Guodong Sa, Haodong Bai, Zhenyu Liu, Xiaojian Liu and Jianrong Tan
The assembly simulation in tolerance analysis is one of the most important steps for the tolerance design of mechanical products. However, most assembly simulation methods are…
Abstract
Purpose
The assembly simulation in tolerance analysis is one of the most important steps for the tolerance design of mechanical products. However, most assembly simulation methods are based on the rigid body assumption, and those assembly simulation methods considering deformation have a poor efficiency. This paper aims to propose a novel efficient and precise tolerance analysis method based on stable contact to improve the efficiency and reliability of assembly deformation simulation.
Design/methodology/approach
The proposed method comprehensively considers the initial rigid assembly state, the assembly deformation and the stability examination of assembly simulation to improve the reliability of tolerance analysis results. The assembly deformation of mating surfaces was first calculated based on the boundary element method with optimal initial assembly state, then the stability of assembly simulation results was assessed by the density-based spatial clustering of applications with noise algorithm to improve the reliability of tolerance analysis. Finally, combining the small displacement torsor theory, the tolerance scheme was statistically analyzed based on sufficient samples.
Findings
A case study of a guide rail model demonstrated the efficiency and effectiveness of the proposed method.
Research limitations/implications
The present study only considered the form error when generating the skin model shape, and the waviness and the roughness of the matching surface were not considered.
Originality/value
To the best of the authors’ knowledge, the proposed method is original in the assembly simulation considering stable contact, which can effectively ensure the reliability of the assembly simulation while taking into account the computational efficiency.
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Xiaoyi He, Liping Li, Xiaojian Liu, Yongsheng Wu, Shujiang Mei and Zhen Zhang
Hand, foot and mouth disease (HFMD) is a common infectious disease in infants and children. HFMD has caused millions of cases and a large epidemic worldwide. A number of studies…
Abstract
Purpose
Hand, foot and mouth disease (HFMD) is a common infectious disease in infants and children. HFMD has caused millions of cases and a large epidemic worldwide. A number of studies have shown that the incidence of HFMD is closely related to various factors such as meteorological factors, environmental air pollution factors and socio-economic factors. However, there are few studies that systematically consider the impact of various factors on the incidence of HFMD. The paper aims to discuss these issues.
Design/methodology/approach
This study used grey correlation analysis and principal component analysis (PCA) method to systematically analyse the impact of meteorological factors, health resource factors, socio-economic factors and environmental air pollution factors on the incidence of HFMD in Shenzhen.
Findings
The incidence of HFMD in Shenzhen was affected by multiple factors. Grey correlation analysis found eight influencing factors which are as follows: volume of industrial waste gas emission; the days of air quality equal to or above grade; the volume of industrial nitrogen oxide emission; precipitation; the mean air temperature; the gross domestic product; the expenditure for medical and health care; and the gross domestic product per capita. PCA found that the gross domestic product, the volume of industrial soot emission, the relative humidity, and the days of air quality equal to or above grade have a higher load value.
Originality/value
This study is the one of the first studies that apply the grey correlation analysis to analyse the influencing factors of HFMD in the English literature, which to some extent fills up the blank in this field.
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Hongshuai Guo, Shuyou Zhang, Nan Zhang, Xiaojian Liu and Guodong Yi
The step effect and support structure generated by the manufacturing process of fused deposition molding parts increase the consumables cost and decrease the printing quality…
Abstract
Purpose
The step effect and support structure generated by the manufacturing process of fused deposition molding parts increase the consumables cost and decrease the printing quality. Multiorientation printing helps improve the surface quality of parts and reduce support, but path interference exists between the printing layer and the layers printed. The purpose of this study is to design printing paths between different submodels to avoid interference when build orientation changed.
Design/methodology/approach
Considering support constraint, build orientation sequence is designed for submodels decomposed by model topology. The minimum printing angle between printing layers is analyzed. Initial path through the oriented bounding box is planned and slice interference relationship is then detected according to the projection topology mapping. Based on the relationship matrix of multiorientation slice, feasible path is calculated by directed graph (DG). Final printing path is determined under support constraint and checked by minimum printing angle. The simulation model of the robotic arm is established to verify the accessibility of printing path under the constraint of support and slice.
Findings
The proposed method can reduce support structure, decrease volume error and effectively solve the interference problem of the printing path for multiorientation slice.
Originality/value
The method based on projection topology mapping greatly improves the efficiency of interference detection. A feasible path calculated through DGs ensures the effectiveness of the printing path with the constraint of support and slice.
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Guanxiong Wang, Xiaojian Hu and Ting Wang
By introducing the mass customization service mode into the cloud logistics environment, this paper studies the joint optimization of service provider selection and customer order…
Abstract
Purpose
By introducing the mass customization service mode into the cloud logistics environment, this paper studies the joint optimization of service provider selection and customer order decoupling point (CODP) positioning based on the mass customization service mode to provide customers with more diversified and personalized service content with lower total logistics service cost.
Design/methodology/approach
This paper addresses the general process of service composition optimization based on the mass customization mode in a cloud logistics service environment and constructs a joint decision model for service provider selection and CODP positioning. In the model, the two objective functions of minimum service cost and most satisfactory delivery time are considered, and the Pareto optimal solution of the model is obtained via the NSGA-II algorithm. Then, a numerical case is used to verify the superiority of the service composition scheme based on the mass customization mode over the general scheme and to verify the significant impact of the scale effect coefficient on the optimal CODP location.
Findings
(1) Under the cloud logistics mode, the implementation of the logistics service mode based on mass customization can not only reduce the total cost of logistics services by means of the scale effect of massive orders on the cloud platform but also make more efficient use of a large number of logistics service providers gathered on the cloud platform to provide customers with more customized and diversified service content. (2) The scale effect coefficient directly affects the total cost of logistics services and significantly affects the location of the CODP. Therefore, before implementing the mass customization logistics service mode, the most reasonable clustering of orders on the cloud logistics platform is very important for the follow-up service combination.
Originality/value
The originality of this paper includes two aspects. One is to introduce the mass customization mode in the cloud logistics service environment for the first time and summarize the operation process of implementing the mass customization mode in the cloud logistics environment. Second, in order to solve the joint decision optimization model of provider selection and CODP positioning, this paper designs a method for solving a mixed-integer nonlinear programming model using a multi-layer coding genetic algorithm.
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Jun Zhang, Xiaojian Ou, Lin Li, Qianqian Chen, Zifan Zhang, Ting Huo, Xiaoyu Lin, Fangfang Niu, Shengyuan Zhao, Fang We, Hui Li, Chunli Liu, Zhenbin Chen, Sujun Lu, Peng Zhang and Jinian Zhu
A novel grafted temperature-responsive ReO4− Imprinted composite membranes (Re-ICMs) was successfully prepared by using polyvinylidene fluoride (PVDF) resin membranes as…
Abstract
Purpose
A novel grafted temperature-responsive ReO4− Imprinted composite membranes (Re-ICMs) was successfully prepared by using polyvinylidene fluoride (PVDF) resin membranes as substrates, this study aimed to separate and purify ReO effectively.
Design/methodology/approach
Re-ICMs were synthesized by PVDF resin membranes as the substrate, acrylic acid (AA), acrylamide (AM), ethylene glycol dimethacrylate (EGDMA) were functional monomers. The morphology and structure of Re-ICMs were characterized by scanning electron microscope and Fourier transform infrared spectroscopy.
Findings
The maximum adsorption capacity toward ReO4− was 0.1,163 mmol/g and the separation decree had relation to MnO4− was 19.3. The optimal operation conditions were studied detailedly and the results as follows: the molar ratios of AA, AM, EGDMA, ascorbic acid, NH4ReO4, were 0.8, 0.96, 0.02, 0.003 and 0.006. The optimal time and temperature were 20 h and 40°C, respectively. The Langmuir and pseudo-second-order models were fit these adsorption characteristics well.
Practical implications
Rhenium (Re) is mainly used to chemical petroleum and make superalloys for jet engine parts. This study was representing a technology in separate and purify of Re, which provided a method for the development of the petroleum and aviation industry.
Originality/value
This contribution provided a novel method to separate ReO4− from MnO4−. The maximum adsorption capacity was 0.1163 mmol/g at 35°C and the adsorption equilibrium time was within 2 h. Meanwhile, the adsorption selectivity rate ReO4−/MnO4− was 19.3 and the desorption rate was 78.3%. Controlling the adsorption experiment at 35°C and desorption experiment at 25°C in aqueous solution, it could remain 61.3% of the initial adsorption capacity with the adsorption selectivity rate of 13.3 by 10 adsorption/desorption cycles, a slight decrease, varied from 78.3% to 65.3%, in desorption rate was observed.
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Gang Yao, Xiaojian Hu, Liangcheng Xu and Zhening Wu
Social media data from financial websites contain information related to enterprise credit risk. Mining valuable new features in social media data helps to improve prediction…
Abstract
Purpose
Social media data from financial websites contain information related to enterprise credit risk. Mining valuable new features in social media data helps to improve prediction performance. This paper proposes a credit risk prediction framework that integrates social media information to improve listed enterprise credit risk prediction in the supply chain.
Design/methodology/approach
The prediction framework includes four stages. First, social media information is obtained through web crawler technology. Second, text sentiment in social media information is mined through natural language processing. Third, text sentiment features are constructed. Finally, the new features are integrated with traditional features as input for models for credit risk prediction. This paper takes Chinese pharmaceutical enterprises as an example to test the prediction framework and obtain relevant management enlightenment.
Findings
The prediction framework can improve enterprise credit risk prediction performance. The prediction performance of text sentiment features in social media data is better than that of most traditional features. The time-weighted text sentiment feature has the best prediction performance in mining social media information.
Practical implications
The prediction framework is helpful for the credit decision-making of credit departments and the policy regulation of regulatory departments and is conducive to the sustainable development of enterprises.
Originality/value
The prediction framework can effectively mine social media information and obtain an excellent prediction effect of listed enterprise credit risk in the supply chain.
Details
Keywords
Ammar Yasir, Xiaojian Hu, Murat Aktan, Pablo Farías and Abdul Rauf
Contemporary changes have occurred in country-level policies and tourists’ intentions in recent years. The role of maintaining a country’s image is trendy in crisis control but…
Abstract
Purpose
Contemporary changes have occurred in country-level policies and tourists’ intentions in recent years. The role of maintaining a country’s image is trendy in crisis control but has not yet been discussed in domestic tourism research. Extending the Stimulus Organism Response model, this study aims to focus on “trustable WOM creation” in China. In addition, it aimed to discover how behavioral changes encourage domestic tourism intention (DTI).
Design/methodology/approach
This study explored the mediating role of DTI and the moderating role of maintenance of country image (MCI) for trustable word of mouth (WOM) creation. Using the snowball sampling technique, a structural equation modeling analysis (Smart PLS-4) was employed to analyze the data of 487 Chinese tourists.
Findings
Findings confirm that behavioral changes positively encourage domestic tourism and discourage international tourism, with significant negative moderation by MCI. MCI has an insignificant positive moderating effect between government-media trust and DTI. Furthermore, DTI positively and directly affects the creation of trustable WOM. In addition, it had a 20% mediation effect (VAF%) between behavioral changes and WOM creation, higher than the rejected mediation effect (12%), in the causal relationship between government-media trust and WOM creation.
Practical implications
WOM creation varies from different behavioral changes, but findings suggest that government-media trust and DTI influenced it significantly. Based on the study findings, the government and media can enhance domestic tourism by maintaining the country’s image. These findings both encourage and control the recovery of tourism.
Originality/value
This study provides a theoretical explanation for tourists' behavioral changes during the pandemic. Moreover, it shows that despite avoiding international tourism due to behavioral changes and government-media trust, MCI moderation with the mediation effect of DTI can create trustable WOM. To the best of the authors’ knowledge, this is the first study to theoretically promote tourism through DTI-induced psychology as a mediator and an organism affect prevailing among Chinese tourists.
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Shi Xu, Hongyu Gao, Fukang Yang, Ziyue Zhang, Shuolei Wang, Xiaojian Jiang and Yubing Dong
The purpose of this study is to improve the mechanical properties, thermal insulation properties and flame retardant properties of polyethylene terephthalate (PET), the organic…
Abstract
Purpose
The purpose of this study is to improve the mechanical properties, thermal insulation properties and flame retardant properties of polyethylene terephthalate (PET), the organic montmorillonite (OMMT)/SiO2 aerogel/PET composites and fibers were prepared, and the effects of the OMMT/SiO2 aerogel on the structure, thermal conductivity and flame retardance of the OMMT/SiO2 aerogel/PET composites and their fibers were systematically investigated.
Design/methodology/approach
The OMMT/SiO2 aerogel/PET composites and fibers were prepared by in-situ polymerization and melt spinning using SiO2 aerogel as thermal insulation filler and OMMT (DK2) as comodified filler.
Findings
The experimental results showed that OMMT improved the crystallization properties of PET. Compared with the crystallinity of SiO2 aerogel/PET composites (34.8%), SiO2 aerogel/PET composites and their fibers reached 45.1% and 49.2%, respectively. The breaking strength of the OMMT/SiO2 aerogel/PET composite fibers were gradually increased with the OMMT content. When the content of OMMT was 0.8 wt.%, the fracture strength of the composite fibers reached 4.40 cN/dtex, which was 54% higher than that of the SiO2 aerogel/PET fiber. In addition, the thermal insulation properties of the composites and their fibers were improved by addition of fillers, and at the same time reached the flame retardant level. The thermal conductivity of the 0.8 wt.% OMMT/SiO2 aerogel/PET composites was 101.78 mW/(m·K), which was 49.3% and 58.8% lower than that of the SiO2 aerogel/PET composites and the pure PET, respectively. The thermal conductivity of the fiber fabrics woven from the 0.8 wt.% OMMT/SiO2 aerogel/PET composites was 28.18 mW/(m·K), which was 29.0% and 44.6% lower than that of the SiO2 aerogel/PET composite fiber fabrics and PET fiber fabrics. The flame retardancy of the composites was improved, with an limiting oxygen index value of 29.2% for the 0.8 wt.% OMMT/SiO2 aerogel/PET composites, which was 4.1% higher compared to the SiO2 aerogel/PET composites, and achieved the flame retardant level.
Research limitations/implications
The SiO2 aerogel/PET composites and their fibers have good mechanical properties, flame retardant properties and thermal insulation properties, exhibited good potential for application in the field of thermal insulation, such as warm clothing. Nowadays, as the energy crisis is becoming more and more serious, it is very important to improve the thermal insulation properties of PET to reduce energy losses and mitigate the energy crisis.
Originality/value
In this study, PET based composites and their fibers with excellent mechanical properties, thermal insulation properties and flame retardant property were obtained by using three-dimensional network porous silica aerogel with low density and low thermal conductivity as the thermal insulation functional filler and two-dimensional layered OMMT as the synergetic modified filler.
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Yan Gao, Qiubo Li, Wei Wu, Qiwei Wang, Yizhe Su, Junxi Zhang, Deyuan Lin and Xiaojian Xia
The purpose of this paper is to study the effect of current-carrying condition on the electrochemical process and atmospheric corrosion behavior of the commercial aluminum alloys.
Abstract
Purpose
The purpose of this paper is to study the effect of current-carrying condition on the electrochemical process and atmospheric corrosion behavior of the commercial aluminum alloys.
Design/methodology/approach
Potentiodynamic polarization tests were performed to study the electrochemical process of the aluminum alloys. Salt spray tests and weight loss tests were carried out to study the atmospheric corrosion behavior. The corrosion morphology of the alloys was observed, and the products were analyzed.
Findings
The corrosion process of four aluminum alloys was accelerated in the current-carrying condition. Moreover, the acceleration effect on A2024 and A7075 was much stronger than that on A1050 and A5052. The main factors would be the differences in microstructure and corrosion resistance between these alloys. As the carried current increased, the corrosion rate and corrosion current density of the aluminum alloys gradually increased, with the protection of the corrosion product film decreasing linearly.
Originality/value
This is a recent study on the corrosion behavior of conductors under current-carrying condition, which truly understands the corrosion status of power grid materials. Relevant results provide support for the corrosion protection and safe service of aluminum alloy in power systems.
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Hongyu Gao, Shi Xu, Fukang Yang, Ziyue Zhang, Shuolei Wang, Xiaojian Jiang and Yubing Dong
Crystallization kinetics is a key factor that controls the crystallization process of polymers and influences the crystallinity and morphology of polymers. This study aims to…
Abstract
Purpose
Crystallization kinetics is a key factor that controls the crystallization process of polymers and influences the crystallinity and morphology of polymers. This study aims to explore the effects of functional filler SiO2 aerogel and co-modified filler organic montmorillonite (OMMT) on the crystallization process of polyester polyethylene terephthalate (PET). In this study, the nonisothermal crystallization kinetics of OMMT/SiO2 aerogel/PET composites were studied by Jeziorny method.
Design/methodology/approach
The catalyst (Sb2O3), OMMT and SiO2 aerogel were uniformly dispersed in ethylene glycol (EG). Then, the mixture and terephthalic acid (PTA) were put into a semicontinuous polyester synthesis reactor, and the SiO2 aerogel/PET composites were prepared by esterification and polycondensation.
Findings
Non-isothermal kinetic results showed that the high cooling rate hindered the movement of the molecular chain of the composites and made the crystallization peak move toward the low-temperature direction. With the increase of crystallization temperature (Tc), the melt crystallization rate decreases, but the cold crystallization rate increases. The introduction of OMMT and SiO2 aerogel condensation affected the nucleation and growth mode of crystals, lengthened the time with a relative crystallinity of 50% (t1/2) and decreased the crystallization rate. OMMT improved the crystallinity and Avrami index of the composites.
Research limitations/implications
Effects of thermal insulation functional filler SiO2 aerogel and co-modified filler OMMT on the crystallization process of PET were studied by non-isothermal crystallization kinetics, and the effects of SiO2 aerogel and OMMT on the nucleation mechanism of PET were clarified, which provided a theoretical reference for the preparation and performance optimization of PET matrix composites.
Originality/value
In this study, the OMMT/SiO2 aerogel/PET composites were prepared by in-situ polymerization, the crystallinity of PET matrix composites was improved, and the effects of OMMT and SiO2 aerogel on the crystallization process of PET were clarified.