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In most European member states, employees stay with a company for over ten years. During this time, people gain valuable experience and build up expertise that is lost to production companies when employees leave. Despite increasing digitalisation, there will still be processes, especially in individual production, that require experts. Ontologies are an established method for formalising knowledge. Standards are needed to ensure interoperability. However, not all reference models are based on the standardised basic formal ontology. To the best of our knowledge, there are also no references for modelling human-bound production steps. We have developed the freely accessible ROXANA ontology based on actual use cases from special-purpose machines. This ontology is based on the basic formal ontology and uses references from the common core ontologies and the industrial ontology foundry. The difficulty with expert-bound process steps in production is individuality and complexity. The design of special-purpose machines is individual, as are the machine-specific documents and the associated workflows. This paper presents the ontology, explains it using practical examples, and shows its implementation in a real software-based expert system. [ABSTRACT FROM AUTHOR]

The design of metallic glasses (MGs) with good properties is one of the long-standing bottlenecks in materials science and engineering, which has been relying mostly on far less efficient traditional trial-and-error methods. Even the currently popular machine learning-based forward designs, which use manual input to navigate high dimensional compositional space, often become inefficient with the increasing compositional complexity in MGs. Here, we developed an inverse design machine learning model, leveraging the variational autoencoder (VAE), to directly generate the MGs with good glass-forming ability (GFA). We demonstrate that our VAE with the property prediction model is not only an expressive generative model but also able to do accurate property prediction. Our model allows us to automatically generate novel MG compositions by performing simple operations in the latent space. After randomly generating 3000MG compositions using the model, a detailed analysis of four typical metallic alloys shows that unreported MG compositions with better glass-forming ability can be predicted. Moreover, our model facilitates the use of powerful optimization algorithms to efficiently guide the search for MGs with good GFA in the latent space. We believe that this is an efficient way to discover MGs with excellent properties. [ABSTRACT FROM AUTHOR]

We consider the context of machining systems design where both equipment selection and line balancing decisions have to be taken in order to minimise the total cost of the system. The designed flow line employs multi-positional machines with rotary tables where vertical and horizontal machining modules can be used for the realisation of machining processes. For this challenging optimisation problem in production research, we develop an innovative mathematical model based on a mixed-integer linear programme and a heuristic algorithm for an approximate solution. An extensive numerical experiment is conducted in order to evaluate the performances of the proposed mathematical model and the developed heuristic. The obtained results show that the decision makers can use the elaborated methods for solving efficiently even large-scale industrial problems. [ABSTRACT FROM AUTHOR]

Development of nanophotonics has made it possible to control the wavelength and direction of thermal radiation emission, but it is still limited by Kirchhoff's law. Magneto-optical materials or Weyl semimetals have been used in recent studies to break the time-reversal symmetry, resulting in a violation of Kirchhoff's law. Currently, most of the work relies on the traditional optical design basis and can only realize the nonreciprocal thermal radiation at a specific angle or wavelength. In this work, on the basis of material informatics, a design framework of a multilayer nonreciprocal thermal absorber with high absorptivity and low emissivity at any arbitrary wavelength and angle is proposed. Through a comprehensive investigation of the underlying mechanism, it has been discovered that the nonreciprocal thermal radiation effect is primarily attributed to excitation of the cavity mode at the interface between the metal and the multilayer structure. Moreover, the impact of factors, such as layer count, incidence angle, extinction coefficient, and applied magnetic field on nonreciprocal thermal radiation, is thoroughly explored, offering valuable insights to instruct the design process. Additionally, by expanding the optimization objective, it becomes feasible to design fixed dual-band or even multi-band nonreciprocal thermal absorbers. Consequently, this study offers essential guidelines for advancing the control of nonreciprocal thermal radiation. [ABSTRACT FROM AUTHOR]

The Horizon 2020 (H2020) Future Emerging Technologies (FET) OPEN Project E.T.PACK is dedicated to advancing Electrodynamic Tether (EDT) technology by developing a specialized Deorbit Device prototype for end-of-life satellite deorbiting. In collaboration with the E.T.PACK consortium, the University of Padova conducted test campaigns aimed at evaluating the Deployment Mechanism design. This paper offers an overview of these tests, with a specific emphasis on the outcomes derived from tape spool examinations and deployment tests conducted on specific tape lengths. Furthermore, the paper delineates the setup for upcoming end-to-end deployment tests, highlighting the integration of a tape collecting machine to minimize manual intervention. The three-coil spool successfully passed qualification tests under thermal-vacuum conditions, exhibiting no instances of cold-welding. Additionally, shaker tests validated the spool ability to withstand launch conditions without requiring additional containment flanges. Furthermore, the Deployment Mechanism demonstrated its proficiency in smoothly deploying tapes with varying characteristics within the desired velocity range. Moreover, the deployment process, following a specific profile, proceeded seamlessly without any complications. Consistent continuity was maintained throughout the deployment processes, with no instances of jams or disruptions observed. These testing outcomes represent a fundamental step in the preparation and testing of the Engineering Qualification Model of the Deployment Mechanism, instilling confidence that subsequent end-to-end deployment tests will progress smoothly. To this end, a specific upside-down configuration will be implemented, and a recollecting machine was designed and manufactured to facilitate tape gathering, ensuring a streamlined and efficient testing process. A description of the end-to-end deployment test setup, including the recollecting machine, is also provided in this paper. • Development of the E.T.PACK Deorbit Device based on electrodynamic tether technology. • The E.T.PACK Device is designed for end-of-life satellite deorbiting. • Test campaigns to evaluate the tape spool and the deployment mechanism design. • The spool passed thermal-vacuum tests and endured shaker tests for launch conditions. • The deployment mechanism showed smooth, uninterrupted deployment at target velocities. [ABSTRACT FROM AUTHOR]

This paper highlights the most significant enhancements made to PaRSEC, a scalable task-based runtime system designed for hybrid machines, during the Exascale Computing Project (ECP). The enhancements focus on expanding the capabilities of PaRSEC to address the evolving landscape of parallel computing. Notable achievements include the integration of support for three major types of accelerators (NVIDIA, AMD, and Intel GPUs), the refinement and increased flexibility of the communication subsystem, and the introduction of new programming interfaces tailored for irregular applications. Additionally, the project resulted in the development of powerful debugging and performance analysis tools aimed at assisting users in understanding and optimizing their applications. We present a comprehensive demonstration of these advancements through a series of benchmarks and applications within ECP and beyond, thereby showcasing the enhanced capabilities of PaRSEC across the diverse architectures within the ECP, providing valuable insights into the runtime system's adaptability and performance across varied computing environments. [ABSTRACT FROM AUTHOR]

This study aims to observe and simulate the internal movement of fungal material substrate during the piercing and laying of black fungal sticks using the discrete element method (DEM). The contact parameters of fungi were calibrated on the different sizes within the cultivation sticks. Key parameters, such as particle stiffness, friction coefficients, and damping factors, were adjusted to replicate the interactions among fungal particles. DEM simulations were used to accurately reflect realworld mechanical behavior. Both physical experiments and DEM simulations were conducted on piercing after calibration. The physical experiments were conducted to measure the key substrate parameters, particularly for the influences of repose angle on the substrate settles. The DEM simulations were fine-tuned to closely match the real-life scenarios after measurements. In simulations, virtual tools were inserted into the modeled fungal sticks, in order to observe substrate behavior under controlled conditions. The comparison was performed on the depth and diameter of the holes created during piercing, in order to validate the accuracy of the DEM model. The simulation results were compared with experimental data obtained from a fully automatic piercing machine. The relative errors between the simulation and experimental data were 3.6% for the hole depth and 4.5% for the hole diameter. The low error margins confirmed that the high accuracy of the model was achieved to replicate the real-world conditions, providing for the reliability of the DEM model in the subsequent simulations. In addition to the piercing simulations, a systematic investigation was also made to explore the impact of landing shock on the deformation of fruiting holes within the fungal sticks. The falling behavior of fungal sticks was simulated in a semi-automatic laying machine. Displacement velocities of substrate particles around the ear holes were measured at three positions along the fungal stick: the top, middle, and bottom. The velocities were recorded as 441, 621, and 1 115 mm/s, respectively. There was the most significant deformation at the bottom of the stick and then decreased towards the top. The diameter and depth of the bottom ear holes were 12.3% and 14.3% smaller, respectively, compared with the top ones. The minimum aperture diameter and depth were 3.2 and 32.5 mm after simulation, respectively, fully meeting the requirements for ear production. Therefore, the fungal sticks remained suitable for agricultural use, even after deformation under landing shock. The semi-automatic laying machine was effective with the acceptable deformation for practical agricultural production. In conclusion, the DEM model was validated to accurately simulate the piercing and laying in the internal movement of fungal material within black fungal sticks. The insights were gained on the deformation caused by landing shock. The findings can greatly contribute to the design and operation of machinery in mushroom cultivation. The quality and functionality of fungal sticks were maintained throughout the production. The DEM model can be expected to improve agricultural practices in mushroom cultivation. [ABSTRACT FROM AUTHOR]

This paper presents a theoretical framework to enhance the prediction of dynamic responses in complex mechanical systems, such as vehicle structures, by incorporating both translational and rotational degrees of freedom. Traditional receptance coupling methods often neglect rotational effects, leading to significant inaccuracies at higher frequencies. Additionally, approaches that implicitly include full dynamics frequently result in redundancy of generalized coordinates, especially at connection points. To address these limitations, the generalized receptance coupling method using Frequency-Based Substructuring is extended to explicitly account for rotational dynamics resulting in a refined GRCFBS approach. This extension enhances both the understanding and prediction of system responses, which are represented through the receptance matrix or Frequency Response Function. Building on Jetmundsen's foundational work, the proposed framework introduces a practical, generalized formulation that explicitly incorporates full translational and rotational dynamics at each substructure node. This explicit definition provides deeper insights into system behavior, particularly for complex interactions between substructures under weak and strong coupling scenarios at interface points. The Euler–Bernoulli beam theory is employed to model rotational behavior at critical points, yielding reduced-order and explicit receptance matrices for substructures in the coupling process. The methodology's accuracy and applicability in capturing resonance and anti-resonance modes are validated through two case studies: the coupling of two flexible subsystems and the integration of flexible and rigid components. Results are benchmarked against numerical finite element analysis, and all limitations and potential improvements are discussed. By directly incorporating rotational dynamics directly, this approach enables more reliable dynamic response predictions under multi-directional loading conditions, particularly for vehicle and machinery system design. The GRCFBS method offers a versatile and reliable tool for dynamic system analysis, with significant potential for vibration analysis over a broad frequency range. [ABSTRACT FROM AUTHOR]

Posaconazole (PCZ) is a triazole antifungal agent with a broad-spectrum activity. Our research aims to present a novel approach by combining a 2-level fractional factorial design and machine learning to optimize both chromatography and extraction experiments, allowing for the development of a rapid method with a low limit of quantification (LOQ) in low-volume plasma samples. The PCZ retention time at the optimized condition (organic phase 58%, methanol 6%, mobile pH = 7, column temperature: 39 °C, and flow rate of 1.2 mL/min) was found to be 8.2 ± 0.2 min, and the recovery of the PCZ at the optimized extraction condition (500 µL extraction solvent, NaCl 10% w/v, plasma pH = 11, extraction time = 10 min, and centrifuge time = 1 min) was calculated above 98%. The results of machine learning models were in line with the results of experimental design. Method validation was performed according to ICH guideline. The method was linear in the range of 50–2000 ng/mL and LOQ was found to be 50 ng/mL. Additionally, the validated method was applied to analyze PCZ nanomicelles and conduct pharmacokinetic studies on rats. Half-life (t1/2), mean residence time (MRT), and the area under the drug concentration–time curve (AUC) were found to be 7.1 ± 0.6 h, 10.5 ± 0.9 h, and 1725.7 ± 44.1 ng × h/mL, respectively. [ABSTRACT FROM AUTHOR]

Unlike previous design procedures for parallel machine tools (PMTs), this paper first analyzes the path and posture requirements of the tools in universal processing, then proposes and constructs a new class of PMs that can provide the required path and posture. This opens up new ideas for the design of PMTs. Based on the reciprocal screw theory, a type synthesis process of asymmetrical lower-mobility PMs was proposed. Through this process, a novel class of four-limbed parallel mechanisms (PMs) providing three translations and one rotation around a horizontal axis (y-axis), denoted as 4-3T1R(y) PMs, was successfully proposed and constructed. Such PMs can be applied to the design of PMTs, especially the design of micro-electrical discharge machining (micro-EDM) PMTs. The structural design of a new 2RRC-2CRU PM, which was a member of 4-3T1R(y) PMs, was performed, and its mobility was analyzed in detail to demonstrate the efficiency of the proposed type synthesis process. The inverse, forward, and velocity kinematics problems of the 2RRC-2CRU PM were solved for further applications. [ABSTRACT FROM AUTHOR]

Currently, Brazilian coffee farming seeks the rational use of resources through sustainable practices. As a result, the development of machinery with more efficient input application systems and the adoption of precision agriculture techniques have been yielding excellent results. This study was divided into two stages, with the first involving the adaptation of a solid fertilizer application machine with fixed doses, allowing dose variation using an electronic controller. The second stage consisted of conducting trials and their applications under operational conditions. The results confirmed that the developed system remained stable in terms of variable-rate fertilizer distribution for coffee cultivation. The machine's lateral fertilizer distribution range met the demands of coffee farming satisfactorily. In field conditions, the developed system exhibited an average error of −2.9%, compared to the programmed doses, validating the accuracy of the machine and its suitability for use in coffee plantations. [ABSTRACT FROM AUTHOR]

Among the many possible metal‐cutting processes, milling is regarded as one of the most widely applied processes to machine different engineering materials productively. During the milling process, there is relative motion between the endmill tool and the workpiece. Energy is required to drive the cutting force used by the tool in separating the chips from the workpiece. Several studies have focused on the effects of milling process parameters on the cutting force, for instance by varying the cutting parameters, machining properties and the extent of cooling/lubrication. Other studies have explored the influence of tool geometry and material properties on the cutting force. Results from these studies have brought about improvements in the design of milling machinery and tools. The current study presents a novel automated approach for tool geometry optimization which is fully coded in Matlab. An automated and parametrized endmill design procedure was created featuring input parameters such as rake angle, relief angle, clearance angle and helix angle, all of which have been shown, through numerous studies, to influence cutting forces. The parameters were here used to generate the shape profile for one cutting edge of a flat endmill. This cutting edge profile is next copied and rotated, as per the design's pitch angle, to form the complete set of cutting flutes for the flat endmill. Next, the surface defined by the completed profile is meshed using quadrilateral elements. The 3D endmill design is then formed by extruding, and twisting as per the helix angle, this quadrilateral mesh to form a solid hexahedral mesh. Finally, an automated iterative optimization process was defined, featuring the above parametrized design process coupled with Abaqus‐based finite element simulation of the milling process. The expected result is that the proposed optimization procedure will be able to identify the endmill design parameters which minimize the cutting force. At the completion of the optimization, a minimized maximum resultant cutting force value is obtained from using the newly optimized endmill. The resultant cutting force was reduced by 17.6%. It is anticipated that the automated design, meshing and simulation‐driven optimization approach is generalizable to other tool design variations. [ABSTRACT FROM AUTHOR]

The mechanical transplanting of over aged seedlings (OAS) of rice poses several challenges, including seedling mortality and a significant delay in the greening period, which severely restrict yield. The causes of these issues remain unknown. Through theoretical analysis, mechanical tests, bench tests, and growth experiments were conducted to explore the reasons for seedling mortality and the significant delay in the greening period from the perspectives of seedlings, transplanting machines, and post-transplant growth. The results indicated that OAS transplanting causes combined root and stem injuries. For 40-day-old seedlings, the energy required for stem elasto-plastic deformation ranged from 1.37 to 7.19 N mm. Within this deformation range, the stem sustains internal injury but is not considered as injured seedling. The main factors influencing stem injury were the stem's major axis length and elastic modulus, whereas root injury was primarily affected by root diameter. Root and stem injuries significantly inhibited seedling growth, as demonstrated by significant structural changes in the stem 3 days post-transplantation, along with partial seedling mortality. New roots emerged only 9 days post-transplantation, and the heart leaf growth rate and SPAD value at 12 days were only 49% and 77% those of uninjured transplanted seedlings, respectively. Based on these findings, it was concluded that the seedling mortality and significant delay in the greening period observed in OAS transplantation are due to inhibited nutrient absorption and transport, caused by stem elasto-plastic deformation and weakened root vitality. These results may serve as a basis for improving transplanting machine design and optimising rice cultivation practices. • Transplant injuries in over aged seedlings (OAS) stem from root and stem injury. • Elasto-plastic stem deformation causes internal injury, which is difficult to detect. • Stem major axis length and elastic modulus are key factors influencing stem injury. • Root diameter is the key factor influencing root injury. • Stem deformation and weak root vitality cause transplant mortality in OAS. [ABSTRACT FROM AUTHOR]

G-Lattices—a novel family of periodic lattice structures introduced by Arash Armanfar and Erkan Gunpinar—demonstrate diverse mechanical properties owing to their generatively designed shapes. To assess the properties of lattice structures effectively, experimental tests and finite element analysis (FEA) are commonly used. However, the complex nature of these structures poses challenges, leading to high computation time and costs. This study proposes a machine learning (ML) approach to predict the mechanical properties of G-Lattices quickly under defined loading conditions. G-Lattice training data is generated through a sampling technique, and voxelized data is employed as ML feature vectors for predicting properties determined by FEA. To address the uneven distribution of target values, samples are clustered and utilized to train a classification model. This two-step process involves the classification of G-Lattices, followed by the application of specific regression models trained for each cluster for precise predictions. According to experiments, the ML model obtained, which predicts stiffness-over-volume ratios for G-Lattices, achieved a mean absolute percentage error of 6.5% for 1600 G-Lattices in a few seconds. Furthermore, approximately 70% of the 40,000 G-Lattices exhibited errors within 5%. The ML model's rapid predictions and acceptable accuracy make it useful for quick decision-making and seamless integration into optimization processes. [ABSTRACT FROM AUTHOR]

Sun coral, identified as Tubastraea coccinea and Tubastraea tagusensis, are invasive marine species originally from the Pacific Ocean that have become a significant threat to native biodiversity and ecosystems in Brazil. The rapid growth and unique reproduction strategies of Tubastraea species have facilitated their success as invasive species. In the past two decades, Brazil has experienced a notable loss of biodiversity, partially attributed to invasive species, as reported by the Brazilian Platform on Biodiversity and Ecosystem Services. Current management efforts primarily involve manual removal, often employing sledgehammers and chisels, carried out by environmental government agencies, in partnership with NGOs and volunteers. However, the need for more efficient management strategies emphasizes the important role of engineering and technology in improving environmental management. To address this issue, our work focuses on the development and prototyping of two underwater tools: an impact hammer and a rotating brush. These tools are designed with ergonomic features, operating time, and size considerations suitable for use by SCUBA divers. Our prototypes have successfully met the required specifications and offer potential for large-scale manufacturing, promising more effective measures for controlling invasive sun coral in Brazil. [ABSTRACT FROM AUTHOR]

Cashew (Anacardium occidentale L.) plays an important role in global agriculture, particularly in commercializing the cashew kernel. Nevertheless, kernel extraction poses a challenge due to the nut variable shape and size. Characterizing the properties of the cashew nut becomes a pivotal input for the advancement of processes and machinery. This work presents a comprehensive characterization of raw and steamed cashew nuts from Puerto Carreño, Colombia, with focus on morphological, physical, and mechanical properties. Cashew nut samples from different farms in the region were collected. Morphological properties, including size and shape, were analyzed by measuring length, width, and thickness for 100 nuts from each supplier, both in their raw state and after steaming. Geometric diameter and sphericity were calculated, and qualitative shape characterization was performed. Physical properties, such as mass, bulk density, true density, and moisture content, were also measured. Angle of repose and coefficient of friction were determined to assess flow and frictional behavior. Additionally, compressive mechanical properties were evaluated through uniaxial compression testing along three orientations. The findings indicated significant differences in morphological and mechanical properties between raw and steamed cashew nuts. Conversely, the results demonstrated that cashew nuts from Vichada region exhibit a noteworthy degree of dispersion and larger dimensions than those from Asia and Africa, comparable to those from Brazil. The findings guide machinery design in the cashew industry and offer insights into the physical, morphological, and mechanical properties of cashew nuts in Puerto Carreño, contributing to understanding and enabling quality assessment, processing optimization, and product development. [ABSTRACT FROM AUTHOR]

Fatigue design is a compulsory topic in education for several engineering specialties, particularly mechanical engineering. Textbooks on the design of machine elements have included, since long ago, the treatment of high-cycle fatigue (HCF) according to a classical theory based on the pioneering work of many researchers such as Carl Richard Soderberg. Perusing textbooks published over a long period, as well as comparing current ones, leads to the conclusion that the classical approach is presented with some differences in many of these textbooks, and this raises the need for some clarification: what are the consequences of the differences found? The present technical note addresses this problem, starting by presenting the classical approach, emphasising the variations in presentation identified, and then making a systematic comparison in order to grade the conservatism of the several variants found. [ABSTRACT FROM AUTHOR]

Smart agriculture development mainly depends on the intelligence and reliability of autonomous agricultural machinery. Automatic navigation systems (ANSs) play a key role in intelligent agricultural machinery design, as they not only reduce farmers' workloads but also improve their land utilization rates. In this paper, a tractor ANS based on dynamic path search and a fuzzy Stanley model (FSM) was designed, and its capability for whole-field path tracking was tested. First, the tracking performance of the steering control module was validated after the automatic reconstruction of the tractor platform. Then, a navigation decision system was established based on a unified reference waypoint search framework, where the path generation for whole-field coverage was presented. Finally, the gain coefficient of the Stanley model (SM) was adjusted adaptively according to the tracking error by utilizing the fuzzy logic controller. Subsequently, the developed tractor ANS was tested in the field. The experiment's results indicate that the FSM outperformed the SM in straight path tracking and whole-field path tracking. When the tractor traveled at a speed of 1 m/s, the maximum lateral tracking error for the straight path was 10 cm, and the average lateral tracking error was 5.2 cm, showing improvements of 16.7% and 10.3% compared to the SM. Whole-field autonomous navigation showed that the maximum lateral tracking error was improved from 34 cm for the SM to 27 cm for the FSM, a reduction of approximately 20.6%, illustrating the superiority of the FSM in the application of whole-field path tracking. As the maximum tracking error of whole-field autonomous navigation appears in the turning stage, where tractors often stop working, the designed ANS satisfies the requirements of a self-driving system for unmanned tractors. [ABSTRACT FROM AUTHOR]

The involute profile is used almost exclusively in the manufacturing of spur gears. Nevertheless, in machinery design, the evaluation of environmental factors, such as energy efficiency, has become increasingly important when choosing between feasible solutions. As a result, the study of alternative profiles is gaining interest. The key novelty of this study is the comparative analysis of involute and cycloidal gear profiles with respect to frictional power losses in the tooth contact, as well as their impact on energy efficiency in spur gear transmissions. The coefficient of friction is approximated using two widely applied analytical lubrication models: the elastohydrodynamic and mixed elastohydrodynamic, both of which provide enough accurate values with a reasonable amount of computation burden in comparison with numerical methods. An additional contribution of this study is a sensitivity assessment of the energy efficiency of the cycloidal profile with regard to the auxiliary centrode diameters. This allows for an understanding of the geometrical constraints of this profile, specifically the maximum pressure angle—which is related to the radial loads applied to the shaft—and the tooth height—which is related to the bending moment at the tooth root—and hence, setting the appropriate ones to be equivalent to the involute profile. For the comparative analysis, equivalent profiles are selected based on similar tooth bending moments and radial loads supported by the shaft. After determining the centrode diameters of the cycloidal profile, the efficiency of both gear profiles and their sensitivity to gear size and gear ratio are compared. This study concludes that, for both profiles and friction analytical models, efficiency improves with increasing gear sizes and gear ratios, eventually converging to a constant value. Furthermore, both cycloidal and involute profiles exhibit comparable performance in terms of energy efficiency across both lubrication analytical models. [ABSTRACT FROM AUTHOR]

On 14 June 2023, the European Parliament adopted Regulation (EU) 2023/1230 on machinery, which entered into force on 19 July 2023 (with some exceptions as per art. 54, according to a corrigendum issued to address a clerical error as regards the application dates in the original version) and shall apply from 20 January 2027, replacing the Machinery Directive 2006/42/EC. The main innovations/differences introduced by the Machinery Regulation (MR) compared to the Machinery Directive (MD) are critically analysed here, with a focus on sustainability issues. Some of these issues are covered by several international standards (such as BS 8887, ISO 10987 or DIN 91472), which also define the criteria and requirements for the remanufacturing process, although some technical gaps remain. Using the example of agricultural machinery, this paper proposes a methodology for determining the areas of acceptability for remanufactured products: these are expressed in terms of structural performance (e.g., the number of cycles ahead to failure expressed as the mutual of damage 1 − D = 0.625 ) and the functional and safety requirements of the original machine. In this way, the issue of "substantial modification of machinery" is explored in terms of the safety obligations that the remanufactured machinery must fulfil. The paper is therefore a contribution to circular design by providing general criteria for the extension of the service life of machinery while at the same time considering safety issues. [ABSTRACT FROM AUTHOR]

This paper proposes a novel consequent pole machine (CPM) to improve cogging torque, torque ripple, and torque per magnet volume compared to a conventional CPM. The proposed structure consists of a consequent pole rotor that reduces permanent magnet (PM) material. Different from conventional surface permanent magnet machines (SPMs) and conventional CPMs, the proposed CPM has an additional iron pole (AIP) extension under the magnet. This structure is suggested in order to increase the magnet pole angle while maintaining the magnet volume by partially substituting the magnet with iron. The design of the proposed machine was optimized to achieve higher torque and lower torque ripple. Comparisons of the proposed CPM with a conventional SPM and CPM were conducted to show the superiority of the proposed CPM utilizing AIP. The results showed that the proposed CPM exhibits 68% lower cogging torque, 75% lower torque ripple, and 16% higher torque per magnet volume with the same magnet volume compared with the conventional CPM. [ABSTRACT FROM AUTHOR]

To comprehensively improve the thermal, static and dynamic characteristics and achieve lightweighting for CNC machine tools, this paper proposes a multi-objective joint optimization method based on coupled thermal–mechanical–vibration collaborative analysis. The dual-spindle component of a CNC machine tool is taken as the parameterized model. According to the theories of thermal characteristics, statics, and dynamics, the solution of thermal-mechanical coupling deformation and the solution of vibration characteristics under prestress are repeatedly conducted, that are working collaboratively with each process of parameters sensitivity computing, selection of design variables, central composite design, and multi-objective joint optimization. The response surfaces of the objective functions are established. The optimal parameter combination for improving CNC machine tool performance is effectively obtained. And the multiple objectives of improving the thermal, static and dynamic characteristics, as well as lightweighting, are achieved. The results show that the mass of the optimized component is reduced by 10.1%; the first-order natural frequency is increased by 3.9%; the coupling deformation of the end face of the left spindle seat is reduced by 5.3%; and the coupling deformation of the end face of the right left spindle seat is reduced by 9.0%, while the temperature of the component hardly increases. This indicates that this method can comprehensively improve the performance of CNC machine tool components and provide a reference for the multi-objective joint optimization design of CNC machine tools. [ABSTRACT FROM AUTHOR]

Paving straw checkerboard barriers in the desert is an efficient measure of wind break and sand fixation. Generally, straw checkerboard barriers are paved manually. Focusing on the low automation level of straw checkerboard barrier paving, a portable paving vehicle for straw checkerboard barriers was designed in this paper. First, the portable paving vehicle for straw checkerboard barriers was designed using SolidWorks, and the design contents include a grass insertion mechanism, an intermittent transmission mechanism, a metamorphic mechanism, and motor and power supply. Then, the load test of the grass insertion mechanism was carried out to determine the maximum force load of 25 N during the grass insertion process, and the strength of the rocker and the horizontal slide rod were checked. Among them, the safety factor of the rocker rod and the horizontal slide rod were 1 and 1.5, respectively, and the allowable stress of the rocker rod and the horizontal slide rod was 27.3 MPa and 205 MPa. The maximum stresses of 0.92 MPa and 67 MPa were less than the allowable stresses, which meet the strength requirements. In order to verify the design principle and the results of the strength check, the grass insertion mechanism, rocker, and horizontal slide rod were analyzed by using ABAQUS. The results show that the grass insertion mechanism has an obvious rapid return characteristic, which is in agreement with the design principle. At the same time, the maximum stress of the rocker rod and the horizontal slide rod was 1 MPa and 36 MPa, respectively, which meets the strength requirements. Finally, the physical prototype was manufactured and its running state was verified. The results show that the physical prototype can pave the straw checkerboard sand barrier on the sand normally, and the portable paving vehicle for straw checkerboard barriers can be a reference for other sand-control vehicles and provide an effective way of paving straw checkerboard barriers to control desertification. [ABSTRACT FROM AUTHOR]

Studies on the discrete element method (DEM) parameters of Morchella seeds are limited due to their high moisture content and weak inter-particle adhesion. However, accurate DEM simulations are crucial for the design of agricultural machinery. Physical experiments were conducted to measure the fundamental properties of Morchella seeds, and a DEM model was established using the Hertz–Mindlin with JKR contact model. Subsequently, Plackett–Burman, steepest ascent, and Box–Behnken experiments were employed. They were used to analyze the significance of key contact parameters. A second-order polynomial regression model for the repose angle was developed, and significant contact parameters were optimized and calibrated. The results showed that the seed-to-seed rolling friction coefficient, seed-to-seed surface energy, and seed-to-steel rolling friction coefficient significantly impacted the repose angle. The simulation results using the optimized contact parameters closely matched the repose angle measured in physical experiments. The relative error was only 0.16%, validating the accuracy of the parameter calibration. [ABSTRACT FROM AUTHOR]

Prediction models in foreign exchange markets have been very popular in recent years, and in particular, through the use of techniques based on Machine Learning. This growth has made it possible to train several techniques that increasingly allow us to improve predictions according to the criteria that each algorithm supports and can cover. However, the development of these models and their deployment within computer platforms is a complex task, given the variety of approaches that each researcher uses based on the training process and therefore by definition of the model, which leads to the consumption of high computing resources for its training, as well as various processes for its deployment. For this reason, the following article focuses on designing a technological platform oriented to micro services, which minimizes the consumption of resources and facilitates the integration of various techniques and the analysis of various criteria, which improves their analysis and validation in a Web environment. [ABSTRACT FROM AUTHOR]

This study aimed to improve small-scale cabbage harvesting, which usually depends on labour-intensive methods. To solve this issue, an electric cabbage harvester for single-row applications was designed and developed. The harvester integrates different units, such as cutting, conveying, precise cabbage pushing, propelling, power supply (lead acid batteries), storage bin, and handle. The study involved selecting appropriate driving motors, optimising transmission in each unit, and designing the power supply. Critical components, including the cutter, pusher, and propelling shafts, were designed and subjected to static and dynamic analysis using ANSYS R18.0. In the static analysis torque values of 27.52 Nm, 40.99 Nm, and 888.35 Nm were used for the cutter, pusher, and propelling shafts, respectively, with dynamic analysis assuming peak torques 1.5 times higher. Maximum equilibrium stresses in the static analysis were 14.20 MPa, 7.35 MPa, and 36.36 MPa, while the dynamic analysis recorded 22.996 MPa, 9.145 MPa, and 66.88 MPa, all below the material's yield stress. The results confirmed the safety and reliability of these components during field operations. A 2571 × 880 × 742 mm prototype was developed, with hand vibration and noise levels measured at 2.098 m/s2 and 78 dB(A), ensuring ergonomic safety. The harvester presents a promising solution for mechanising small-scale cabbage harvesting. [ABSTRACT FROM AUTHOR]

The development of machines explores the development of a manufacturing system. This perspective offers challenges adjacent to the materials, the product that wants to be manufactured, the technical considerations that must be covered during implementation and the manner of delivering the products to the user. This article addresses the design and development of machines, on the one hand the redesign of a multifunctional platform, and on the other hand a 3D food printer. The second is emphasised, since its main objective is to help the food problems that exist today. The design phases, aspects considered for its implementation such as food safety, the choice of the substrate, the functionality of the food, transportation and the pre- and post-processes required. In this manner, the selection and innovation of materials constitutes a primary source of innovation and research in the integral development of a 3D food printer. The main source of value of these both cases lie in customisation. The experiences of a multidisciplinary research team in the development processes are compiled and the design and creation process are shown, in order to contribute to deal with design and development to tackle fundamental problems of society. [ABSTRACT FROM AUTHOR]

Design Thinking is a user-centred framework that captures unmet needs of users and generates ideas for sustainable solutions. Quality Function Deployment is a tool that translates the voice of customers into engineering attributes required for product and process design. Both concepts are globally adopted in various fields including but not limited to; manufacturing industries, business and service sectors, education, research, health care and social innovation. This study aims to propose a methodological framework that combine principles from user-driven ideation and customer-focused product/process design for the development of a sustainable solution in the context of small-scale agricultural community. The framework is validated with a case study at a learning community centre in Thailand. The machine was built with functions that allowed it to shred plants and mix the fertiliser simultaneously which was well accepted and sustainably used in the community. A policy recommendation based on this study is when working with community-based problems, the designers should immerse themselves with the community to completely understand the problem and solution context. A co-creation between the designers and the community users is encouraged to obtain impactful solutions. Local resources and accessible technology should be taken into account to reassure an effective and sustainable solution. [ABSTRACT FROM AUTHOR]

Developing contemporary antennas is a challenging endeavor that requires considerable engineering insight. The most laborious stage is to devise an antenna architecture that delivers the required functionalities, e.g., multiband operation. Iterative by nature (hands-on topology modifications, parametric studies, trial-and-error geometry selection), it typically takes many weeks and requires considerable engagement from a human expert. Consequently, only a few possible design options concerning the fundamental antenna geometry may be considered. Automated topology rendition and geometry parameter optimization are highly relevant, especially from the industrial perspective. Therein, reducing time-to-market and limiting the involvement of trained experts is critical. This research proposes an innovative procedure for unsupervised development of planar antennas. Our method leverages flexible antenna parameterization based on re-sizable elliptical patches. It permits the realization of a massive number of geometries of diverse shapes and complexities using a small number of decision variables. Computational intelligence methods are employed to conduct antenna evolution exclusively based on specifications and possible constraints (e.g., maximum size). Fine-tuning of the structure geometry is achieved through low-cost local search routines. Our methodology is demonstrated by designing several antennas featuring distinct characteristics (broadband, single-, dual- and triple-band). The obtained results, supported by experimental data, underscore the presented approach's versatility and capability to render unconventional topologies at reasonably low computational expenses. As mentioned earlier, the design process is fully automated without human expert involvement. [ABSTRACT FROM AUTHOR]

Most single-screw extruders used in the plastics processing industry are plasticizing extruders, designed to melt solid pellets or powders within the screw channel during processing. In many cases, the efficiency of the melting process acts as the primary throughput-limiting factor. If the material melts too late in the process, it may not be sufficiently mixed, resulting in substandard product quality. Accurate prediction of the melting process is therefore essential for efficient and cost-effective machine design. A practical method for engineers is the modeling of the melting process using mathematical–physical models that can be solved without complex numerical methods. These models enable rapid calculations while still providing sufficient predictive accuracy. This study revisits the modified Tadmor model by Potente, which describes the melting process and predicts the delay-zone length, extending from the hopper front edge to the point of melt pool formation. Based on extensive experimental investigations, this model is adapted by redefining the flow temperatures at the phase boundary and accounting for surface porosity at the beginning of the melting zone. Additionally, the effect of variable solid bed dynamics on model accuracy is examined. Significant model improvements were achieved by accounting for reduced heat flow into the solid bed due to the porous surface structure in the solid conveying zone, along with a new assumption for the flow temperature at the phase boundary between the solid bed and melt film. [ABSTRACT FROM AUTHOR]

The emergence of 3D and 4D printing has transformed the field of polymer composites, facilitating the fabrication of complex structures. As these manufacturing techniques continue to progress, the integration of machine learning (ML) is widely utilized to enhance aspects of these processes. This includes optimizing material properties, refining process parameters, predicting performance outcomes, and enabling real-time monitoring. This paper aims to provide an overview of the recent applications of ML in the 3D and 4D printing of polymer composites. By highlighting the intersection of these technologies, this paper seeks to identify existing trends and challenges, and outline future directions. [ABSTRACT FROM AUTHOR]

In this paper, we introduce an innovative design approach based on combined numerical simulations and machine learning (ML) analysis to investigate the design key parameters of ultra‐low scale junctionless gate‐all‐around (JLGAA) field‐effect transistor (FET) devices. To this end, precise 3D numerical models that incorporate quantum effects and ballistic transport are employed to simulate the current–voltage (I–V) characteristics of 10 nm‐scale JLGAA FET devices. The influence of design parameter variations and high‐k dielectric material on the subthreshold characteristics is thoroughly examined. Various ML algorithms were employed to analyze and classify the key design parameters influencing the subthreshold figures‐of‐merit (FoMs), the subthreshold swing (SS) factor and ION/IOFF ratio. The obtained results highlight that channel radius and channel doping design parameters are particularly important for affecting swing factor behavior. Similarly, these features also play a significant role in predicting and affecting ION/IOFF current ratio values. Additionally, machine learning is used to determine the optimal design parameters for each figure of merit (FoM) output value. In this context, the models effectively predicted both ION/IOFF current ratios and SS classification, with Naive Bayes achieving an accuracy of 90.8% for ION/IOFF and 92.6% for SS, showcasing the model's robustness in these classification tasks. [ABSTRACT FROM AUTHOR]

The practical development of Li | |S batteries is hindered by the slow kinetics of polysulfides conversion reactions during cycling. To circumvent this limitation, researchers suggested the use of transition metal-based electrocatalytic materials in the sulfur-based positive electrode. However, the atomic-level interactions among multiple electrocatalytic sites are not fully understood. Here, to improve the understanding of electrocatalytic sites, we propose a multi-view machine-learned framework to evaluate electrocatalyst features using limited datasets and intrinsic factors, such as corrected d orbital properties. Via physicochemical characterizations and theoretical calculations, we demonstrate that orbital coupling among sites induces shifts in band centers and alterations in the spin state, thus influencing interactions with polysulfides and resulting in diverse Li-S bond breaking and lithium migration barriers. Using a carbon-coated Fe/Co electrocatalyst (synthesized using recycled Li-ion battery electrodes as raw materials) at the positive electrode of a Li | |S pouch cell with high sulfur loading and lean electrolyte conditions, we report an initial specific energy of 436 Wh kg−1 (whole mass of the cell) at 67 mA and 25 °C. The atomic-level interactions among electrocatalytic sites in Li | |S batteries remain unclear. Here, authors propose a multiview machine-learned framework to evaluate electrocatalyst features using limited datasets and intrinsic factors, thus enhancing the understanding of electrocatalytic sites. [ABSTRACT FROM AUTHOR]

Addressing the challenges of limited passability and adaptability encountered by existing pipe robots in navigating through tee and four-way junction pipes, This article designs a pipe robot based on the principle of metamorphism. This robot is designed with a variable number of linkages, constituting the core of its system structure. Through this innovative approach, it achieves movement in diverse types of pipelines by altering its own structural configuration. Kinematic analysis is conducted using both the Denavit-Hartenberg (D-H) method and screw theory, providing expressions for the forward kinematics in terms of the robot's positional and attitudinal states, as well as geometric solutions for the inverse kinematics. Simulations conducted in MATLAB and ADAMS software demonstrate consistent postural changes of the robot, validating its design and capabilities. Prototype experiments in a 500 mm diameter pipeline further confirm the robot's structural design rationality and its ability to navigate through tee and four-way junction pipes by altering its posture. The results indicate that this pipe robot effectively navigates through straight, vertical tee, and horizontal four-way junction pipes, offering a viable solution for efficiently maneuvering through complex pipeline junctions. [ABSTRACT FROM AUTHOR]

Copyright of Machine Tool & Hydraulics is the property of Guangzhou Mechanical Engineering Research Institute (GMERI) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The design of integrated circuits in the analog spectrum is intricate due to the signals' continuous nature. Additionally, it is strongly affected by the physical implementation of their devices and interconnections on the layout, a design task that has stubbornly defied all automation attempts. In this paper, one limitative factor is identified that must be addressed to finally push automation tools into the analog integrated circuit design flow: accurate assessment of post-layout performance degradation. For this purpose, a performance-driven placement generator highly integrated with off-the-shelf tools already adopted by circuit/layout designers, i.e., circuit simulator, verification tools (layout-versus-schematic) and layout extractor, is proposed. Toward maximum post-layout accuracy, this generator promotes an exhaustive simulation-based synthesis, extracting, simulating and verifying the post-layout functional behavior of every candidate floorplan. Additionally, to bypass the time-consuming extractions/simulations and accelerate synthesis, novel post-layout performance regressors based on different highly accurate machine learning techniques are also being developed. The data used to train them can be directly and conveniently acquired from previous precise post-placement simulations. Experimental results over two analog circuit structures show that a set of performance regressors based on tree-based models, while operating on compressed design spaces, allow for the speeding up of synthesis by more than 20×, which represents a step toward an efficient fully automatic performance-driven analog integrated circuit design flow. [ABSTRACT FROM AUTHOR]

This research integrates experimental visualization via high-speed photography with numerical simulations, leveraging large eddy simulation and the Schnerr–Sauer (S-S) cavitation model, to examine cavitation dynamics on a flat-plate hydrofoil across a range of tip clearance settings. We identify three distinct cavitation patterns caused by tip clearance (CT) in terms of the flow structures and interactions of tip leakage vortex cavitation, tip separation vortex cavitation (TSVC), and shear layer cavitation. The flat-plate hydrofoil demonstrates stronger TSVC and more pronounced vortex interactions compared to National Advisory Committee for Aeronautics 0009 hydrofoils. A phase diagram is established to predict the cavitation patterns of CT under different operational conditions of the cavitation number σ and the angle of attack α. We also observe a downwash effect from the vortices, influencing the cavitation length on the suction side of the hydrofoil. The findings are significant for optimizing hydrofoil designs in fluid machinery where effective cavitation management is critical. [ABSTRACT FROM AUTHOR]

• Much research on human machine interface design exists for driving automation. • A literature review identified commonalities and differences of interface design. • Multimodal alerts are prominent, useful, and effective. • We propose 10 guidelines for interface design in driving automation systems. The effectiveness of the human–machine interface (HMI) in a driving automation system is based, in part, on how it issues alerts and requests to the driver—it must quickly and sufficiently orient the driver to the driving task. While much research on the design of HMIs exists, unique associations and meaningful relationships must be considered collectively to offer guidance for vehicle automation. The purpose of the current study was to: (a) review and synthesize existing research and guidance on HMI design as it related to requests to intervene (RTI) for driving automation systems and (b) propose a clear and comprehensive set of recommendations that could inform future system development and implementation. A thorough literature search and selection process was followed the PRISMA guidelines and resulted in the review of 93 articles. The review's outcome indicates multimodal alerts are prominent, useful, and effective. Many of the HMIs reported in the literature were similar in that they abided by well-established HMI-design guidelines. A small subset of HMIs established evidence for distinct and innovative design principles. Taken together, this study proposed 10 recommendations for HMI design in driving automation systems, ranging from the utility of auditory versus visual alerts to the timing, sensitivity, and location of alerts. [ABSTRACT FROM AUTHOR]

Observational data with massive sample sizes are often distributed on many local machines. From an experimental design perspective, investigators often desire to identify the effect of new treatments (even ML algorithms) on many blocks of experimental data. With time requirements or budget constraints, assigning all treatments to each block is not always feasible. This creates incomplete responses with respect to a randomized complete block design (RCBD). These incomplete responses are missing by design. However, whether they can be estimated with missing imputation methods is not well understood. Thus, it is challenging to correctly identify the treatment effects with missing data. To this end, this paper provides a method for imputation and analysis of the responses with missing data. The proposed method consists of three steps: Reconstruction, Imputation, and 'Complete'-data Analysis (RICA). The incomplete responses are imputed with the expectation-maximization (EM) algorithm. The RCBD model is then fitted by the resulting dataset. The identifiability result suggests that the missing may be nonignorable for each block, but the whole data of an incomplete design are missing by design when the design is balanced. Theoretical results on relative efficiency also inform us when the missingness should be imputed for incomplete designs with the role of balanced variance. Applications on real-world data verify the efficacy of this method. [ABSTRACT FROM AUTHOR]

The existing I2C interfaces require significant CPU intervention for data communication. In SOC systems, when using internally integrated I2C modules as masters, software control of I/O ports is necessary to emulate the I2C protocol for data transmission. This paper proposes a Mini I2C bus interface circuit design scheme that supports both master and slave modes. The I2C interface features minimal CPU intervention during data transmission, ease of use, small circuit area, and low power consumption. Additionally, the internal state machine design employs independent finite state machines (FSMs) for master and slave modes, enabling flexible configuration of the I2C module to operate in either mode. In comparison to reference (ShenZhen in Microelectronics Technology CO.BJ8M306A, Datasheet.2019.12.2., 2019), the proposed I2C solution reduces CPU instructions by 50% during data transmission, and by 33% compared to reference (GigaDevice Semiconductor Inc. GD32F1x0, Datasheet, 2022). After DC synthesis, the proposed design occupies only 14% of the area and consumes only 3.6% of the power of the Open Source I2C Design (Forencich in verilog-i2c. GitHub repository. Retrieved from https://github.com/alexforencich/verilog-i2c, n.d.). Therefore, this design scheme is better suited for low-power systems. The proposed design was validated through simulation using Xilinx ISE 14.7 with a SPARTAN 3 FPGA model xc3s500e-5pq208, and finally implemented using Huahong 95 nm CMOS technology, demonstrating high integration and low power consumption. [ABSTRACT FROM AUTHOR]

Copyright of Industria Textila is the property of Institutul National de Cercetare-Dezvoltare pentru Textile si Pielarie and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In order to solve the problems of traditional orchard-specific green manure crushing and returning machines, such as the single operation effect, root system damage, unsustainable green manure growth, and low utilization rate, an offset crushing–furrowing–burying–straw-returning machine was designed for green manures in orchards. Based on quadratic regression combination experiments, the Discrete Element Method (EDEM) was used to construct a discrete element model simulating the deep furrowing and burying processes of the furrowing and soil-covering device, where the advance speed, plow-shaped furrowing blade rotation speed, and furrowing depth were considered as experimental factors and the coverage rate was taken as an evaluation index, and then simulation analyses were carried out to obtain experimental data; Design-Expert was used to perform ANOVA and RSM analyses, thus finding that its optimal working parameter portfolio consists of the advance speed of 42 m/min, the furrowing blade rotation speed of 300 r/min, and the furrowing depth of 190 mm, and that the coverage rate is 95.82% when this parameter portfolio is applied. Field experiments were conducted to validate the optimal parameter portfolio. The experimental results show that with an average coverage rate of 90.87% (4.95% away from the optimal value based on the simulation experiments on average), an average crushing length qualification rate of 91.24%, and an average root system damage rate of 5.6%, this device is applicable for its operation conditions. The development of this machine and the construction of its parameter model can provide a certain reference value for developing and optimizing related machines including green manure-returning machines. [ABSTRACT FROM AUTHOR]

This article describes the complete development of a design project for a context-integrated appropriate technology, a gravity ropeway for transporting agricultural products in remote areas of Nepal. The main purpose was to improve and optimize existing gravity ropeway designs, prioritizing simplicity, safety, and local manufacturability and maintenance. The design process followed a phased methodological approach used in machine design, which included stages of definition, conceptual design, materialization, and detailed design. The results of the ropeway installation demonstrate a reduction in the time and effort required by farmers to transport their products, consequently leading to a significant improvement in their quality of life. Despite the methodology followed, deficiencies were identified in the project execution procedure: lack of documentation and lack of explicit consideration of the local context in the design specifications, which could compromise the continuity and success of the project. This analysis highlights the need to adapt traditional design methodologies to appropriate technology projects. Specific procedures that address the characteristics of the local environment should be included to integrate the design into the context and accurately determine the needs of users in development projects. [ABSTRACT FROM AUTHOR]

In the process of product design decision-making (PDDM), decision-makers (DMs) conventionally engage in discussions to evaluate design alternatives. Achieving a consistent result is essential for selecting optimal product design schemes, as it helps eliminate preference conflicts. However, uncertainties and ambiguities, along with the interrelationships among DMs, make it challenging to attain an acceptable consensus level in PDDM. To address this issue, intuitionistic fuzzy sets (IFSs) are introduced to capture DMs' preferences regarding product design schemes, and a trust network is integrated to analyze DMs' interrelationships. A double hierarchy linguistic term set (LTS) is employed to assess DMs' relationships, and an incomplete trust network is supplemented by leveraging the transitivity principle, thereby determining DMs' weights. By establishing a consensus measurement model, DMs contributing less to consensus are identified, and consensus optimization is achieved through the modification of DMs' preferences or the calibration of their trust relationships. A consensus reaching process (CRP) for PDDM is proposed, and the technique for order preference by similarity to ideal solution (TOPSIS) is utilized to rank product design schemes after consensus is reached. A case study involving the decision-making process for a specific household disinfection machine design illustrates the efficacy of our method in achieving consensus by integrating vague PDDM data. [ABSTRACT FROM AUTHOR]

The current investigation examines the influence of footing shape, the base area of footing (A), the mass of footing-machine assembly (m), and eccentric force settings (mee) on the dynamic response and performance of machine foundation systems. Five different footing configurations are employed to perform field block vibration tests involving three square, one circular and one rectangular footing. The experiments are performed at the geotechnical field laboratory of IIT Kanpur, India (N26°30′59.0892″, E80°13′51.6888″). The accuracy and reliability of the experimental results are endorsed by the results obtained from the mass-spring-dashpot (MSD) analysis. In addition, an artificial neural network (ANN) model is created to anticipate the dynamic behaviour of the soil-foundation system. A thorough parametric study demonstrates the efficacy of the developed ANN model. It is revealed from the investigation that the stiffness (k) and the damping ratio (D) of the soil for square foundations increase by 7% and 3%, respectively, with a 40% increase in A. Similarly, the circular foundation exhibits 7 and 3% higher k and 4 and 3% higher D than those obtained for square and rectangular foundations, respectively. For square foundations, a 24% enhancement in m leads to a 42 and 4% increase in k and D, respectively. In contrast, for circular and rectangular foundations, a 13% increase in m results in a 27 and 19% increase in k and D, respectively. In this study, experimental testing, analytical validation, and ANN modelling provide insight into the response of machine foundations under various operating conditions. The results of this study can be utilized to optimize the design of machine foundations. [ABSTRACT FROM AUTHOR]

In the future ten years, the mining depths of more than 30% metal mines will exceed 1000 m. Deep metal mining is confronted with complex geological conditions such as high in-situ stress, high ground temperature, highly-changeable grounds and strong mining disturbance, which bring severe challenges to roadway construction. Due to the shortcomings of noncontinuous operation, low construction rate and frequent disaster occurrence, traditional drilling-and-blasting method cannot meet the construction requirement, therefore the use of tunnel boring machine (TBM)for continuous mechanical tunnelling becomes the future development direction of deep metal mine roadway construction. However, due to the distinctive engineering geological features and roadway construction requirements, the application of TBM tunnelling technology in deep metal mine roadway construction still suffers from some technological problems and challenges. First, this paper summarizes the three main application difficulties for TBM tunnelling technology in deep metal mine roadway construction; 1) the lack of adaptative TBM type selection and machine design theory; 2) the lack of high efficient TBM tunnelling technology; 3) the lack of prewarning, prevention and control technology for engineering disasters. Then, this paper introduces the current research progresses for TBM tunnelling technology in deep metal mine roadway construction from six aspects, i. e., efficient rock breakage theory for cutterhead and cutters, adaptative TBM type selection and machine design technology, accurate tunnelling performance prediction and evaluation methodology, tunnelling technology for small turning radius or highly-inclined roadways, intelligent prewarning, prevention and control technology for engineering disasters, intelligent decision-making and assisted-driving technology. The above research progresses primarily indicate the development direction for the extensive application of TBM tunnelling technology for rapid roadway construction in deep metal mines. [ABSTRACT FROM AUTHOR]

Student attrition poses significant societal and economic challenges, leading to unemployment, lower earnings, and other adverse outcomes for individuals and communities. To address this, predictive systems leveraging machine learning and big data aim to identify at-risk students early and intervene effectively. This study leverages big data and machine learning to identify key parameters influencing student dropout, develop a predictive model, and enable real-time monitoring and timely interventions by educational authorities. Two preliminary trials refined machine learning models, established evaluation standards, and optimized hyperparameters. These trials facilitated the systematic exploration of model performance and data quality assessment. Achieving close to 100% accuracy in dropout prediction, the study identifies academic performance as the primary influencer, with early-year subjects like Mechanics and Materials, Design of Machine Elements, and Instrumentation and Control having a significant impact. The longitudinal effect of these subjects on attrition underscores the importance of early intervention. Proposed solutions include early engagement and support or restructuring courses to better accommodate novice learners, aiming to reduce attrition rates. [ABSTRACT FROM AUTHOR]

This paper presents a method aimed at improving comprehension of AC electric machine principles by facilitating the learning of the Rotating Magnetic Field (RMF) through visualization tools provided by Finite Element Method (FEM) software. First, traditional methods used in textbooks to explain RMF in electric machines are reviewed, with an analysis of various instructional strategies. Acknowledging the limitations of these conventional approaches and the inherent complexity of RMF comprehension, a novel visualization method is proposed. Understanding RMFs in electric machines is fundamental for electrical engineers due to their crucial role in electric machine design and optimization. While textbooks typically rely on mathematical explanations and simple sketches, advancements in computer and software technology offer opportunities to utilize finite element tools for enhanced comprehension. Through dynamic animations and interactive simulations, emphasis is placed on prioritizing conceptual understanding over mathematical descriptions. Furthermore, this paper explores the development of pre‐simulation models in FEM tools to facilitate RMF learning in AC electric machines, and the process of creating a model to teach rotating magnetic fields in electric machines is carefully outlined. This approach holds promise for engineers seeking a deeper understanding of electric machines and can also be utilized by educators to enhance their teaching methodologies. [ABSTRACT FROM AUTHOR]

Bean damage is one of the primary concerns in the pod-breaking process. Studies for pod-breaking machines are ongoing to ensure that the products made from these machines are of good quality. The objective of the study is to determine the physical and mechanical characteristics of the UF-18 pod. The Arduino-based load compressor testing machine was designed and developed to characterize the UF-18 pod. It was found that the average geometric mean diameter, surface area, and sphericity index of 115.37 mm, 41,899.48 mm2, and 0.6372, respectively, and with a variation of ±27.17, ±14538133.04, and ±0.00038 respectively. Furthermore, the cacao pod samples had an average dimension of 181.29 mm, 94.26 mm, 90.01 mm, and 17.44 mm measured for the length, equatorial diameter, intermediate diameter and external thickness, respectively. Different pod sizes and thicknesses require various forces ranging from 36.94 to 92.42 kg (362.38 N to 906.64 N) and time ranging from 6-11 seconds to be able to break the pods. Determining the physical and mechanical properties of cacao pods enables fabricators to design efficient machines, which lessens the force to break and the damage to the beans, thus producing quality beans. [ABSTRACT FROM AUTHOR]