Guo‐Quan Lu, Xingsheng Liu, Sihua Wen, Jesus Noel Calata and John G. Bai
In this paper, some strategies taken to improve the reliability of solder joints on power devices in single device and multi‐chip packages are presented. A strategy for improving…
Abstract
In this paper, some strategies taken to improve the reliability of solder joints on power devices in single device and multi‐chip packages are presented. A strategy for improving solder joint reliability by adjusting solder joint geometry, underfilling and utilization of flexible substrates is discussed with emphasis on triple‐stacked solder joints that resemble the shape of an hourglass. The hourglass shape relocates the highest inelastic strain away from the weaker interface with the chip to the bulk region of the joint, while the underfill provides a load transfer from the joints. Thermal cycling data show significant improvements in reliability when these techniques are used. The design, testing and finite‐element analyses of an interconnection structure, termed the Dimple‐Array Interconnect, for improving the solder joint reliability is also presented.
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Wan Xu, Xinsheng Liu, Huijuan Zhang, Ting Huo, Zhenbin Chen and Yuan Sun
This study aims to prepare an imprinted composite membrane with grafted temperature-sensitive blocks for the efficient adsorption and separation of rhenium(Re) from aqueous…
Abstract
Purpose
This study aims to prepare an imprinted composite membrane with grafted temperature-sensitive blocks for the efficient adsorption and separation of rhenium(Re) from aqueous solutions.
Design/methodology/approach
PVDF resin membrane was used as the substrate, dopamine and chitosan (CS) were used to modify the membrane surface and temperature-sensitive block PDEA was grafted on the membrane surface. Then acrylic acid (AA) and N-methylol acrylamide (N-MAM) were used as the functional monomers, ethyleneglycol dimethacrylate (EGDMA) as the cross-linker and ascorbic acid-hydrogen peroxide (Vc-H2O2) as the initiator to obtain the temperature-sensitive ReO4− imprinted composite membranes.
Findings
The effect of the preparation process on the performance of CS–Re–TIICM was investigated in detail, and the optimal preparation conditions were as follows: the molar ratios of AA–NH4ReO4, N-MAM and EGDMA were 0.13, 0.60 and 1.00, respectively. The optimal temperature and time of the reaction were 40 °C and 24 h. The maximum adsorption capacity of CS–Re–TIICM prepared under optimal conditions was 0.1071 mmol/g, and the separation was 3.90 when MnO4− was used as the interfering ion. The quasi first-order kinetics model and Langmuir model were more suitable to describe the adsorption process.
Practical implications
With the increasing demand for Re, the recovery of Re from Re-containing secondary resources becomes important. This study demonstrated a new material that could be separated and recovered Re in a complex environment, which could effectively alleviate the conflict between the supply and demand of Re.
Originality/value
This contribution provided a new material for the selective separation and purification of ReO4−, and the adsorption capacity and separation of CS–Re–TIICM were increased with 1.673 times and 1.219 time compared with other Re adsorbents, respectively. In addition, when it was used for the purification of NH4ReO4 crude, the purity was increased from 91.950% to 99.999%.
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Cheng Xue, Zhaowang Xia, Xingsheng Lao and Zhengqi Yang
The purpose of this study is to provide some references about applying the semi-active particle damper to enhance the stability of the pipe structure.
Abstract
Purpose
The purpose of this study is to provide some references about applying the semi-active particle damper to enhance the stability of the pipe structure.
Design/methodology/approach
This paper establishes the dynamical models of semi-active particle damper based on traditional dynamical theory and fractional-order theory, respectively. The semi-active particle damping vibration isolation system applied in a pipe structure is proposed, and its analytical solution compared with G-L numerical solution is solved by the averaging method. The quantitative relationships of fractional-order parameters (a and kp) are confirmed and their influences on the amplitude-frequency response of the vibration isolation system are analyzed. A fixed point can be obtained from the amplitude-frequency response curve, and the optimal parameter used for improving the vibration reduction effect of semi-active particle damper can be calculated based on this point. The nonlinear phenomenon caused by nonlinear oscillators is also investigated.
Findings
The results show that the nonlinear stiffness parameter p will cause the jump phenomenon while p is close to 87; with the variation of nonlinear damping parameter μ, the pitchfork bifurcation phenomenon will occur with an unstable branch after the transient response; with the change of fractional-order coefficient kp, a segmented bifurcation phenomenon will happen, where an interval that kp between 18.5 and 21.5 has no bifurcation phenomenon.
Originality/value
This study establishes a mathematical model of the typical semi-active particle damping vibration isolation system according to fractional-order theory and researches its nonlinear characteristics.
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Zhen Yang, Yun Lin, Xingsheng Gu and Xiaoyi Liang
The purpose of this paper is to study the electrochemical properties of electrode material on activated carbon double layer capacitors. It also tries to develop a prediction model…
Abstract
Purpose
The purpose of this paper is to study the electrochemical properties of electrode material on activated carbon double layer capacitors. It also tries to develop a prediction model to evaluate pore size value.
Design/methodology/approach
Back-propagation neural network (BPNN) prediction model is used to evaluate pore size value. Also, an improved heuristic approach genetic algorithm (HAGA) is used to search for the optimal relationship between process parameters and electrochemical properties.
Findings
A three-layer ANN is found to be optimum with the architecture of three and six neurons in the first and second hidden layer and one neuron in output layer. The simulation results show that the optimized design model based on HAGA can get the suitable process parameters.
Originality/value
HAGA BPNN is proved to be a practical and efficient way for acquiring information and providing optimal parameters about the activated carbon double layer capacitor electrode material.
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Jin Zhu, Xingsheng Gu and Wei Gu
The purpose of this paper is to set up a two‐stage stochastic integer‐programming model (TSM) for the multiperiod scheduling of multiproduct batch plants under demand uncertainty…
Abstract
Purpose
The purpose of this paper is to set up a two‐stage stochastic integer‐programming model (TSM) for the multiperiod scheduling of multiproduct batch plants under demand uncertainty involving the constraints of material balances and inventory constraints, as well as the penalty for production shortfalls and excess.
Design/methodology/approach
Scheduling model is formulated as a discrete‐time State Task Network. Given a scheduling horizon consisting of several time‐periods in which product demands are placed, the objective is to select a schedule that maximizes the expected profit for a single and multiple product with a given probability level. The stochastic elements of the model are expressed with equivalent deterministic optimization models.
Findings
The TSM model not only allows for uncertain product demand correlations, but also gives different processing modes by a range of batch sizes and a task‐dependent processing time. The experimental results show that the TSM model is more appropriate than another model for multiperiod scheduling of multiproduct batch plants under correlated uncertain demand.
Research limitations/implications
The choice of penalty parameter of demand uncertainty is the main limitation.
Practical implications
The paper provides very useful advice for multiperiod scheduling of multiproduct batch plants under demand uncertainty.
Originality/value
A stochastic model for the multiperiod scheduling of multiproduct batch plants under demand uncertainty was set up. A test problem involving 12 correlated uncertain product demands and two alternative models verified the availability of the TSM.
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Zhen Yang, Kangning Song, Xingsheng Gu, Zhi Wang and Xiaoyi Liang
Nitrogen oxides (NOx) have been considered as primarily responsible for many serious environmental problems. Removing NO is the key task to remove NOx hazards. To clarify, NO…
Abstract
Purpose
Nitrogen oxides (NOx) have been considered as primarily responsible for many serious environmental problems. Removing NO is the key task to remove NOx hazards. To clarify, NO removal process for pitch-based spherical-activated carbons (PSACs), an online prediction and optimization technique in real-time based on support vector machine algorithm in regression (support vector regression [SVR]) is discussed. The purpose of this paper is to develop a predictor and optimizer system on selective catalytic reduction of NO (SCRN) using experimental data and data-driven SVR intelligence methods.
Design/methodology/approach
Predictor and optimizer using developed SVR have been proposed. To modify the training efficiency of SVR, the authors especially customize batch normalization and k-fold cross-validation techniques according to the unique characteristics of PSACs model.
Findings
The results present that SVR provides a property regression model since it can linkage linear and non-linear process and property relationships in few experimental data sets. Also, the integrated normalization and k-fold cross-validation show a satisfying improvement and results for SVR optimization. The predicted results of predictor and optimizer in single and double factor systems are in excellent agreement with the experimental data.
Originality/value
SCRN-PO for predicting and optimization SCRN problems is developed by data-driven methods. The outperformed SCRN-PO system is used to predict multiple-factors property parameters and obtain optimum technological parameters in real-time. Also, experiment duration is greatly shortened.
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Liu Wei‐hua, Xu Xue‐cai, Ren Zheng‐xu and Peng Yan
On one side, the purpose of this paper is to numerically analyze the emergency order allocation mechanism and help managers to understand the relationship between the emergency…
Abstract
Purpose
On one side, the purpose of this paper is to numerically analyze the emergency order allocation mechanism and help managers to understand the relationship between the emergency coefficient, uncertainty and emergency cost in two‐echelon logistics service supply chain. On the other side, the purpose of this paper is to help managers understand how to deal with the problem of order allocation in the two‐echelon logistics service supply chain better in the case of emergency.
Design/methodology/approach
The paper presents a multi‐objective planning model for emergency order allocation and then uses numerical methods with LINGO 8.0 software to identify the model's properties. The application of the order allocation model is then presented by means of a case study.
Findings
With the augment of uncertainty, the general cost of logistics service integrator (LSI) is increasing, while the total satisfaction of all functional logistics service providers (FLSPs) is decreasing, as well as the capacity reliability; at the same time the emergency cost coefficient is closely correlative with the satisfaction and general penalty intensity of FLSPs; finally, the larger the emergency cost coefficient is, the more satisfaction of FLSPs, but the capacity reliability goes up first and down later.
Research limitations/implications
Management should note that it is not better when emergency cost coefficient is bigger. The general satisfaction degree of FLSP increases with the augment of emergency cost coefficient, but there is an upper limit of the value, i.e. it will not increase indefinitely with the augment of emergency cost coefficient. This paper also has some limitations. The optional emergency cost coefficient only adopted a group of data to analyze while the trend of the reliability of logistics capacity needs to be further discussed. In addition, the algorithm of emergency order allocation model in the case of multi‐objective remains to be solved.
Practical implications
Under emergency conditions, LSIs can adopt this kind of model to manage their FLSPs to obtain the higher logistics performance. But LSIs should be careful selecting emergency cost coefficient. In accordance with different degrees of emergency logistics demand, LSIs can determine reasonable emergency cost coefficient, but not the bigger, the better, on the premise that LSIs acquire maximum capacity guarantee degree and overall satisfaction degree of FLSPs. FLSPs can make contract bargaining of reasonable emergency coefficient with LSIs to make both sides get the best returns and realize the benefit balance.
Originality/value
Many studies have emphasized the capacity allocation of manufactures, order allocation of manufacturing supply chain and scheduling model of emergency resources without monographic study of supply chain order allocation of logistics service. Because the satisfaction degree of FLSPs the cost of integrators needs to be considered in the process of order allocation, and the inventory cost of capacity does not exist, it is different from the issue of capacity allocation planning of manufacture supply chain. Meanwhile, the match of different kinds of logistics service capacity must be considered for the reason of the integrated feature of logistics service. Additionally, cost is not the most important decision objective because of the characteristics of demand uncertainty and weak economy. Accordingly, this paper considers these issues.
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Cong Yin, Yujing Zhou, Peiyu He and Meng Tu
This research takes the transfer behavior of users from Tencent QQ to WeChat as an example to discuss the wider transfer behavior of social media users on the Internet.
Abstract
Purpose
This research takes the transfer behavior of users from Tencent QQ to WeChat as an example to discuss the wider transfer behavior of social media users on the Internet.
Design/methodology/approach
This paper collects data through a combination of offline interviews and online questionnaire surveys, and utilizes data analysis tools to construct structural equation modeling (SEM). Using Statistical Product and Service Solutions (SPSS) Statistics 22.0 and Analysis of Moment Structures (AMOS) 22.0 software with SEM, this study was carried out to provide reasonable statistical support for relevant proposed hypotheses based on 368 effective samples acquired through the questionnaire.
Findings
The findings of this study show that subjective norm, transfer experience, social communication, and knowledge acquisition all have significant associations with transfer intention and switching behavior. To be specific, transfer intention exerts a positive association on switching behavior; function setting, privacy protection and personal innovation have a favorable association with transfer intention; transfer cost has a significantly negative relationship with transfer intention and switching behavior; function setting has no important relationship on switching behavior.
Originality/value
The research results provide a reference for improving the viscosity and loyalty of social media users in the new era and resolving the problem of user churn.
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This paper presents a mixed-integer programming model for a single machine earliness/tardiness scheduling problem where the objective is to minimize total earliness/tardiness…
Abstract
Purpose
This paper presents a mixed-integer programming model for a single machine earliness/tardiness scheduling problem where the objective is to minimize total earliness/tardiness duration when the uncertainty of parameters such as processing times and due date is coded with grey numbers.
Design/methodology/approach
Grey theory and grey numbers are used for illustrating the uncertainty of parameters in processing times and common due date, where the objective is to minimize the total earliness/tardiness duration. The paper proposes a 0–1 mathematical model for the problem and an effective heuristic method for the problem by using expected processing times for ordering jobs.
Findings
The uncertainty of the processing times and common due date are encoded with grey numbers and a position-dependent mixed-integer mathematical programming model is proposed for the problem in order to minimize total grey earliness/tardiness duration of jobs having grey processing times and a common due date. By using expected processing times for ranking grey processing times, V-shaped property of the problem and an efficient heuristic method for the problem are proposed. Solutions obtained from the heuristic method show that the heuristic is effective. The experimental study also reveals that while differences between upper and lower bounds of grey processing times decrease, the proposed heuristic's performance decreases.
Originality/value
The grey theory and grey numbers have been rarely used as machine scheduling problems. Therefore, this study provides an important contribution to the literature.
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Yunqi Chen and Yichu Wang
This paper aims to identify key factors influencing the development of advanced manufacturing clusters and propose governance pathways for their digital innovation ecosystems.
Abstract
Purpose
This paper aims to identify key factors influencing the development of advanced manufacturing clusters and propose governance pathways for their digital innovation ecosystems.
Design/methodology/approach
A quantitative analysis of the Tai-Xin Integrated Economic Zone in China is conducted using data collected through a questionnaire survey. An evaluation index for the development level of advanced manufacturing clusters is constructed, and a structural equation model is used to identify key influencing factors and governance pathways.
Findings
This paper reveals that factors such as industrial foundation, technological innovation capability, social institution environment and government policies have a significant positive impact on the development of digital innovation ecosystem in advanced manufacturing clusters. It constructs a governance model for the digital innovation ecosystem and proposes three major pathways: integration of heterogeneous innovation resources, enhancement of digital capabilities, and fostering digital collaborative governance. The crucial role of digital technology in improving data processing efficiency, optimizing resource allocation and promoting collaboration among entities is emphasized. These pathways can optimize resource allocation, boosting the competitiveness and innovation capacity of clusters.
Originality/value
By incorporating advanced manufacturing clusters into the digital innovation ecosystem framework, this paper enriches theoretical research on both fronts. It offers specific governance pathways and policy recommendations, providing valuable references and guidance for promoting the digital transformation and ecosystem construction of manufacturing clusters.