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1 – 10 of 36Xiaoli Kong, Bo Zhou, Jixiao Wang and Wenping Li
The purpose of this paper is to study the engineering application of diamond like carbon (DLC) coatings on the surfaces of piston pins and bucket tappets for a 2.0 L supercharged…
Abstract
Purpose
The purpose of this paper is to study the engineering application of diamond like carbon (DLC) coatings on the surfaces of piston pins and bucket tappets for a 2.0 L supercharged gasoline engine. The friction loss and durability of DLC-coated components were investigated.
Design/methodology/approach
The tribological characteristics were examined under oil-lubricated conditions in a CETR UMT reciprocating tribometer. In a motored engine test rig, friction loss torque test was performed to estimate the improvement in fuel economy. Fired engine durability bench tests of typical duration of 450 h were completed to access the durability and wear resistance of DLC coating. Before and after durability tests, coated and uncoated components were measured on the sliding surface by a profilometer technique.
Findings
Friction and wear test results show that DLC coating has low friction coefficient and reduces the wear rates by almost ten times compared to those of uncoated surfaces. Friction loss measurements indicate that DLC-coated tappets can reduce valve train friction loss by 29 per cent, and DLC-coated piston pins can reduce piston group friction by 11 per cent. Based on fired engine durability bench tests, it is evidenced that none of the coated tappets and pins show any noticeable peeling or delamination. Wear profiles analysis results indicate that DLC-coated engine components give rise to a substantial reduction in wear.
Originality/value
DLC coating applied onto the working surface of piston pin and bucket tappet can effectively reduce the friction loss of gasoline engine. DLC coating exhibits sufficient durability and improves friction and wear performance.
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Wenping Wang, Jiaoli Wang, Xinhuan Huang and Qiuying Shen
The purpose of this paper is to attempt to calculate the trust degree between two enterprises in an industrial network using grey correlation degree algorithm for exploring…
Abstract
Purpose
The purpose of this paper is to attempt to calculate the trust degree between two enterprises in an industrial network using grey correlation degree algorithm for exploring characteristics of community structure and evolution rules of cluster cooperation networks in axle‐type and satellite‐type clusters.
Design/methodology/approach
Starting from analysis of trust formation mechanism of inter‐enterprise in industrial networks, adjacency of inter‐enterprise relationship, their information acquisition ability, their influence power in network and their past interaction experience are chosen as influencing factors of the trust between two enterprises. Grey correlation degree algorithm was chosen to calculate the trust degree between two enterprises in an industrial network. According to the rules of dynamic adjustment of trust degree originated from thoughts of the prisoners' dilemma model, computer simulation is applied to explore characteristics of community structure and evolution rules of cluster cooperation network in axle‐type and satellite‐type clusters.
Findings
With the dynamic adjustment of enterprises' trust degree, the network density of axle‐type and satellite‐type cluster networks was decreasing as the cluster scale was enlarging, and eventually tended to be stable; community structure was emerged in axle‐type and satellite‐type industrial clusters as the cluster scale was enlarging; community characteristics were obviously stronger in axle‐type cluster networks than in satellite‐type; communities were overlapped in axle‐type cluster networks, that is, bridge nodes emerged between communities.
Originality/value
This paper is the first to apply the grey correlation degree algorithm to calculate the trust degree between two enterprises in cluster networks for designing the rules of dynamic adjustment of trust degree.
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Hong Liu, Qishan Zhang and Wenping Wang
The purpose of this paper is to realize a location‐routing network optimization in reverse logistics (RL) using grey systems theory for uncertain information.
Abstract
Purpose
The purpose of this paper is to realize a location‐routing network optimization in reverse logistics (RL) using grey systems theory for uncertain information.
Design/methodology/approach
There is much uncertain information in network optimization and location‐routing problem (LRP) of RL, including fuzzy information, stochastic information and grey information, etc. Fuzzy information and stochastic information have been studied in logistics, however grey information of RL has not been covered. In the LRP of RL, grey recycling demands are taken into account. Then, a mathematics model with grey recycling demands has been constructed, and it can be transformed into grey chance‐constrained programming (GCCP) model, grey simulation and a proposed hybrid particle swarm optimization (PSO) are combined to resolve it. An example is also computed in the last part of the paper.
Findings
The results are convincing: not only that grey system theory can be used to deal with grey uncertain information about location‐routing problem of RL, but GCCP, grey simulation and PSO can be combined to resolve the grey model.
Practical implications
The method exposed in the paper can be used to deal with location‐routing problem with grey recycling information in RL, and network optimization result with grey uncertain factor could be helpful for logistics efficiency and practicability.
Originality/value
The paper succeeds in realising both a constructed model about location‐routing of RL with grey recycling demands and a solution algorithm about grey mathematics model by using one of the newest developed theories: grey systems theory.
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Hong Liu, Wenping Wang and Qishan Zhang
The purpose of this paper is to realize a multi‐objective location‐routing network optimization in reverse logistics using particle swarm optimization based on grey relational…
Abstract
Purpose
The purpose of this paper is to realize a multi‐objective location‐routing network optimization in reverse logistics using particle swarm optimization based on grey relational analysis with entropy weight.
Design/methodology/approach
Real world network design problems are often characterized by multi‐objective in reverse logistics. This has recently been considered as an additional objective for facility location problem or vehicle routing problem in reverse logistics network design. Both of them are shown to be NP‐hard. Hence, location‐routing problem (LRP) with multi‐objective is more complicated integrated problem, and it is NP‐hard too. Due to the fact that NP‐hard model cannot be solved directly, grey relational analysis and entropy weight were added to particle swarm optimization to decision among the objectives. Then, a mathematics model about multi‐objective LRP of reverse logistics has been constructed, and a proposed hybrid particle swarm optimization with grey relational analysis and entropy weight has been developed to resolve it. An example is also computed in the last part of the paper.
Findings
The results are convincing: not only that particle swarm optimization and grey relational analysis can be used to resolve multi‐objective location‐routing model, but also that entropy and grey relational analysis can be combined to decide weights of objectives.
Practical implications
The method exposed in the paper can be used to deal with multi‐objective LRP in reverse logistics, and multi‐objective network optimization result could be helpful for logistics efficiency and practicability.
Originality/value
The paper succeeds in realising both a constructed multi‐objective model about location‐routing of reverse logistics and a multi‐objective solution algorithm about particle swarm optimization and future stage by using one of the newest developed theories: grey relational analysis.
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Wenping Wang, Xinhuan Huang and Jie Xie
The paper attempts to analyze the network structure of value activity in manufacturing clusters, propose the model of value creation of cluster's value activity network, and…
Abstract
Purpose
The paper attempts to analyze the network structure of value activity in manufacturing clusters, propose the model of value creation of cluster's value activity network, and explore the inner mechanism and optimization strategies of value creation in manufacturing clusters from the perspective of cluster's value activity network.
Design/methodology/approach
This paper applies a genetic algorithm to optimally search in the target space, and repeatedly exerts genetic operation (select, cross, variation) on the population to explore the optimal configuration strategy between value creation activity and resource utilization. It also analyzes the relation between object function of value creation and relative parameters.
Findings
The total value created by value activity network was impacted by the degree of effective configuration between all kinds of resources and value activities; the total value created by value activity network is positively related to activity units' elasticity coefficient of value creation of human resource, material resources and relations resource, and is negatively correlated to cost coefficient of human resource, material resources and relations resource; when the cooperative relations between activity units create positive relationship profit, the total value created by value activity network increases with the increase of cooperative relations between activity units.
Practical implications
Enterprises in clusters should reasonably configure and incorporate the resource among value activities through adding, deleting or reconfiguring activities, which makes the value activities network create maximum value; enterprises can transform the type of activity units to increase elasticity coefficient of value creation of human resources, such as transforming production activities into the high value‐added activities; enterprises can optimally incorporate the technical, material resources and human resources among activities to increase value creation elastic coefficient of material resources; enterprises can decrease cost coefficient by maintaining the stability of long‐term cooperation with the suppliers and strengthening the cultivation of talents; enterprises can increase profits from relation resource or reduce cost coefficient of relationship by updating activities, building trust mechanism and communication mechanisms and establishing long‐term cooperation relationship to improve value creation activities.
Originality/value
This paper proposes the model of value creation from the perspective of cluster's value activity network, and applies a genetic algorithm to explore the optimal configuration strategies between value creation activity and resource utilization.
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Xinhuan Huang and Wenping Wang
This paper aims to construct evaluation index system of industrial economy-ecology-coordinated development based on “driving-force-pressure-state-impact-response” conceptual…
Abstract
Purpose
This paper aims to construct evaluation index system of industrial economy-ecology-coordinated development based on “driving-force-pressure-state-impact-response” conceptual model. Grey target theory is introduced to evaluate industrial economy-ecology-coordinated development level and identify its key influencing factors. On that basis, the countermeasures are proposed to improve industrial economy-ecology-coordinated development in China.
Design/methodology/approach
Bull's-eye degree of grey target theory is introduced to evaluate industrial economy-ecology-coordinated development level of 31 provinces, municipalities and autonomous regions in China. The contribution degree of influence factors is analyzed by contribution degree theory.
Findings
The results show that first, the overall level of industrial economy-ecology-coordinated development in China is not high, there is a big gap of coordinated development level between provinces, municipalities and autonomous region, and there is still a large room to improve the status quo. Second, the major factors affecting industrial economy-ecology-coordinated development are gross industrial output value (GIOV) share of investment completed in the treatment of industrial pollution, common industrial solid wastes produced per GIOV, sulphur dioxide emission per GIOV, energy consumption per 10,000 yuan of gross regional product.
Originality/value
This paper constructs evaluation index system of industrial economy-ecology-coordinated development and applies grey target theory to evaluate industrial economy-ecology-coordinated development level and identify its key influencing factors.
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In this paper, the organism model for knowledge‐based enterprise is proposed. A dynamic capacity grey set is defined and analyzed based on the definition of the growth and…
Abstract
In this paper, the organism model for knowledge‐based enterprise is proposed. A dynamic capacity grey set is defined and analyzed based on the definition of the growth and development for knowledge‐based enterprise organism. The structure of the capacity whiten core, a subset of the capacity grey set, is optimized for different periods of the organism's life cycle. The organism grey topological structure model of knowledge‐based enterprise is described to possess the essential capacity grey set.
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Xuan Wang, Tao Huang, Wenping Zhang, Qingfeng Zeng and Xin Sun
This study aims to investigate the role of information normalization in online healthcare consultation, a typical complex human-to-human communication requiring both effectiveness…
Abstract
Purpose
This study aims to investigate the role of information normalization in online healthcare consultation, a typical complex human-to-human communication requiring both effectiveness and efficiency. The globalization and digitization trend calls for high-quality information, and normalization is considered an effective method for improving information quality. Meanwhile, some researchers argued that excessive normalization (standardized answers) may be perceived as impersonal, repetitive, and cold. Thus, it is not appreciated for human-to-human communication, for instance, when patients are anxious about their health condition (e.g. with high-risk disease) in online healthcare consultation. Therefore, the role of information normalization in human communication is worthy to be explored.
Design/methodology/approach
Data were collected from one of the largest online healthcare consultation platforms (Dxy.com). This study expanded the existing information quality model by introducing information normalization as a new dimension. Information normalization was assessed using medical templates, extracted through natural language processing methods such as Bidirectional Encoder Representations from Transformers (BERT) and Latent Dirichlet Allocation (LDA). Patient decision-making behaviors, namely, consultant selection and satisfaction, were chosen to evaluate communication performance.
Findings
The results confirmed the positive impact of information normalization on communication performance. Additionally, a negative moderating effect of disease risk on the relationship between information normalization and patient decision-making was identified. Furthermore, the study demonstrated that information normalization can be enhanced through experiential learning.
Originality/value
These findings highlighted the significance of information normalization in online healthcare communication and extended the existing information quality model. It also facilitated patient decision-making on online healthcare platforms by providing a comprehensive information quality measurement. In addition, the moderating effects indicated the contradiction between informational support and emotional support, enriching the social support theory.
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Xiangkai Zhang, Renxin Wang, Wenping Cao, Guochang Liu, Haoyu Tan, Haoxuan Li, Jiaxing Wu, Guojun Zhang and Wendong Zhang
Human-induced marine environmental noise, such as commercial shipping and seismic exploration, is concentrated in the low-frequency range. Meanwhile, low-frequency sound signals…
Abstract
Purpose
Human-induced marine environmental noise, such as commercial shipping and seismic exploration, is concentrated in the low-frequency range. Meanwhile, low-frequency sound signals can achieve long-distance propagation in water. To meet the requirements of long-distance underwater detection and communication, this paper aims to propose an micro-electro-mechanical system (MEMS) flexible conformal hydrophone for low-frequency underwater acoustic signals. The substrate of the proposed hydrophone is polyimide, with silicon as the piezoresistive unit.
Design/methodology/approach
This paper proposes a MEMS heterojunction integration process for preparing flexible conformal hydrophones. In addition, sensors prepared based on this process are non-contact flexible sensors that can detect weak signals or small deformations.
Findings
The experimental results indicate that making devices with this process cannot only achieve heterogeneous integration of silicon film, metal wire and polyimide, but also allow for customized positions of the silicon film as needed. The success rate of silicon film transfer printing is over 95%. When a stress of 1 Pa is applied on the x-axis or y-axis, the maximum stress on Si as a pie-zoresistive material is above, and the average stress on the Si film is around.
Originality/value
The flexible conformal vector hydrophone prepared by heterogeneous integration technology provides ideas for underwater acoustic communication and signal acquisition of biomimetic flexible robotic fish.
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