Search results

The purpose of this study is to set up a dynamic model of material extrusion (ME) additive manufacturing plates for the prediction of their dynamic behavior (i.e. dynamic inherent characteristic, resonant response and damping) and also carry out its experimental validation and sensitivity analysis.

Based on the classical laminated plate theory, a dynamic model is established using the orthogonal polynomials method, taking into account the effect of lamination and orthogonal anisotropy. The dynamic inherent characteristics of the ME plate are worked out by Ritz method. The frequency-domain dynamic equations are then derived to solve the plates’ resonant responses, with which the damping ratio is figured out according to the half-power bandwidth method. Subsequently, a series of experimental tests are performed on the ME samples to obtain the measured data.

It is shown that the predictions and measurements in terms of dynamic behavior are in good agreement, validating the accuracy of the developed model. In addition, sensitivity analysis shows that increasing the elastic modulus or Poisson’s ratio will increase the corresponding natural frequency of the ME plate but decrease the resonant response. When the density is increased, both the natural frequency and resonant response will be decreased.

Future research can be focused on using the proposed model to investigate the effect of processing parameters on the ME parts’ dynamic behavior.

This study shows theoretical basis and technical insight into improving the forming quality and reliability of the ME parts.

A novel reliable dynamic model is set up to provide theoretical basis and principle to reveal the physical phenomena and mechanism of ME parts.

This paper aims to effectively achieve endmembers and relative abundances simultaneously in hyperspectral image unmixing yield. Hyperspectral unmixing, which is an important step before image classification and recognition, is a challenging issue because of the limited resolution of image sensors and the complex diversity of nature. Unmixing can be performed using different methods, such as blind source separation and semi-supervised spectral unmixing. However, these methods have disadvantages such as inaccurate results or the need for the spectral library to be known a priori.

This paper proposes a novel method for hyperspectral unmixing called fuzzy c-means unmixing, which achieves endmembers and relative abundance through repeated iteration analysis at the same time.

Experimental results demonstrate that the proposed method can effectively implement hyperspectral unmixing with high accuracy.

The proposed method present an effective framework for the challenging field of hyperspectral image unmixing.

This paper aims to provide a comprehensive analysis of the state of the art in energy efficiency for autonomous mobile robots (AMRs), focusing on energy sources, consumption models, energy-efficient locomotion, hardware energy consumption, optimization in path planning and scheduling methods, and to suggest future research directions.

The systematic literature review (SLR) identified 244 papers for analysis. Research articles published from 2010 onwards were searched in databases including Google Scholar, ScienceDirect and Scopus using keywords and search criteria related to energy and power management in various robotic systems.

The review highlights the following key findings: batteries are the primary energy source for AMRs, with advances in battery management systems enhancing efficiency; hybrid models offer superior accuracy and robustness; locomotion contributes over 50% of a mobile robot’s total energy consumption, emphasizing the need for optimized control methods; factors such as the center of mass impact AMR energy consumption; path planning algorithms and scheduling methods are essential for energy optimization, with algorithm choice depending on specific requirements and constraints.

The review concentrates on wheeled robots, excluding walking ones. Future work should improve consumption models, explore optimization methods, examine artificial intelligence/machine learning roles and assess energy efficiency trade-offs.

This paper provides a comprehensive analysis of energy efficiency in AMRs, highlighting the key findings from the SLR and suggests future research directions for further advancements in this field.

The purpose of this paper is to conduct a comprehensive experimental study to achieve optimal surface roughness of aluminum rolled with freshly ground rollers of two high rolling mills.

Various rolling oils and processing conditions are applied in the rolling process. Resultant surface roughness is measured with a profilometer; and surface topography of aluminum after rolling is observed under scanning electron microscope. In order to examine the oil film thickness (the most critical factor in rolling process), a planimeter is used to measure the area of oil patch resulting from a precisely controlled oil droplet, which in turn allows calculation of outlet oil film thickness as an approximation to inlet oil film thickness in the deformation region.

The experimental results indicate that two major factors have dominant impacts on aluminum's surface roughness in the rolling lubrication process: reduction of roller; and viscosity of lubrication oil. Based upon analysis of the experimental data, optimal roller reduction is found to be within range (23%, 30%) and optimal oil viscosity should be chosen, such that the ratio between inlet oil film thickness in the deformation region and the combined surface roughness is around 1.

According to the authors' observations, the above parameter choices generally assure excellent surface quality of aluminum after rolling.

This study aims to investigate the influence of geometry of bush-pin pair from a perspective of optimal lubrication through a thermal elastohydrodynamic lubrication model for finite line contact.

A constitutive equation: Ree-Eyring fluid is used in the calculations. The real chain sizes, i.e. equivalent radius of curvature, bush length, length of the rounded corner area and rounded corner radius, are jointed investigated. Moreover, the effects of the length of the rounded corner area and the radius of rounded corner are investigated.

It is found that the current standard of the chain might not consider the importance of lubrication, and the lubrication state can be improved effectively by choosing an optimal radius of rounded corner and the length of the corner area.

By optimally selecting sizes, the occurrence of high pressure, high temperature rise and near zero film thickness at the ends of bush, especially under heavier load, can be effectively avoided.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-01-2020-0031/

The coupling impact of hybrid uncertain errors on the machine precision is complex, as a result of which the designing method with multiple independent error sources under uncertainties remains a challenge. For the purpose of precision improvement, this paper focuses on the robot design and aims to present an assembly precision design method based on uncertain hybrid tolerance allocation (UHTA), to improve the positioning precision of the mechanized robot, as well as realize high precision positioning within the workspace.

The fundamentals of the parallel mechanism are introduced first to implement concept design of a 3-R(4S) &3-SS parallel robot. The kinematic modeling of the robot is carried out, and the performance indexes of the robot are calculated via Jacobian matrix, on the basis of which, the 3D spatial overall workspace can be quantified and visualized, under the constraints of limited rod, to avoid the singular position. The error of the robot is described, and a probabilistic error model is hereby developed to classify the hybrid error sensitivity of each independent uncertain error source by Monte Carlo stochastic method. Most innovatively, a methodology called UHTA is proposed to optimize the robot precision, and the tolerance allocation approach is conducted to reduce the overall error amplitude and improve the robotized positioning precision, on the premise of not increasing assembly cost.

The proposed approach is validated by digital simulation of medical puncture robot. The experiment highlights the mathematical findings that the horizontal plane positioning error of the parallel robotic mechanism can be effectively reduced after using UHTA, and the average precision can be improved by up to 39.54%.

The originality lies in UHTA-based precision design method for parallel robots. The proposed method has widely expanding application scenarios in industrial robots, biomedical robots and other assembly automation fields.

The purpose of this paper is to study the interaction of main marine organisms on localized corrosion of 316L stainless steel in the Dalian Sea area.

The steel plate was immersed in the Dalian Sea area for nine months to observe the biofouling and localized corrosion. The local potential distribution on the steel plate covered by marine organisms was measured. The local electrochemical measurements were performed to facilitate understanding the interfacial status under different biofouling conditions. The local surface morphologies and corrosion products were characterized.

The localized corrosion of stainless steel is mainly induced by the attachment of barnacles on the steel. The mussels have no influence on the localized corrosion. The cover of sea squirts could mitigate the localized corrosion induced by barnacles. Both crevice corrosion and pitting corrosion were found beneath the barnacle without the covering of sea squirts. The pitting damage was more serious than the crevice corrosion in the Dalian Sea area. The probing of sulfur element indicates that the potential growth of sulfate-reducing bacteria at barnacle center.

The above findings revealed that the interaction of marine organisms has significant influences on the localized corrosion of stainless steel. The influences of macro-fouling and micro-fouling on localized corrosion are discussed.

The influence of the number and arrangement of bolts on the tensile properties of bolted composite laminates was studied in the present study.

Based on the finite element model, the stiffness degradation method is used to simulate the damage evolution process for the failure of bolted composite laminates. Using ABAQUS finite element software combined with material failure criteria, the numerical calculation of the connection strength and failure mode of bolted composite laminates was carried out.

The results of the study show that the tensile strength of the composite laminates connected by three bolts is higher than that of the laminates connected by two bolts. And the arrangement of different bolts has a great influence on the failure strength of bolted laminates.

Bolted connection of composite laminates is a common problem in engineering practice. The effect of bolt arrangement and number on the strength of composite laminates is studied in this manuscript.

In the high-speed trains (HSTs) production process, assembly sequence planning (ASP) problems is an extremely core issue. ASP problems influence the economic cost, amount of workers and the working time in the assembly process, seriously. In the design process of HSTs, the assembly sequence is usually given by experience, and the correctness of the assembly sequence is difficult to guarantee by experience and low effectiveness. The ASP based on improved discrete particle swarm optimization (IDPSO) algorithm was proposed to address these issues.

In view of the local convergence problem with basic DPSO in ASP, this paper presents an IDPSO, in which a chosen strategy of global optimal particle is introduced in, to solve the ASP problems in the assembly process of HSTs operation panel. The geometric feasibility, the assembly stability, and the number of assembly orientation changes of the assembly are chosen to be the optimization objective. Furthermore, the influences of the population size, the weight coefficient, and the learning factors to the stability and efficiency of IDPSO algorithm were discussed.

The results show that the IDPSO algorithm can obtain the global optimum efficiently, which is proved to be a more useful method for solving ASP problems than basic DPSO. The IDPSO approach could reduce the working time and economic cost of ASP problems in HSTs significantly.

The method may save the economic cost, reduce the amount of workers and save the time in the assembly process of HSTs. And also may change the method of ASP in design and manufacturing process, and make the production process in HSTs more efficiently.

A chosen strategy of global optimal particle is presented, which can overcome the local convergence problem with basic DPSO for solving ASP problems.

In this paper, the authors explore the consequences of showrooming and price matching strategy to combat showrooming under the consideration that brick-and-mortar (BM) stores and online retailers hold different costs.

The authors use a duopoly model to analyze the impact of showrooming behavior on competition between a BM store and an online retailer with different types of customers and different costs. Then, they consider the price matching strategy that a BM store could employ to combat showrooming and explore the effect of such a strategy.

Showrooming behavior is detrimental to the profit of the BM store, and the online retailer suffers a loss of their profit unless the relative cost of the BM store is high and only part of the customers exhibit showrooming behavior. As the fraction of customers who seek price matching increases, profits of both the BM store and the online retailer initially decrease and then may increase, even if there is no showrooming.

Unlike existing studies that ignore different costs between online and offline retailers, the authors set different costs between the BM store and the online retailer to consider the effects of showrooming and price matching strategy.