circuit generation has made machine design time consuming at the gate and switch flop levels. As a results of this reality, the style designer made the choice to use hardware description language during the virtual machine layout process. VHDL could be a hardware description language that's accustomed model digital systems. It contains information that you just may find useful. It includes information which will be accustomed explain the virtual machine's behaviour shape, also because the ability to explicitly specify its timing. VHDL could be a difficult and verbose language with many complicated assembles that have complicated semantic meanings and is difficult to grasp initially. The language facilitates hierarchical machine modelling likewise as top don methodologies. It provides an easier method for checking the UART and assisting within the discovery of any discrepancies. It also allows for a more behavioural explanation of the module's characteristics. It makes the look implementation easier to read and understand, and it also provides the flexibility to simply describe dependencies among numerous procedures that arise in complex eventdriven systems. Thus, the layout employs VHDL as a layout language to reap the transmitter module. First, the running version of the transmitter is defined. Then, using VHDL, all of the transmitter's blocks are designed and defined.