Yonghua Song, Jianxia Du and Mingming Zhou
The increasing societal requirement requests higher education institutions to be more responsive to socioeconomic needs and new governmental demands. This study aims to present a…
Abstract
Purpose
The increasing societal requirement requests higher education institutions to be more responsive to socioeconomic needs and new governmental demands. This study aims to present a self-developed multidimensional quality assurance and assessment model for higher education institutions – R.I.S.E model (relevance, impact, significance and excellence) – as a tool for quality assessment in higher education institutions.
Design/methodology/approach
The model was first described at a conceptual level, followed by the examination of its applicability by presenting a case of a university in Macau to substantiate the model with real-life evidence.
Findings
Results showed that the model can be used as an assessment tool to analyze, evaluate and reflect upon the status quo of higher education institutions. Facilitators can use all or part of the model either as a useful baseline to assess performance and prioritize “next steps” or to compare performance across time to determine progress in achieving goals and objectives.
Originality/value
The new model proposed in this study presents multiple perspectives when assessing higher education systems, especially in the transforming stage of a university, to meet upgrading requirements from both the society and the academic community.
Details
Keywords
Yonghua Li, Hao Yin and Qing Xia
This study aims to research the influence of non-probabilistic design variables on interval robust optimization of electric multiple units (EMU) brake module, therefore obtain the…
Abstract
Purpose
This study aims to research the influence of non-probabilistic design variables on interval robust optimization of electric multiple units (EMU) brake module, therefore obtain the reasonable of design variables of the EMU brake module.
Design/methodology/approach
A robust optimization model of the EMU brake module based on interval analysis is established. This model also considers the dimension tolerance of design variables, and it uses symmetric tolerance to describe the uncertainty of design variables. The interval order relation and possibility degree of interval number are employed to deal with the uncertainty of objective function and constraint condition, respectively. On this basis, a multiobjective robust optimization model in view of interval analysis is established and applied to the robust optimization of the EMU brake module.
Findings
Compared with the traditional method and the method proposed in the reference, the maximum stress fluctuation of the EMU brake module structure is smaller after using the method proposed in this paper, which indicates that the robustness of the maximum stress of the structure has been improved. In addition, the weight and strength of the structure meet the design requirements. It shows that this method and model introduced in this research have certain feasibility.
Originality/value
This study is the first attempt to apply the robust optimization model based on interval analysis to the optimization of EMU structure and obtain the optimal solution set that meets the design requirements. Therefore, this study provides an idea for nonprobabilistic robust optimization of the EMU structure.
Details
Keywords
Yonghua Li, Zhe Chen, Maorui Hou and Tao Guo
This study aims to reduce the redundant weight of the anti-roll torsion bar brought by the traditional empirical design and improving its strength and stiffness.
Abstract
Purpose
This study aims to reduce the redundant weight of the anti-roll torsion bar brought by the traditional empirical design and improving its strength and stiffness.
Design/methodology/approach
Based on the finite element approach coupled with the improved beluga whale optimization (IBWO) algorithm, a collaborative optimization method is suggested to optimize the design of the anti-roll torsion bar structure and weight. The dimensions and material properties of the torsion bar were defined as random variables, and the torsion bar's mass and strength were investigated using finite elements. Then, chaotic mapping and differential evolution (DE) operators are introduced to improve the beluga whale optimization (BWO) algorithm and run case studies.
Findings
The findings demonstrate that the IBWO has superior solution set distribution uniformity, convergence speed, solution correctness and stability than the BWO. The IBWO algorithm is used to optimize the anti-roll torsion bar design. The error between the optimization and finite element simulation results was less than 1%. The weight of the optimized anti-roll torsion bar was lessened by 4%, the maximum stress was reduced by 35% and the stiffness was increased by 1.9%.
Originality/value
The study provides a methodological reference for the simulation optimization process of the lateral anti-roll torsion bar.
Details
Keywords
Yonghua Cen and Li Li
Given a product or service, the number of its installed user base has a significant positive effect on the existing users’ loyalty and new users’ conversion. This effect is…
Abstract
Purpose
Given a product or service, the number of its installed user base has a significant positive effect on the existing users’ loyalty and new users’ conversion. This effect is conceptualized as network externalities in economics. Network externalities are supposed to be particularly striking in nowadays online business-to-business (B2B) platforms, but yet the mystery behind their effects on user loyalty to online B2B platforms remains to be delicately unraveled. The purpose of this paper is to discover the factors driving users’ loyalty, especially buyers’ loyalty, to online B2B platforms, by highlighting the impacts of network externalities on loyalty and other mediating factors.
Design/methodology/approach
A conceptual model of buyer loyalty under network externalities is elaborated. The reliability and validity of the instruments of the latent model constructs are assessed by confirmatory factor analysis, and the hypothesized causal relationships among the constructs are tested by structural equation modeling, on 710 valid buyer samples collected from a famous online B2B platform in China.
Findings
The analysis demonstrates that: perceived value, user satisfaction and switching costs are the major predictors of buyer loyalty to online B2B platforms characterized by network externalities; network externalities positively account for buyer loyalty by contributing to perceived value, user satisfaction and switching costs; and direct network externality (measured by perceived network size and perceived external prestige) has a significant effect on indirect network externality (measured by perceived compatibility and perceived complementarity).
Originality/value
The findings allow the authors to conclude meaningful managerial implications for online B2B service providers to build up loyal user bases through improving users’ perceptions of network externalities, switching costs and value.
Details
Keywords
Duo Zhang, Yonghua Li, Gaping Wang, Qing Xia and Hang Zhang
This study aims to propose a more precise method for robust design optimization of mechanical structures with black-box problems, while also considering the efficiency of…
Abstract
Purpose
This study aims to propose a more precise method for robust design optimization of mechanical structures with black-box problems, while also considering the efficiency of uncertainty analysis.
Design/methodology/approach
The method first introduces a dual adaptive chaotic flower pollination algorithm (DACFPA) to overcome the shortcomings of the original flower pollination algorithm (FPA), such as its susceptibility to poor accuracy and convergence efficiency when dealing with complex optimization problems. Furthermore, a DACFPA-Kriging model is developed by optimizing the relevant parameter of Kriging model via DACFPA. Finally, the dual Kriging model is constructed to improve the efficiency of uncertainty analysis, and a robust design optimization method based on DACFPA-Dual-Kriging is proposed.
Findings
The DACFPA outperforms the FPA, particle swarm optimization and gray wolf optimization algorithms in terms of solution accuracy, convergence speed and capacity to avoid local optimal solutions. Additionally, the DACFPA-Kriging model exhibits superior prediction accuracy and robustness contrasted with the original Kriging and FPA-Kriging. The proposed method for robust design optimization based on DACFPA-Dual-Kriging is applied to the motor hanger of the electric multiple units as an engineering case study, and the results confirm a significant reduction in the fluctuation of the maximum equivalent stress.
Originality/value
This study represents the initial attempt to enhance the prediction accuracy of the Kriging model using the improved FPA and to combine the dual Kriging model for uncertainty analysis, providing an idea for the robust optimization design of mechanical structure with black-box problem.
Details
Keywords
This study aims to examine the cross-institutional variation in university greenness and analyze its underlying dynamics.
Abstract
Purpose
This study aims to examine the cross-institutional variation in university greenness and analyze its underlying dynamics.
Design/methodology/approach
This study constructs a University Greenness Index (UGI) and conducts multivariate regression.
Findings
This study finds variation within two dimensions; in the vertical dimension, top-tier universities have significantly higher UGIs than tier-2 universities, and in the horizontal dimension, agricultural and forest, engineering and technology and generalist universities have significantly higher UGIs than other specialist universities. The dynamics underlying the greenness variation lies in different universities’ motivations and resources, which are associated with China’s higher education administrative system, especially the mechanism by which funding is allocated.
Research limitations/implications
The Internet-search-based greenness index has some inherent limitations. First, there exists a gap between green information expression and real green achievement. Second, this research may be difficult to apply to other countries, because of the specific characteristics of China’s higher education system.
Practical implications
Based on the empirical results, two policy implications can be generated. First, for the problem of the vertical dimension variation, related institutional transformation should be launched to promote university greenness. Second, for the problem of the horizon dimension variation, specialist universities can take advantage of an interdisciplinary approach to promote greenness.
Originality/value
This research helps scholars and administrators to better understand the progress being made and the achievements realized with regard to green university initiatives in China.
Details
Keywords
Pengpeng Zhi, Yonghua Li, Bingzhi Chen, Meng Li and Guannan Liu
In a structural optimization design-based single-level response surface, the number of optimal variables is too much, which not only increases the number of experiment times, but…
Abstract
Purpose
In a structural optimization design-based single-level response surface, the number of optimal variables is too much, which not only increases the number of experiment times, but also reduces the fitting accuracy of the response surface. In addition, the uncertainty of the optimal variables and their boundary conditions makes the optimal solution difficult to obtain. The purpose of this paper is to propose a method of fuzzy optimization design-based multi-level response surface to deal with the problem.
Design/methodology/approach
The main optimal variables are determined by Monte Carlo simulation, and are classified into four levels according to their sensitivity. The linear membership function and the optimal level cut set method are applied to deal with the uncertainties of optimal variables and their boundary conditions, as well as the non-fuzzy processing is carried out. Based on this, the response surface function of the first-level design variables is established based on the design of experiments. A combinatorial optimization algorithm is developed to compute the optimal solution of the response surface function and bring the optimal solution into the calculation of the next level response surface, and so on. The objective value of the fourth-level response surface is an optimal solution under the optimal design variables combination.
Findings
The results show that the proposed method is superior to the traditional method in computational efficiency and accuracy, and improves 50.7 and 5.3 percent, respectively.
Originality/value
Most of the previous work on optimization was based on single-level response surface and single optimization algorithm, without considering the uncertainty of design variables. There are very few studies which discuss the optimization efficiency and accuracy of multiple design variables. This research illustrates the importance of uncertainty factors and hierarchical surrogate models for multi-variable optimization design.
Details
Keywords
Jitai Han, Yanan Ge, Yuxin Mao and Meiping Wu
The purpose of this paper is to mainly focus on the relationship between the scanning strategy and surface quality. Surface quality, including surface roughness and flatness, is…
Abstract
Purpose
The purpose of this paper is to mainly focus on the relationship between the scanning strategy and surface quality. Surface quality, including surface roughness and flatness, is important for printed parts. So this paper optimizes the surface quality by changing the scanning strategy.
Design/methodology/approach
This paper is based on the phenomenon after the printed parts. A clear trend can be seen that the surface roughness on the side face shows a clear zigzag shape, so an optimized scanning strategy is used. Surface roughness in measured in macrostructure first by Mitutoyo and the flatness is measured by Hexagon Metrocogy. After that, microstructure on the side face is seen by RTEC to explain this phenomenon.
Findings
The surface quality on the side face shows a significant optimize by changing the scanning strategy. The surface quality on the positive face has some optimization to some degree.
Originality/value
This paper determines the relationship between the surface roughness on the side face and the scanning strategy. Few studies focus on the surface roughness, especially on the side face. Some studies try to optimize the surface roughness on the positive face. However, researchers always neglect the surface roughness on the side face. 2. This paper measures not only the surface roughness, but also the flatness. Surface roughness has a significant impact on the surface quality. However, it still has some limitations. Flatness is also measured to make this paper more representative. 3. This paper explains why scanning strategy can affect the surface quality. These images explain the research better and not just at the theoretical level.
Details
Keywords
Mojtaba Izadi, Aidin Farzaneh, Mazher Mohammed, Ian Gibson and Bernard Rolfe
This paper aims to present a comprehensive review of the laser engineered net shaping (LENS) process in an attempt to provide the reader with a deep understanding of the…
Abstract
Purpose
This paper aims to present a comprehensive review of the laser engineered net shaping (LENS) process in an attempt to provide the reader with a deep understanding of the controllable and fixed build parameters of metallic parts. The authors discuss the effect and interplay between process parameters, including: laser power, scan speed and powder feed rate. Further, the authors show the interplay between process parameters is pivotal in achieving the desired microstructure, macrostructure, geometrical accuracy and mechanical properties.
Design/methodology/approach
In this manuscript, the authors review current research examining the process inputs and their influences on the final product when manufacturing with the LENS process. The authors also discuss how these parameters relate to important build aspects such as melt-pool dimensions, the volume of porosity and geometry accuracy.
Findings
The authors conclude that studies have greatly enriched the understanding of the LENS build process, however, much studies remains to be done. Importantly, the authors reveal that to date there are a number of detailed theoretical models that predict the end properties of deposition, however, much more study is necessary to allow for reasonable prediction of the build process for standard industrial parts, based on the synchronistic behavior of the input parameters.
Originality/value
This paper intends to raise questions about the possible research areas that could potentially promote the effectiveness of this LENS technology.
Details
Keywords
Abdullah AlFaify, James Hughes and Keith Ridgway
The pulsed-laser powder bed fusion (PBF) process is an additive manufacturing technology that uses a laser with pulsed beam to melt metal powder. In this case, stainless steel…
Abstract
Purpose
The pulsed-laser powder bed fusion (PBF) process is an additive manufacturing technology that uses a laser with pulsed beam to melt metal powder. In this case, stainless steel SS316L alloy is used to produce complex components. To produce components with acceptable mechanical performance requires a comprehensive understanding of process parameters and their interactions. This study aims to understand the influence of process parameters on reducing porosity and increasing part density.
Design/methodology/approach
The response surface method (RSM) is used to investigate the impact of changing critical parameters on the density of parts manufactured. Parameters considered include: point distance, exposure time, hatching distance and layer thickness. Part density was used to identify the most statistically significant parameters, before each parameter was analysed individually.
Findings
A clear correlation between the number and shape of pores and the process parameters was identified. Point distance, exposure time and layer thickness were found to significantly affect part density. The interaction between these parameters also critically affected the development of porosity. Finally, a regression model was developed and verified experimentally and used to accurately predict part density.
Research limitations/implications
The study considered a range of selected parameters relevant to the SS316L alloy. These parameters need to be modified for other alloys according to their physical properties.
Originality/value
This study is believed to be the first systematic attempt to use RSM for the design of experiments (DOE) to investigate the effect of process parameters of the pulsed-laser PBF process on the density of the SS316L alloy components.