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There are several lead-free solder alloys available in the industry. Over the years, the most favorable solder composition of tin-silver-copper (Sn-Ag-Cu [SAC]) has been vastly used and accepted for joining the electronic components. It is strongly believed that the silver (Ag) content has a significant impact on the solder mechanical behavior and thus solder thermal reliability performance. This paper aims to assess the mechanical response, i.e. creep response, of the SAC solder alloys with various Ag contents.

A three-dimensional nonlinear finite element simulation is used to investigate the thermal cyclic behavior of several SAC solder alloys with various silver percentages, including 1%, 2%, 3% and 4%. The mechanical properties of the unleaded interconnects with various Ag amounts are collected from reliable literature resources and used in the analysis accordingly. Furthermore, the solder creep behavior is examined using the two famous creep laws, namely, Garofalo’s and Anand’s models.

The nonlinear computational analysis results showed that the silver content has a great influence on the solder behavior as well as on thermal fatigue life expectancy. Specifically, solders with relatively high Ag content are expected to have lower plastic deformations and strains and thus better fatigue performance due to their higher strengths and failure resistance characteristics. However, such solders would have contrary fatigue performance in drop and shock environments and the low-Ag content solders are presumed to perform significantly better because of their higher ductility.

Generally, this research recommends the use of SAC solder interconnects of high silver contents, e.g. 3% and 4%, for designing electronic assemblies continuously exposed to thermal loadings and solders with relatively low Ag-content, i.e. 1% and 2%, for electronic packages under impact and shock loadings.

This study aims to dissect firm knowledge into two main types: internal firm knowledge (knowledge workers) and external firm knowledge (relational knowledge with other firms). This study aims to investigate how each type affects the productivity of the firms. This study also examines how this effect differs among Egyptian firms in the agriculture, manufacturing and service sectors.

The authors use firm-level data in Egypt on the sectoral level. The properties of instrumental variables regression using two-stage least-squares estimation are adopted to overcome endogeneity and omitted variable bias in the empirical estimations.

The study’s findings reveal that the effects of internal and external knowledge on the firm productivity are sector-specific; knowledge-workers and relational knowledge are two times more effective for agriculture than manufacturing and service firms; external knowledge plays a vital role in increasing productivity relative to internal knowledge for the manufacturing sector; finally, internal and external knowledge has the same effect on the service firms.

This research adds to the body knowledge-based theory of the firm by examining the effects of internal and external knowledge on the firms’ productivity. In particular, the paper differentiates this effect across three sectors: agriculture, manufacturing and services. This paper also suggests a novel empirical methodology to address endogeneity and omitted variable bias in this literature of firm knowledge and productivity.

The purpose of this study is to examine the impact of knowledge management dimensions (i.e. knowledge acquisition, knowledge dissemination and knowledge responsiveness) on green innovation. The study also seeks to determine whether these relationships are mediated by the environmental awareness in small and medium enterprises (SMEs) in the UAE.

Data were obtained from a sample of 194 SMEs (two informants from each firm that consist of 388 top managers) in Abu Dhabi, UAE. In this cross-sectional study, convenience random sampling was used. The positivism approach was adopted using a hypothetical statistical induction method. Validated measurement scales were used to measure the study constructs adopted from previous studies. Data were analysed using a quantitative approach with Smart partial least squares structural equation modelling (PLS-SEM) 3.0.

The results of the study indicated a positive and significant association between knowledge acquisition, knowledge dissemination and knowledge responsiveness with green innovation. Moreover, the data analysis confirmed that environmental awareness mediates the relationship between knowledge dissemination and green innovation. However, no mediation role of environmental awareness in the relationship between knowledge acquisition and knowledge responsiveness with green innovation was found.

Knowing how to manage knowledge effectively is considered to be one of the most important aspects of green innovations. Nonetheless, there was a dearth of literature highlighting the relevance of knowledge management for long-term organisational success. The results of this study present practical implications for SME professionals. Green innovation with the support of environmental awareness may help a firm understand and implement the importance of knowledge management into their administrative operations. They can subsequently become eco-innovative ecologically, economically and socially.

This is one of the very few studies that examine the effect of knowledge management dimensions (knowledge acquisition, knowledge dissemination and knowledge responsiveness) on green innovation in UAE SMEs.

This study forecasts the government expenditure components in Nigeria, including recurrent and capital expenditures for 2021 and 2022, based on data from 1981 to 2020.

The study employs statistical/econometric problems using the Feasible Quasi Generalized Least Squares approach. Expenditure forecasts involve three simulation scenarios: (1) do nothing where the economy follows its natural path; (2) an optimistic scenario, where the economy grows by specific percentages and (3) a pessimistic scenario that defines specific economic contractions.

The estimation model is informed by Wagner's law specifying a positive link between economic activities and public spending. Model estimation affirms the expected positive relationship and is relevant for generating forecasts. The out-of-sample results show that a higher proportion of the total government expenditure (7.6% in 2021 and 15.6% in 2022) is required to achieve a predefined growth target (5%).

This study offers empirical evidence that specifically requires Nigeria to invest a ratio of 3 to 1 or more in capital expenditure to recurrent expenditure for the economy to be guided on growth.

This study aims to measure the acceptance of digital resources by integrating knowledge management (KM) factors (i.e. acquisition, sharing, application and protection) into the factors of the technology acceptance model (TAM) (i.e. perceived ease of use and perceived usefulness) and their impact on actual system use through behavioural intention.

Using the quantitative research method, a survey was conducted of the public sector universities of Punjab, Pakistan. Data were collected from postgraduate students and analysed using partial least squares structural equation modelling.

The findings showed that the factors of KM with the integration of TAM significantly impact the acceptance of digital resources. The study’s hypotheses are all supported, and the findings demonstrated that knowledge acquisition, knowledge sharing, knowledge application and knowledge protection significantly influenced perceived usefulness and perceived ease of use, and that these factors are positively correlated with behavioural intentions to use digital resources.

This study has considerable significant implications for policymakers, developers and practitioners in designing digital resources. This study will also assist librarians to discover areas for development that may enhance the use of digital resources among users

The purpose of this paper is to optimize the key parameters (mesh count, paper type and ink type) in screen printing, which are affecting the printed ink volume. The objective of the optimization was to maximize the color reliability by decreasing the color difference (ΔE value) of the prints while minimizing the ink consumption. Screen printing is still dominating the printing industry to make cost-effective production when high volumes are needed.

The experiment was designed using the Taguchi method, and the samples were prepared with screen-printing by using the standard squeegee angle and pressure. The effect of mesh count, ink type and paper type on ink consumption was evaluated with using analysis of variances and main effects plots of S/N ratio and standard deviation.

The factors ink type, paper type and mesh count were found significant for ink consumption due to their Probability (P) values which were lower than 0.05. It was determined that the mesh count was the most critical variable with the analysis of variance. The analysis showed that the selection of an optimum mesh count was the key to controlling the amount of the deposited ink. Although mesh counts were inversely proportional with the ink consumptions, they did not affect the color differences as expected.

The optimization of process parameters, that are most effective on the print quality, is necessary to minimize the ink usage and lower the costs and environmental impact without exceeding the desired ΔE value limits.

This paper aims to propose a method to quickly set the heating zone temperatures and conveyor speed of the reflow oven. This novel approach intensely eases the trial and error in reflow profiling and is especially helpful when reflowing thick printed circuit boards (PCBs) with bulky components. Machine learning (ML) models can reduce the time required for profiling from at least half a day of trial and error to just 1 h.

A highly compact computational fluid dynamics (CFD) model was used to simulate the reflow process, exhibiting an error rate of less than 1.5%. Validated models were used to generate data for training regression models. By leveraging a set of experiment results, the unknown input factors (i.e. the heat capacities of the bulkiest component and PCB) can be determined inversely. The trained Gaussian process regression models are then used to perform virtual reflow optimization while allowing a 4°C tolerance for peak temperatures. Upon ensuring that the profiles are inside the safe zone, the corresponding reflow recipes can be implemented to set up the reflow oven.

ML algorithms can be used to interpolate sparse data and provide speedy responses to simulate the reflow profile. This proposed approach can effectively address optimization problems involving multiple factors.

The methodology used in this study can considerably reduce labor costs and time consumption associated with reflow profiling, which presently relies heavily on individual experience and skill. With the user interface and regression models used in this approach, reflow profiles can be swiftly simulated, facilitating iterative experiments and numerical modeling with great effectiveness. Smart reflow profiling has the potential to enhance quality control and increase throughput.

In this study, the employment of the ultimate compact CFD model eliminates the constraint of components’ configuration, as effective heat capacities are able to determine the temperature profiles of the component and PCB. The temperature profiles generated by the regression models are time-sequenced and in the same format as the CFD results. This approach considerably reduces the cost associated with training data, which is often a major challenge in the development of ML models.

By investigating the thermal-mechanical interaction between the through silicon via (TSV) and the Cu pad, this study aimed to determine the effect of electroplating defects on the upper surface protrusion and internal stress distribution of the TSV at various temperatures and to provide guidelines for the positioning of TSVs and the optimization of the electroplating process.

A simplified model that consisted of a TSV (100 µm in diameter and 300 µm in height), a covering Cu pad (2 µm thick) and an internal drop-like electroplating defect (which had various dimensions and locations) was developed. The surface overall deformation and stress distribution of these models under various thermal conditions were analyzed and compared.

The Cu pad could barely suppress the upper surface protrusion of the TSV if the temperature was below 250 ?. Interfacial delamination started at the collar of the TSV at about 250 ? and became increasingly pronounced at higher temperatures. The electroplating defect constantly experienced the highest level of strain and stress during the temperature increase, despite its geometry or location. But as its radius expanded or its distance to the upper surface increased, the overall deformation of the upper surface and the stress concentration at the collar of the TSV showed a downward trend.

Previous studies have not examined the influence of the electroplating void on the thermal behavior of the TSV. However, with the proposed methodology, the strain and stress distribution of the TSV under different conditions in terms of temperature, dimension and location of the electroplating void were thoroughly investigated, which might be beneficial to the positioning of TSVs and the optimization of the electroplating process.

This paper aims to investigate the effect of physical vapor deposition (PVD)-coated stencil wall aperture on the life span of fine-pitch stencil printing.

The fine-pitch stencil used in this work is fabricated by electroform process and subsequently nano-coated using the PVD process. Stencil printing process was then performed to print the solder paste onto the printed circuit board (PCB) pad. The solder paste release was observed by solder paste inspection (SPI) and analyzed qualitatively and quantitatively. The printing cycle of up to 80,000 cycles was used to investigate the life span of stencil printing.

The finding shows that the performance of stencil printing in terms of solder printing quality is highly dependent on the surface roughness of the stencil aperture. PVD-coated stencil aperture can prolong the life span of stencil printing with an acceptable performance rate of about 60%.

Stencil printing is one of the important processes in surface mount technology to apply solder paste on the PCB. The stencil’s life span greatly depends on the type of solder paste, stencil printing cycles involved and stencil conditions such as the shape of the aperture, size and thickness of the stencil. This study will provide valuable insight into the relationship between the coated stencil wall aperture via PVD process on the life span of fine-pitch stencil printing.

The purpose of this study is to highlight the indigenous knowledge systems (IKS) preservation efforts in South Africa, with a focus on the National Recordal System and the Indigenous Knowledge Systems Documentation Centres (IKSDCs) across South Africa.

Anchored in the interpretivist paradigm, the qualitative research approach was adopted to explore the objectives of the study. The multiple case study method was considered appropriate and adopted for the study. The data for this study was collected through comprehensive face-to-face interviews and Web content analysis. The population of the study consisted of the staff at the IKSDCs in the selected academic institutions. The purposive sampling technique was used to select the following set of participants in each academic institution: IKS managers/coordinators, digitization officers and online collection administrators.

The findings provide an in-depth understanding of the IKS landscape in South Africa. The findings and recommendations of this paper would be useful to researchers who wish to know more about digitization efforts in South Africa. It would also be useful to all stakeholders and policymakers.

The paper brings to the fore the efforts of the South African government in preserving IKS through documentation and digitization. The paper highlights the sources of indigenous knowledge, types of indigenous knowledge captured, how the indigenous knowledge is ingested in the repositories and how the data is captured. Generally, the roles of the IKSDCs in the capture and preservation of IKS are highlighted.