Chuangui Yang, Junwen Wang, Liang Mi, Xingbao Liu, Yangqiu Xia, Yilei Li, Shaoxing Ma and Qiang Teng
This paper aims to propose a four-point measurement model for directly measuring the pose (i.e. position and orientation) of industrial robot and reducing its calculating error…
Abstract
Purpose
This paper aims to propose a four-point measurement model for directly measuring the pose (i.e. position and orientation) of industrial robot and reducing its calculating error and measurement uncertainty.
Design/methodology/approach
A four-point measurement model is proposed for directly measuring poses of industrial robots. First, this model consists of a position measurement model and an orientation model gotten by the position of spherically mounted reflector (SMR). Second, an influence factor analysis, simulated by Monte Carlo simulation, is performed to investigate the influence of certain factors on the accuracy and uncertainty. Third, comparisons with the common method are carried out to verify the advantage of this model. Finally, a test is carried out for evaluating the repeatability of five poses of an industrial robot.
Findings
In this paper, results show that the proposed model is better than the three-SMRs model in measurement accuracy, measurement uncertainty and computational efficiency. Moreover, both measurement accuracy and measurement uncertainty can be improved by using the proposed influence laws of its key parameters on the proposed model.
Originality/value
The proposed model can measure poses of industrial robots directly, accurately and effectively. Additionally, influence laws of key factors on the accuracy and uncertainty of the proposed model are given to provide some guidelines for improving the performance of the proposed model.
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Yang Chuangui, Liu Xingbao, Yue Xiaobin, Mi Liang, Wang Junwen, Xia Yangqiu, Yu Hailian and Chen Heng
This paper aims to solve the nonlinear problem in the uncertainty evaluation of the measurement of the positioning repeatability (RP) of industrial robots and provide guidance to…
Abstract
Purpose
This paper aims to solve the nonlinear problem in the uncertainty evaluation of the measurement of the positioning repeatability (RP) of industrial robots and provide guidance to restrict the uncertainty of measurement of RP (uRP).
Design/methodology/approach
Firstly, some uncertain sources existing in the measurement procedure of RP are identified. Secondly, the probability distribution function (PDF) of every source is established on the basis of its measurements. Some spatial combined normal distributions are adopted. Then, a method, based on Monte Carlo method (MCM) and established measurement model, is developed for the estimation of uRP. Thirdly, some tests are developed for the identification and validation of the selected PDFs of uncertain sources. Afterwards, the proposed method is applied for the evaluation and validation of the uRP. Finally, influence analyses of some key factors are proposed for the quantification of their relative contributions to uRP.
Findings
Results show that the proposed method can reasonably and objectively estimate the uRP of the selected industrial robot, and changes of the industrial robots’ position and the laser trackers measurement are correlated. Additionally, the uRP of the selected industrial robot can be restricted by using the results of its key factors on uRP.
Originality/value
This paper proposes the spatial combined normal distribution to model the uncertainty of the repeatability of the laser tracker and industrial robot. Meanwhile, the proposed method and influence analyses can be used in estimating and restricting the uRP and thus useful in determining whether the RP of a tested industrial robot meets its requirements.
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Zirui Zeng, Junwen Xu, Shiwei Zhou, Yufeng Zhao and Yansong Shi
To achieve sustainable development in shipping, accurately identifying the impact of artificial intelligence on shipping carbon emissions and predicting these emissions is of…
Abstract
Purpose
To achieve sustainable development in shipping, accurately identifying the impact of artificial intelligence on shipping carbon emissions and predicting these emissions is of utmost importance.
Design/methodology/approach
A multivariable discrete grey prediction model (WFTDGM) based on weakening buffering operator is established. Furthermore, the optimal nonlinear parameters are determined by Grey Wolf optimization algorithm to improve the prediction performance, enhancing the model’s predictive performance. Subsequently, global data on artificial intelligence and shipping carbon emissions are employed to validate the effectiveness of our new model and chosen algorithm.
Findings
To demonstrate the applicability and robustness of the new model in predicting marine shipping carbon emissions, the new model is used to forecast global marine shipping carbon emissions. Additionally, a comparative analysis is conducted with five other models. The empirical findings indicate that the WFTDGM (1, N) model outperforms other comparative models in overall efficacy, with MAPE for both the training and test sets being less than 4%, specifically at 0.299% and 3.489% respectively. Furthermore, the out-of-sample forecasting results suggest an upward trajectory in global shipping carbon emissions over the subsequent four years. Currently, the application of artificial intelligence in mitigating shipping-related carbon emissions has not achieved the desired inhibitory impact.
Practical implications
This research not only deepens understanding of the mechanisms through which artificial intelligence influences shipping carbon emissions but also provides a scientific basis for developing effective emission reduction strategies in the shipping industry, thereby contributing significantly to green shipping and global carbon reduction efforts.
Originality/value
The multi-variable discrete grey prediction model developed in this paper effectively mitigates abnormal fluctuations in time series, serving as a valuable reference for promoting global green and low-carbon transitions and sustainable economic development. Furthermore, based on the findings of this paper, a grey prediction model with even higher predictive performance can be constructed by integrating it with other algorithms.
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Yu Fu, Junwen Zhao, Xujia Li and Yiwen Peng
This paper aims to prepare high corrosion-resistant chromium-free zinc-aluminum (Zn–Al) coatings reinforced with multi-walled carbon nanotubes (MWCNTs) and nano-ZnO particle…
Abstract
Purpose
This paper aims to prepare high corrosion-resistant chromium-free zinc-aluminum (Zn–Al) coatings reinforced with multi-walled carbon nanotubes (MWCNTs) and nano-ZnO particle composites.
Design/methodology/approach
The morphology, composition and corrosion resistance of the coatings were analyzed by electrochemical tests, water contact angle tests, immersion tests, scanning electron microscopy/energy dispersive spectrometer and X-ray diffraction.
Findings
The composite coating with 0.3% MWCNTs and 0.5% nano-ZnO particles demonstrated both high shielding performance and cathodic protection performance, which was attributed to the porosity filling of MWCNTs and nano-ZnO particles together with the electrical connection of MWCNTs between the zinc and aluminum powders.
Originality/value
This work laid an experimental foundation for the preparation and corrosion mechanism of high corrosion-resistant chromium-free Zn–Al coating reinforced with MWCNTs and nano-ZnO particles.
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Yingxiang Zhao, Junde Guo, Xiaoni Yan, Shan Du, Min Gong, Biao Sun, Junwen Shi and Wen Deng
The purpose of this paper is to investigate the friction and wear mechanisms in copper-based self-lubricating composites with MoS2 as the lubricating phase, which provides a…
Abstract
Purpose
The purpose of this paper is to investigate the friction and wear mechanisms in copper-based self-lubricating composites with MoS2 as the lubricating phase, which provides a theoretical basis for subsequent research on high-performance copper-based self-lubricating materials.
Design/methodology/approach
Friction tests were performed at a speed of 100 r/min, a load of 10 N, a friction radius of 5 mm and a sliding speed of 30 min. Friction experiments were carried out at RT-500°C. The phase composition of the samples was characterized by X-ray diffraction of Cu Ka radiation, and the microstructure, morphology and elemental distribution were characterized by scanning electron microscopy and energy dispersive spectroscopy. Reactants and valences formed during the wear process were analyzed by X-ray photoelectron spectroscopy.
Findings
The addition of MoS2 can effectively improve friction-reducing and anti-wear action of the matrix, which is beneficial to form a lubricating film on the sliding track. After analyzing different changing mechanism of the sliding tracks, the oxides and sulfides of MoS2, MoO2, Cu2O, CuO and Ni(OH)2 were detected to form a synergetic lubricating film on the sliding track, which is responsible for the excellent tribological properties from room to elevated temperature.
Research limitations/implications
For self-lubrication Cu–Sn–Ni–MoS2 material in engineering field, there are still few available references on high-temperature application.
Practical implications
This paper provides a theoretical basis for the following research on copper-based self-lubricating materials with high performance.
Originality/value
With this statement, the authors hereby certify that the manuscript is the results of their own effort and ability. They have indicated all quotes, citations and references. Furthermore, the authors have not submitted any essay, paper or thesis with similar content elsewhere. No conflict of interest exits in the submission of this manuscript.
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Jun Yan Cui, Hakim Epea Silochi, Robert Wieser1, Shi Junwen, Habachi Bilal, Samuel Ngoho and Blaise Ravelo
The purpose of this paper is to develop a familiarity analysis of resistive-capacitive (RC) network active circuit operating with unfamiliar low-pass (LP) type negative group…
Abstract
Purpose
The purpose of this paper is to develop a familiarity analysis of resistive-capacitive (RC) network active circuit operating with unfamiliar low-pass (LP) type negative group delay (NGD) behavior. The design method of NGD circuit is validated by simulation with commercial tool and experimental measurement.
Design/methodology/approach
The present research work methodology is structured in three main parts. The familiarity theory of RC-network LP-NGD circuit is developed. The LP-NGD circuit parameters are expressed in function of the targeted time-advance. Then, the feasibility study is based on the theory, simulation and measurement result comparisons.
Findings
The RC-network based LP-NGD proof of concept is validated with −1 and −0.5 ms targeted time-advances after design, simulation, test and characterized. The LP-NGD circuit unity gain prototype presents NGD cut-off frequencies of about 269 and 569 Hz for the targeted time-advances, −1 and −0.5 ms, respectively. Bi-exponential and arbitrary waveform signals were tested to verify the targeted time-advance.
Research limitations/implications
The performance of the unfamiliar LP-NGD topology developed in the present study is limited by the parasitic elements of constituting lumped components.
Practical implications
The NGD circuit enables to naturally reduce the undesired delay effect from the electronic and communication systems. The NGD circuit can be exploited to reduce the delay induced by electronic devices and system.
Social implications
As social impacts of the NGD circuit application, the NGD function is one of prominent solutions to improve the technology performances of future electronic device in term of communication aspect and the transportation system.
Originality/value
The originality of the paper concerns the theoretical approach of the RC-network parameters in function of the targeted time-advance and the input signal bandwidth. In addition, the experimental results are also particularly original.
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Abstract
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Alhan Farhanah Abd Rahim, Aida Azrenda Mustakim, Nurul Syuhadah Mohd Razali, Ainorkhilah Mahmood, Rosfariza Radzali, Ahmad Sabirin Zoolfakar and Yusnita Mohd Ali
Porous silicon (PS) was successfully fabricated using an alternating current photo-assisted electrochemical etching (ACPEC) technique. This study aims to compare the effect of…
Abstract
Purpose
Porous silicon (PS) was successfully fabricated using an alternating current photo-assisted electrochemical etching (ACPEC) technique. This study aims to compare the effect of different crystal orientation of Si n(100) and n(111) on the structural and optical characteristics of the PS.
Design/methodology/approach
PS was fabricated using ACPEC etching with a current density of J = 10 mA/cm2 and etching time of 30 min. The PS samples denoted by PS100 and PS111 were etched using HF-based solution under the illumination of an incandescent white light.
Findings
FESEM images showed that the porous structure of PS100 was a uniform circular shape with higher density and porosity than PS111. In addition, the AFM indicated that the surface roughness of porous n(100) was less than porous n(111). Raman spectra of the PS samples showed a stronger peak with FWHM of 4.211 cm−1 and redshift of 1.093 cm−1. High resolution X-ray diffraction revealed cubic Si phases in the PS samples with tensile strain for porous n(100) and compressive strain for porous n(111). Photoluminescence observation of porous n(100) and porous n(111) displayed significant visible emissions at 651.97 nm (Eg = 190eV) and 640.89 nm (Eg = 1.93 eV) which was because of the nano-structure size of silicon through the quantum confinement effect. The size of Si nanostructures was approximately 8 nm from a quantized state effective mass theory.
Originality/value
The work presented crystal orientation dependence of Si n(100) and n(111) for the formation of uniform and denser PS using new ACPEC technique for potential visible optoelectronic application. The ACPEC technique has effectively formed good structural and optical characteristics of PS.
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Octaviano Rojas Luiz, Fernando Bernardi de Souza, João Victor Rojas Luiz and Daniel Jugend
The purpose of this paper is to analyze the state of the art in Critical Chain Project Management (CCPM), outlining the CCPM literature to date, in an effort to guide future…
Abstract
Purpose
The purpose of this paper is to analyze the state of the art in Critical Chain Project Management (CCPM), outlining the CCPM literature to date, in an effort to guide future studies.
Design/methodology/approach
The paper is based on a bibliometric analysis using Scopus and Web of Science databases. The authors identified the principal journals, articles and authors regarding the research theme, as well as the authors elaborated co-citation and co-occurrence network maps to support the analysis.
Findings
The authors described five co-citation clusters: Fundamentals of Critical Chain, Scheduling, Operations Research, Multi-project and Network, and General Project Management. The most frequently occurring keywords were: “project management,” “critical chain,” “scheduling” and “theory of constraints.” Observing the distribution, the expression “project management” occupied a central position, connecting two other clusters, represented by the keywords “scheduling” and “critical chain.” The authors proposed an evolutive framework for the CCPM state of the art in three stages, according to the most frequent topics identified: Conceptual, Deepening of Applications and Methodological Maturity.
Originality/value
This research adopts a systematic approach based on bibliometric tools, which allows a more rigorous organization of the literature. Co-citation and keyword co-occurrence maps provide evidence of how the main themes in CCPM relate. Besides, the presented historical framework allows new research in CCPM to be directed to the most recent topics of interest that have gaps to be explored.