Xiaojing Liu, Tiru Arthanari and Yangyan Shi
This paper examines the establishment of supply chain robustness against corruption by utilizing risk interactions.
Abstract
Purpose
This paper examines the establishment of supply chain robustness against corruption by utilizing risk interactions.
Design/methodology/approach
Based on empirical results from the New Zealand dairy industry, a system dynamics model is established to explore the underlying relationships among variables.
Findings
The results show that although certain supply chain risks seem unrelated to corruption, their mitigation would help mitigate the impact of corruption due to risk interactions; and mitigation of some of the risks is more effective in mitigating the impact of corruption. Leverage risks have been defined and identified in this research, which expands the extant knowledge in reducing the impact of corruption on supply chains.
Originality/value
The research illustrates how the impact of corruption can be studied in an integrated way with dairy supply chain SD analysis. It is a pioneering study to mitigate the impact of corruption on supply chains from supply chain robustness.
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Xiaojing Liu, Tiru Arthanari and Yangyan Shi
To improve robustness of a dairy supply chain (SC) against corruption, the purpose of this paper is to propose a systemic model of a corruption impacted dairy SC, exposing…
Abstract
Purpose
To improve robustness of a dairy supply chain (SC) against corruption, the purpose of this paper is to propose a systemic model of a corruption impacted dairy SC, exposing relationships among SC operations, risks and the impact of corruption.
Design/methodology/approach
Cases from the dairy industry in New Zealand (NZ) are used for thematic analysis of interview data collected from participants at senior levels of NZ dairy firms. Based on these and other inputs from literature, a systemic model is built subsequently.
Findings
Mitigating certain risks can significantly alleviate the impact of corruption, an external factor, on supply chain performance (SCP). The causal loop diagram (CLD) developed here brings out the modifying effect of corruption on dairy risks and SCP.
Practical implications
The illustration of the CLD helps business managers better understand the interactions among risk variables and explains the systemic reasons for SC vulnerability.
Originality/value
This is the first paper to construct a holistic system to comprehensively reveal the interactions of supply chain risks (SCRs) and the impact of corruption. Also, by utilizing SCR interactions, this study indicates a pathway to mitigate the negative effects of corruption through improving dairy SC robustness.
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Jia-Neng Cheng, Yan Liu, Hongwei Che, Guoping Yan, Xinghai Liu, Xiaojing Liu, Xiaoyan Wang and Bo Bi
The purpose of this investigation was to study a transparent coating based on organic silicone resins prepared by the hydrolysis and condensation of methyltriethoxysilane and…
Abstract
Purpose
The purpose of this investigation was to study a transparent coating based on organic silicone resins prepared by the hydrolysis and condensation of methyltriethoxysilane and tetraethoxysilane.
Design/methodology/approach
The coating film was characterized by IR, UV, thermal gravity analysis, scanning electron microscope and an automatic contact angle meter. Some properties of the coating film, such as adhesion, impact resistance and wear-resistance also were evaluated.
Findings
These uniform, clear and smooth coating films possessed the high transparent and light transmittance, high density, high hydrophobicity, good adhesion, hardness and anti-corrosion.
Originality/value
The coating may be considered as a protective film for the surfaces of the metals and plastics.
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Xiaojing Wang, Hao Liu and Guojia Man
Aiming at the cavitations and noise problem of hydraulic cone valve and based on the radial force analysis of the valve core, the radial deviation of the spool is considered to…
Abstract
Purpose
Aiming at the cavitations and noise problem of hydraulic cone valve and based on the radial force analysis of the valve core, the radial deviation of the spool is considered to obtain the changing rules of cavitations and noise.
Design/methodology/approach
The solid model of the internal flow field of cone valve is established. The mesh models are divided using ICEM-CFD software. The numerical simulation of the liquid-gas two-phase flow is performed on the cavitation and noise of the flow field inside the cone valve based on FLUENT software. The visible experimental platform for cavitation and noise of hydraulic cone valve is built. According to the contrast of the experimental results, the correctness of the simulation results is verified.
Findings
The results show that the radial deviation causes the position of the cavitation accumulates in the valve cavity on the side of the upper cone. In addition, the strength of the cavitation changes slowly with the half cone angle of 45°, and the noise level is the smallest. Furthermore, appropriately increasing the opening degree within a reasonable range can effectively suppress cavitation and reduce the noise level.
Originality/value
The cavitation can be suppressed and the noise level can be reduced by means of changing the three factors, which lays the foundation for the design and theoretical research of the cone valve.
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Xiaojing Zheng and Xiaoxian Wang
This study aims to examine the effect of board gender diversity on corporate litigation in China’s listed firms. The key questions this study addresses are: what are the effect of…
Abstract
Purpose
This study aims to examine the effect of board gender diversity on corporate litigation in China’s listed firms. The key questions this study addresses are: what are the effect of board gender diversity on corporate litigation in terms of both the frequency and severity of consequence, is there any heterogeneous effects of the relationships across firm performance?
Design/methodology/approach
A sample consists of 25,668 firm-year observations from over 3,340 firms is examined using logistic regression analysis and negative binomial regression analysis. The authors also use event study method and ordinary least square (OLS) regression to explore female directors’ effects on reducing the negative consequences of litigation. The logistic regression and OLS regression are reestimated with interaction terms when examining the firm performance heterogeneity.
Findings
The authors document that firms with greater female representation on their boards experience fewer and less severe corporate litigations. Moreover, in high-performing firms, board gender diversity plays a more potent role in reducing the frequency and consequences of corporate litigation than low-performing firms.
Originality/value
This study is among the first to examine the relationship between board gender diversity and the comprehensive corporate litigations under Chinese context. It sheds new light on China’s boardroom dynamics, offering valuable empirical implication to Chinese corporate policymakers on the role of female directors.
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Zhenghai Liu, Hui Tang, Dong Liu, Jingji Zhao, Xinyue Zhu, Yu Du, Xiaojing Tian and Ming Cong
In response to the complex external structure of high-precision aviation plugs, which makes it difficult to search outside the hole and adjust inside the hole during automated…
Abstract
Purpose
In response to the complex external structure of high-precision aviation plugs, which makes it difficult to search outside the hole and adjust inside the hole during automated assembly. This paper aims to propose an assembly framework that combines multi-agent search and variable parameter compliant control to solve this problem.
Design/methodology/approach
First, a multi-agent search strategy (MAS) based on Gaussian Mixture Model and Deep Q-Network was proposed to optimize displacement direction and actions, thereby improving search speed and success rate. Then, a variable parameter admittance control method (RL-VPA) based on dual delay depth deterministic policy gradient (TD3) was proposed, which dynamically optimized the internal parameters of the admittance controller and adopted state space discretization to improve convergence speed and assembly efficiency.
Findings
Compared to spiral search and single-agent search, the average search success rate has improved by approximately 10% and 6.6%. Compared to fixed admittance control and other RL-based methods, the average assembly success rate has increased by approximately 38.6%, 22% and 8.6%. Compared with the training results of the model without state discretization, it was found that state discretization helps the model converge quickly. To verify the generalization ability of the assembly framework, experiments were conducted on three different pin counts of aviation plugs, the assembly success rate reached 86.7%, all of which showed good assembly results. Finally, combining state space discretization to reduce the impact of environmental noise, improve training effectiveness and convergence speed.
Originality/value
MAS has been proposed to optimize displacement direction and action, improving search speed and success rate. RL-VPA is designed to dynamically optimize the internal parameters of the admittance controller, enhancing the robustness and generalization ability of the model. Additionally, state space discretization is combined to improve training effectiveness and convergence speed.
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Minghao Wang, Ming Cong, Yu Du, Dong Liu and Xiaojing Tian
The purpose of this study is to solve the problem of an unknown initial position in a multi-robot raster map fusion. The method includes two-dimensional (2D) raster maps and…
Abstract
Purpose
The purpose of this study is to solve the problem of an unknown initial position in a multi-robot raster map fusion. The method includes two-dimensional (2D) raster maps and three-dimensional (3D) point cloud maps.
Design/methodology/approach
A fusion method using multiple algorithms was proposed. For 2D raster maps, this method uses accelerated robust feature detection to extract feature points of multi-raster maps, and then feature points are matched using a two-step algorithm of minimum Euclidean distance and adjacent feature relation. Finally, the random sample consensus algorithm was used for redundant feature fusion. On the basis of 2D raster map fusion, the method of coordinate alignment is used for 3D point cloud map fusion.
Findings
To verify the effectiveness of the algorithm, the segmentation mapping method (2D raster map) and the actual robot mapping method (2D raster map and 3D point cloud map) were used for experimental verification. The experiments demonstrated the stability and reliability of the proposed algorithm.
Originality/value
This algorithm uses a new visual method with coordinate alignment to process the raster map, which can effectively solve the problem of the demand for the initial relative position of robots in traditional methods and be more adaptable to the fusion of 3D maps. In addition, the original data of the map can come from different types of robots, which greatly improves the universality of the algorithm.
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Yu Du, Jipan Jian, Zhiming Zhu, Dehua Pan, Dong Liu and Xiaojing Tian
Aiming at the problems of weak generalization of robot imitation learning methods and higher accuracy requirements of low-level detectors, this study aims to propose an imitation…
Abstract
Purpose
Aiming at the problems of weak generalization of robot imitation learning methods and higher accuracy requirements of low-level detectors, this study aims to propose an imitation learning method based on structural grammar.
Design/methodology/approach
The paper proposes a hybrid training model based on artificial immune algorithm and the Baum–Welch algorithm to extract the action information of the demonstration activity to form the {action-object} sequence and extract the symbol description of the scene to form the symbol primitives sequence. Then, probabilistic context-free grammar is used to characterize and manipulate these sequences to form a grammar space. Minimum description length criteria are used to evaluate the quality of the grammar in the grammar space, and the improved beam search algorithm is used to find the optimal grammar.
Findings
It is found that the obtained general structure can parse the symbol primitive sequence containing noise and obtain the correct sequence, thereby guiding the robot to perform more complex and higher-order demonstration tasks.
Practical implications
Using this strategy, the robot completes the fourth-order Hanoi tower task has been verified.
Originality/value
An imitation learning method for robots based on structural grammar is first proposed. The experimental results show that the method has strong generalization ability and good anti-interference performance.
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Xiaojing Feng, Bin Cui, Yaxiong Liu, Lianggang Li, Xiaojun Shi and Xiaodong Zhang
The purpose of this paper is to solve the problems of poor mechanical properties, high surface roughness and waste support materials of thin-walled parts fabricated by…
Abstract
Purpose
The purpose of this paper is to solve the problems of poor mechanical properties, high surface roughness and waste support materials of thin-walled parts fabricated by flat-layered additive manufacturing process.
Design/methodology/approach
This paper proposes a curved-layered material extrusion modeling process with a five-axis motion mechanism. This process has advantages of the platform rotating, non-support printing and three-dimensional printing path. First, the authors present a curved-layered algorithm by offsetting the bottom surface into a series of conformal surfaces and a toolpath generation algorithm based on the geodesic distance field in each conformal surface. Second, they introduce a parallel five-axis printing machine consisting of a printing head fixed on a delta-type manipulator and a rotary platform on a spherical parallel machine.
Findings
Mechanical experiments show the failure force of the five-axis printed samples is 153% higher than that of the three-axis printed samples. Forming experiments show that the surface roughness significantly decreases from 42.09 to 18.31 µm, and in addition, the material consumption reduces by 42.90%. These data indicate the curved-layered algorithm and five-axis motion mechanism in this paper could effectively improve mechanical properties and the surface roughness of thin-walled parts, and realize non-support printing. These methods also have reference value for other additive manufacturing processes.
Originality/value
Previous researchers mostly focus on printing simple shapes such as arch or “T”-like shape. In contrast, this study sets out to explore the algorithm and benefits of modeling thin-walled parts by a five-axis machine. Several validated models would allow comparability in five-axis printing.
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Minghao Wang, Ming Cong, Dong Liu, Yu Du, Xiaojing Tian and Bing Li
The purpose of this study is to designed a robot odometry based on three dimensional (3D) laser point cloud data, inertial measurement unit (IMU) data and real-time kinematic…
Abstract
Purpose
The purpose of this study is to designed a robot odometry based on three dimensional (3D) laser point cloud data, inertial measurement unit (IMU) data and real-time kinematic (RTK) data in underground spatial features and gravity fluctuations environment. This method improves the mapping accuracy in two types of underground space: multi-layer space and large-scale scenarios.
Design/methodology/approach
An IMU–Laser–RTK fusion mapping algorithm based on Iterative Kalman Filter was proposed, and the observation equation and Jacobian matrix were derived. Aiming at the problem of inaccurate gravity estimation, the optimization of gravity is transformed into the optimization of SO(3), which avoids the problem of gravity over-parameterization.
Findings
Compared with the optimization method, the computational cost is reduced. Without relying on the wheel speed odometer, the robot synchronization localization and 3D environment modeling for multi-layer space are realized. The performance of the proposed algorithm is tested and compared in two types of underground space, and the robustness and accuracy in multi-layer space and large-scale scenarios are verified. The results show that the root mean square error of the proposed algorithm is 0.061 m, which achieves higher accuracy than other algorithms.
Originality/value
Based on the problem of large loop and low feature scale, this algorithm can better complete the map loop and self-positioning, and its root mean square error is more than double compared with other methods. The method proposed in this paper can better complete the autonomous positioning of the robot in the underground space with hierarchical feature degradation, and at the same time, an accurate 3D map can be constructed for subsequent research.