Machine Design Research Articles

Design and simulation of a desk-size parallel kinematic machine for simulation of seismic events

Design and simulation of a desk-size parallel kinematic machine for simulation of seismic events

Deep Learning Methods in Soft Robotics: Architectures and Applications

The area of soft robotics has been subject to intense research efforts in the past two decades and constitutes a paradigm for advanced machine design in future robotic applications. However, standard methods for industrial robotics may be difficult to apply when analyzing soft robots. Deep learning, which has undergone rapid and transformative advancements in recent years, offers a set of powerful tools for analyzing and designing complex soft machines capable of operating in unstructured environments and interacting with humans and objects in a delicate manner. This review summarizes the most important state‐of‐the‐art deep learning architectures classified under supervised, unsupervised, semisupervised, and reinforcement learning scenarios and discusses their main features and benefits for different soft robotic applications, including soft robot manipulators, soft grippers, soft sensors, and e‐skins, as well as bioinspired soft robots. Specific properties of recent deep learning architectures and the usefulness of their features in addressing various types of issues found in soft robotics are analyzed. The existing challenges and future prospects are identified and discussed in view of the enhanced integration of both areas, which improves the performance of next‐generation soft machines operating in real‐world conditions.

Improvement in an Analytical Approach for Modeling the Melting Process in Single-Screw Extruders

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.

Demonstration of a programmable optical lattice atom interferometer

Performing interferometry in an optical lattice formed by standing waves of light offers potential advantages over its free-space equivalents since the atoms can be confined and manipulated by the optical potential. We demonstrate such an interferometer in a one-dimensional lattice and show the ability to control the atoms by imaging and reconstructing the wave function at many stages during its cycle. An acceleration signal is applied, and the resulting performance is seen to be close to the optimum possible for the time-space area enclosed according to quantum theory. Our methodology of machine design enables the sensor to be reconfigurable on the fly, and when scaled up, offers the potential to make state-of-the art inertial and gravitational sensors that will have a wide range of potential applications. Published by the American Physical Society 2024

Effectiveness analysis of a novel rectangular tunnel boring machine with planetary transmission for box jacking

Traditional rectangular tunnel boring machines have low tunneling efficiency, poor soil mixing effects, which has hindered the construction of long-distance and large-section box jacking projects. To overcome these limitations, a new type of full-face excavation boring machine was developed based on a planetary transmission mechanism. This machine achieves full-face excavation by utilizing three eccentric cutter heads that revolve around both the central axis of the cutter plate and their individual shafts. The design methodology, feasibility, and principles of this new mechanism were introduced. Furthermore, a successful construction project of an underground highway passage in Japan was presented as a case study to demonstrate the design and application of this tunnel boring machine. The case details include the excavation face support mechanism, optimal cutter-head layout, obstacle removal strategies, and methods for reducing jacking resistance. Monitoring data from the project verified the applicability, reliability, and overall engineering performance of the rectangular shield machine developed using the planetary mechanism. This research demonstrates that the planetary transmission mechanism-based boring machine offers superior performance in terms of ground settlement and tunneling speed, potentially providing a comprehensive solution to the challenges in the development of rectangular shield machines for box jacking projects.

Double machine learning and design in batch adaptive experiments

Abstract We consider an experiment with at least two stages or batches and O ( N ) O\left(N) subjects per batch. First, we propose a semiparametric treatment effect estimator that efficiently pools information across the batches, and we show that it asymptotically dominates alternatives that aggregate single batch estimates. Then, we consider the design problem of learning propensity scores for assigning treatment in the later batches of the experiment to maximize the asymptotic precision of this estimator. For two common causal estimands, we estimate this precision using observations from previous batches, and then solve a finite-dimensional concave maximization problem to adaptively learn flexible propensity scores that converge to suitably defined optima in each batch at rate O p ( N − 1 ⁄ 4 ) {O}_{p}\left({N}^{-1/4}) . By extending the framework of double machine learning, we show this rate suffices for our pooled estimator to attain the targeted precision after each batch, as long as nuisance function estimates converge at rate o p ( N − 1 ⁄ 4 ) {o}_{p}\left({N}^{-1/4}) . These relatively weak rate requirements enable the investigator to avoid the common practice of discretizing the covariate space for design and estimation in batch adaptive experiments while maintaining the advantages of pooling. Our numerical study shows that such discretization often leads to substantial asymptotic and finite sample precision losses outweighing any gains from design.

The Exposure Height of Silicon Particle with Round Edges Effect on the Tribological Property of Al-Si Alloy Cylinder Liner

In order to improve the wear resistance of Al-Si alloy cylinder liners, surface treatment is usually used. The Al-Si alloy cylinder liner samples were prepared by mechanical grinding and laser finishing. The mechanical grinding samples were carried out by the independent design and development of a grinding machine. The laser finishing samples were laser-heated by a CO2 continuous transverse-flow laser. Both of the two surface treatments could provide the surfaces of protruding silicon particles with round edges to improve the wear resistance. However, in the exposure height of silicon particles with round edges, the study was lacking. The exposure height of silicon particles is important to the tribological properties of the Al-Si alloy cylinder liner, and should be analyzed in detail. The wear tests were completed by a contraposition reciprocating wear test rig under lubrication. It was found that when the silicon particles were exposed on the surface of the Al-Si alloy cylinder liner sample by 1.2 μm, the mechanical grinding samples and laser finishing samples all exhibited minimum friction coefficients and weight losses. This paper confirms that a suitable exposure height of silicon particles would reduce the probability of adhesion wear and abrasive wear of Al-Si alloy cylinder liners and increase the lubrication. It presents an excellent tribological property. However, when the exposure height of silicon particles is too high, the silicon particle is easily prone to plastic deformation or even falls off during the friction process due to the high stress and larger plastic contact index.

Design of an Axial-Field Flux-Modulated Permanent Magnet Machine for Electric Vehicles

Design of an Axial-Field Flux-Modulated Permanent Magnet Machine for Electric Vehicles

The Design of Permanent Magnet Machine With Segmented Poles Based on Nanocomposite Magnets

The Design of Permanent Magnet Machine With Segmented Poles Based on Nanocomposite Magnets

Design and Optimization of High-Efficiency Coreless PCB Stator Axial Flux PM Machines With Minimal Eddy and Circulating Current Losses

Design and Optimization of High-Efficiency Coreless PCB Stator Axial Flux PM Machines With Minimal Eddy and Circulating Current Losses

Design of an aluminum can pressing machine using a lead screw mechanism with a microcontroller-based monitoring system

The beverage industry is experiencing significant growth; however, the handling and management of can waste, particularly aluminum can waste, still rely on manual processes, such as stepping on or striking the can with a tool to reduce its volume. Therefore, there is a need for innovation to design and create a small-scale can pressing machine. The development of this machine employs the Ulrich method, which encompasses the identification of machine requirements, concept selection, and design embodiment. Based on the results obtained using the Ulrich method, design concept 2 was selected. Subsequently, planning, calculations, and analyses were conducted to identify the core and supporting components necessary for constructing the machine. The next stage involved creating detailed drawings of the machine, followed by fabrication and testing. During testing, the can pressing machine demonstrated the ability to exert a maximum load of 20,110.5 N, with a torque of 220.990 Nm and a power output of 0.5 HP (356.95 watts). The PZEM-004T microcontroller was utilized to monitor the operational control of the electric motor. The machine successfully reduced the volume of cans by 56.5%, decreasing their initial height from 345 mm to 150 mm, and it is capable of processing 75 cans per minute.

A quad-cliff mechanism for eco-printing by pounding technique: design, manufacturing, and testing

Indonesia produces many types of textile products, such as clothing and custom fabrics often with unique patterns. To generate the patterns, there are many methods, including eco-printing by pounding process. However, the process, which was later referred to as eco-pounding, requires much time and energy, which can have a negative impact, such as musculoskeletal disorders, on the human body. To address this issue, the present work proposes a machine that can help the process of eco-pounding. Shigley’s method is applied to guide the design process of the machine. The design and manufacturing processes of the eco-pounding machine are presented, in which three machine design models are first introduced and then analyzed for finalization by benchmarking method. Subsequently, a machine model that uses a so-called quad-cliff mechanism is selected for manufacturing and testing. As a result, the proposed machine can achieve the design requirements that were set. Three pounding movements per second can be obtained by the machine, with possible increases by an engine upgrade. This machine can be considered a prototype for a semi-automatic eco-printing process by pounding technique.

Design and Testing of an Offset Straw-Returning Machine for Green Manures in Orchards

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.

Study of the drive mechanism of the working bodies of a roller machine

A design of a roller machine with an improved drive mechanism of working bodies is developed in the article. The roller machine has expanded functionality when performing technological operations of dehydrating moisture-saturated fiber materials. The developed mechanism ensures stable and reliable operation of the drive of working bodies, regardless of the unevenness and variations in the parameters of the processed moisture-saturated fibrous materials, achieving synchronicity of the working body operation. The study aims to expand the functionality of the roller machine, ensure stable and reliable operation of working roller drives regardless of the unevenness and changes in the parameters of the processed moisture-saturated fibrous materials, and ensure synchronicity of the working rollers.

Design and performance analysis of a novel flux-concentrating fault tolerant permanent magnet vernier machine for rim driven thruster

Design and performance analysis of a novel flux-concentrating fault tolerant permanent magnet vernier machine for rim driven thruster

Effect of Anions on Deformation of Gallium-Based Liquid Metal in Solution.

In this study, deformation behaviors of gallium-based liquid metals in acidified cupric sulfate or cupric chloride solutions with varying concentrations of chloride anion or sulfate anion were investigated to explore their potential applications in soft machines and electronics. Gallium-based liquid metals are known for their unique deformability, making them promising materials for various fields. Previous research has shown that deformation of the liquid metal can be achieved in the presence of acidified cupric or ferric salts. However, the specific influence of different anions on the deformation process remains unclear. Our findings indicate that the deformation rate of the liquid metal increases with higher concentrations of chloride ions and decreases with higher concentrations of sulfate ions in the solution. UV-vis absorbance spectra of the solutions were analyzed to identify the formation of hydrated cupric cations. It was observed that increasing the concentration of Cl- ions promotes the formation of cupric-chloro complexes, thereby reducing the concentration of hydrated cupric ions in the solution. Furthermore, the addition of sulfate ions to the solution enhances the ionic strength of the medium, leading to the dissociation of cupric-chloro complexes. Additionally, sulfate ions can form insoluble layers with gallium ions, which impede the deformation of the liquid metal. The deformation rate of the liquid metal was found to be inversely correlated with the concentration of cupric ions in the solution. These results provide valuable insights into the deformable behavior of gallium-based liquid metals and their potential applications in liquid metal-based soft robots. This study highlights the importance of understanding the role of different anions in the deformation process of liquid metals, shedding light on the design and optimization of soft machines and electronics utilizing these materials.

Closed Circuit of 3-Dimensional Polymer Powders

This article describes the most important stages of testing the levels of innovative readiness of a new machine and material construction solutions for closed loops of polymer powders in 3D additive manufacturing. The aim of this study was to indicate the state and directions of development of the technology of geometric recycling of polymer powders in 3D additive manufacturing, the need to control the geometric quality of the powders, and the quality of the design of machines for their processing in a closed circuit. The method was aimed at creating a strategy and verifying the stages of development of a new idea for stabilizing the geometric and dynamic design features of polymer powders for additive manufacturing (3D printing). Connections and relationships of the variable design features of powders, machines and devices with variable postulated states of products and processes allowed for the analysis, knowledge, description and development of variables for stabilizing geometric features of polymer powders in recycling. The results show the possibilities of supporting innovative creativity according to the adopted method, allow for determining the level of compliance of the quality of the products of the technical system, the effectiveness of preparatory processes for recycling and the non-toxicity of the products and processes of the new technology and their closed loop. The goal of developing useful design values, according to an integrated method of analysis, assessment and environmental development, was achieved, including the proposal of design features of razor blade shredders, supported by genetic algorithms, and devices for stabilizing polymer powders in additive manufacturing with recycling.

Designing Ergonomic Standing Chair for Computer Numerical Control Machine Operators using TRIZ

In this research, the working hours and posture of CNC (Computer Numerical Control) machineoperators were investigated to determine the physical workload that they experienced during theirdaily work. Based on our observations, the operator works 8-hour regular shifts or 12-hour longshifts for 5 – 6 days a week. During these shifts, the operators work in front of the CNC machinewhile standing upright without any tools to rest. Preliminary research was conducted to evaluatethese conditions the results show 13 out of 20 CNC machine operators complained about physicalfatigue while working the CNC machines. It can also be concluded that the operators areexperiencing excessive workload based on a workload assessment using the Quick Exposure Check(QEC) method. To solve this problem, a standing chair is designed with ergonomics in mind. Thedimensions of the standing chair are based on the anthropometry of the CNC machine operators,which was never used before. The design process is conducted using the Theory of InventiveProblem Solving (TRIZ) methodology. Need statements from the CNC machine operators anddesign requirements from the stakeholders are converted into design specifications using TRIZmethodology. Parameters are determined to increase the capability of the existing design based onthe design specifications. The result of this research is a standing chair that is suitable for theoperator’s needs. Based on the analysis of the design result and the stress analysis simulation, it canbe concluded a functional standing chair can be ergonomically designed with the TRIZmethodology.

Optimized design of a fault-tolerant 12-slot/10-pole six-phase surface permanent magnet motor with asymmetrical winding configuration for electric vehicles

This paper presents a comprehensive methodology for optimizing the design of a 12-slot/10-pole permanent magnet (PM) motor with a six-phase winding configuration tailored for electric vehicles (EVs). The design aims to enhance motor performance under both healthy and fault conditions. While the single neutral configuration offers superior torque during faults, it also introduces zero sequence currents and additional space harmonics, which can lead to increased torque ripple that is difficult to control. This study addresses these challenges through innovative machine design optimization. The optimization process begins with sizing equations to establish an initial design. K-means clustering techniques are then employed to identify distinct loading points that accurately represent the full EV driving cycle, effectively minimizing computational power requirements. Following this, the Full Range Minimum Loss (FRML) strategy is applied to determine optimal current profiles across these loading points, significantly reducing copper losses. Finally, a multi-objective optimization approach is utilized to minimize torque ripple, enhance average torque, and optimize machine losses. The results demonstrate substantial improvements in torque and reduced ripple, validated through experiments conducted with a 2 kW lab-scale motor. This integrated approach not only ensures a robust and efficient motor design but also enhances fault tolerance, making it well-suited for advanced EV applications.

Reverse Engineering to Design an Ergonomic Bio Briquette Packaging Machine

Briquettes are solids that are produced through the process of compression and pressure applicationand if burned will produce a small amount of smoke. Briquette production is carried out using ahammer mill where the raw material for briquettes is charcoal which is then crushed into charcoalgranules. The packaging process is still done manually using a shovel to fill the 50kg sack and thentake it to the sewing machine. The worker's posture when using a shovel has a Rapid Entire BodyAssessment (REBA) score of 12 so it has a high work risk of musculoskeletal disorders (MSDs) andrequires immediate improvement. The working environment at the company produces pollutants,meaning that there is no capture container for the fall of charcoal grains from the hammer mill. Basedon the existing problems, a redesign of the existing machine is needed. The proposed machine wasdesigned using the Reverse Engineering method because the existing condition already uses themachine then the existing machine is decomposed to find out the components and functions of theexisting machine to find alternative concepts. The ergonomic approach uses REBA and LBA todetermine changes in worker posture and the forces acting in the human spine. The DEM approachwas chosen to find out if the charcoal grains dropped from the hammer mill were successfully capturedand to find out the flow of the charcoal grains. The results of the proposed machine design have agood impact on workers in the packaging process.