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This paper aims to provide the proper preset temperatures of the convection reflow oven when reflowing a printed circuit board (PCB) assembly with varied sizes of components simultaneously.

In this study, computational fluid dynamics modeling is used to simulate the reflow soldering process. The training data provided to the machine learning (ML) model is generated from a programmed system based on the physics model. Support vector regression and an artificial neural network are used to validate the accuracy of ML models.

Integrated physical and ML models synergistically can accurately predict reflow profiles of solder joints and alleviate the expense of repeated trials. Using this system, the reflow oven temperature settings to achieve the desired reflow profile can be obtained at substantially reduced computation cost.

The prediction of the reflow profile subjected to varied temperature settings of the reflow oven is beneficial to process engineers when reflowing bulky components. The study of reflowing a new PCB assembly can be started at the early stage of board design with no need for a physical profiling board prototype.

This study provides a smart solution to determine the optimal preset temperatures of the reflow oven, which is usually relied on experience. The hybrid physics–ML model providing accurate prediction with the significantly reduced expense is used in this application for the first time.

Considering the external disturbances and dynamic uncertainties during the process of the trajectory tracking, this paper aims to address the problem of the welding robot trajectory tracking with guaranteed accuracy.

The controller consists sliding mode control, fuzzy control and low pass filter. The controller adopts low-pass filter to reduce the high frequency chattering control signal in sliding mode control. The fuzzy control model is used to simulate the external disturbance signal and the dynamic uncertainty signal, so that the controller can effectively restrain the chattering caused by the sliding mode control algorithm, realizing the track of the welding robot effectively and improving the robustness of the robot.

An innovative experiment device was adopted to realize the performance of the proposed controller. Considering the kinematic and dynamic uncertainty during the process of robot tracking, the tracking accuracy was realized within 0.3 mm.

This paper uses Lyapunov stability theory and Barbalat theorem to analyze the stability of the proposed controller.

As for vibrating screen, the separation of granular materials is a very complicated process, particularly the screening with a swing trace. To study the characteristics of stratification and penetration in the swing vibrating screen, a three-dimensional numerical model was developed to simulate the screening process.

The discrete element method (DEM) was used to perform the numerical simulation, and the kinetic model of the swing screening was established. The regions of stratification and penetration were defined, and the mathematical functions relating fine particle ratio of stratification and penetration to time were presented using the least squares method.

The results show that the low value of frequency (5 and 10 Hz) has a limited effect on the stratification, while the obvious effect can be found at high frequency. A low frequencies or small swing angles may enhance the particle penetration. By studying the vibration parameters affecting the stratification and penetration rate, it is found that the frequency has more influence than the swing angle.

The higher screening efficiency and processing capacity can be further obtained for the swing vibrating screen by comparing with the linear vibrating screen. These results reveal the fundamental characteristics of particle motion in the swing screening, which will provide reliable guidance for studying the design optimization of vibrating screen.

Managers of megaprojects face social risk management challenges throughout the various design, construction, and operation stages, owing to the various conflicts of interest among stakeholders, public skepticism, and opposition. However, most existing studies have not focused on the dynamic analysis of integrating social risks in these stages. This study developed a dynamic analysis approach to explore the dynamics of critical social risk factors and related stakeholders of megaprojects and built the managerial maps for various stakeholders.

Based on the social analysis network (SNA), a dynamic network analysis approach for understanding the dynamics of social risk and related stakeholders has been developed by literature and case analysis. The approach comprises the following steps: (1) generating social risk–stakeholder networks in different stages; (2) analysis of the critical stakeholders and social risk factors; (3) dynamic analysis of social risk factors; and (4) developing social risk management maps for various stakeholders. To verify the feasibility and effectiveness of the approach, 40 megaprojects from China were analyzed.

According to the results, the local government is a critical stakeholder during all stages, inadequate information promotion (IIP) and imperfect communication and coordination mechanism (ICCM) are key social risk sources throughout the megaproject life cycle. Furthermore, the management maps for government organizations, project implementation groups, and external stakeholders were constructed.

This research has three contributions. First, a dynamic analysis approach of stakeholder-associated social risks in megaprojects is developed, which enriches the social risk management theory of megaprojects and provides inspiration for future research focus. Second, the social risk–stakeholder networks and critical social risks in different stages are confirmed to provide a more valid and accurate picture of social risk management in megaprojects. Third, the social risk managerial maps for different stakeholders built in this research will be beneficial for governments, project implementation groups, and external stakeholders to optimize management strategies.

An industrialized building system (IBS) is regarded as an effective residential building system that provides several benefits, including high quality, low cost, short time, good flexibility, reduced waste, and strong environmental performance. This system is considered to be valuable in promoting sustainable practices in China, where plans for urbanization have been established. However, the adoption of IBS in China is extremely limited. Potential risks exist and affect the attitudes of practitioners toward the use of this system. The purpose of this paper is to prioritize and analyze these risks and to develop corresponding strategies for mitigating these risks in China.

In total, 24 risks that inhibit the implementation of IBS in China are identified through literature review and examined through interviews for consistency. A questionnaire survey is conducted to quantify the significance of these risks. Cronbach’s coefficient α is employed to measure the internal consistency among the risk factors. The survey results are further analyzed using three case studies.

The top five risks identified are “poor cooperation between multi-interface,” “inappropriate design codes and standards for industrialized buildings,” “lack of management practices and experiences,” “enormous difficulty in achieving return on high initial investment,” and “lack of a quality monitoring mechanism for the production process.” The findings emphasize the government’s leading role in promoting the new building system in its introduction and enforcement of adequate policies and regulations. Practitioners are also instrumental in establishing proper understanding and knowledge of IBS and its application.

This study bridges the knowledge gaps on risk identification for implementing IBS in China. The findings provide practitioners and decision makers with valuable references for adopting adequate risk management methods and policies to promote IBS in China.

China's marine economy occupies an important position within the national economy, and its contribution thereto is constantly improving. The overall operation of the marine economy shows positive developmental trends with potential for further growth. The purpose of this research is to analyse the prosperity of China's marine economy, reveal trends therein and forecast the likely turning point in its operation.

Based on the periodicity and fluctuation of China's marine economy development, China's marine economic prosperity indicator system is established from five perspectives. On this basis, China's marine economic operation prosperity index can be synthesised and calculated, then a dynamic factor model is constructed. Using the filtering method to calculate China's marine economic operational Stock–Watson index, Markov switching has been used to determine the trend to transition. Furthermore, China's current marine economic prosperity is evaluated through analysis of influencing factors and correlation analysis.

The analysis shows that, from 2017 to 2019, the operation of the marine economy is relatively stable, and the prosperity index supports this finding; meanwhile it also exposes problems in China's marine economy, such as an unbalanced industrial structure, low marine economic benefits and insufficient capacity for sustainable development.

Through the analysis of the prosperity of China's marine economy, the authors reveal the trends in China's marine economy and forecast its likely future turning point.

A sustainable transportation system should represent a win-win situation: minimizing transport's impact on the environment and reducing natural disasters' effects on transportation. A well-distributed set of rain gauges is crucial for monitoring services in smart cities. However, those services should consider the uncertainties about the registers of rainfall impacts. In this paper, the authors present a case study of optimal rain gauge location based on an actual database of rainfall events with impacts on urban mobility in the city of Sao Paulo (Brazil).

This paper presents a maximal covering location formulation and proposes a robustness analysis considering spatial location perturbations.

In this case study, the robustness of the objective function is above 99.99%. The robustness for the number of covered demand points is 88.93%, and the frequency associated with every candidate is between 11.71% and 69.49%.

Incorporating spatial uncertainties on coverage problems is essential to provide stakeholders more realistic supporting tools and to draw different possible scenarios.

This study aims to explore service modularity in the context of digital technology and environmental sustainability, particularly considering the transformative impacts of the post-pandemic world. It aims to shed light on how service modularity can adapt to and thrive in these evolving circumstances.

Using a comprehensive analytical approach, this paper addresses the critical concerns and limitations inherent in traditional service modularity concepts. It proposes novel perspectives on service modularity, enriched by recent technological advancements and sustainability imperatives.

The research reveals new dimensions of service modularity, emphasising its significance in the era of digital transformation and heightened environmental awareness. It provides empirical insights into how service modularity can be effectively reimagined and implemented in response to the challenges and opportunities arising from the COVID-19 pandemic.

The findings offer valuable guidance for organisations seeking to enhance their service delivery through modularity. The study underscores the importance of integrating digital innovation and sustainability principles into service design and execution in the post-pandemic era.

This paper makes a novel contribution to the field of service modularity by intertwining it with the realms of digital technology and environmental sustainability. It offers a unique perspective on adapting service modularity to contemporary challenges, thereby enriching the existing body of literature and providing a foundation for future research in this area.

The purpose of this paper is to use the corresponding magnetic sensor and detection method to detect and image the defects of small diameter pipelines. Urban gas pipeline is an energy transportation tool for urban industrial production and social life, which is closely related to urban safety. Preventing the occurrence of urban gas pipeline transportation accidents and carrying out pipeline defect detection are of great significance for the urban economic and social stability. To perform pipeline defect detection, the magnetic flux leakage internal detection method is generally used in the detection of large-diameter long-distance oil and gas pipelines. However, in terms of the internal detection of small-diameter pipelines, due to the heavy weight, large structure of the detection device and small pipe diameter, the detection is more difficult.

In order to solve the above matters, self-made three-dimensional magnetic sensor and three-dimensional magnetic flux leakage imaging direct method are proposed for studying the defect identification. Firstly, for adapting to the diameter range of small-diameter pipelines, and containing the complete information of the defect, a self-made three-dimensional magnetic sensor is made in this paper to improve the accuracy of magnetic flux leakage detection. And on the basis of it, a small diameter pipeline defect detection system is built. Secondly, as detection signal may be affected by background magnetic field interference and the jitter interference, the complete ensemble empirical mode decomposition with adaptive noise method is utilized to screen the detected signal. As a result, the useful signal is reconstructed and the interference signal is removed. Finally, the defect contour inversion imaging of detection is realized based on the direct method of three-dimensional magnetic flux leakage imaging, which includes three-dimensional magnetic flux leakage detection data and data segmentation recognition.

The three-dimensional magnetic flux leakage imaging experimental results shown that, compared to the actual defects, the typical defects, irregular defects and crack groove defects can be analyzed by the magnetic flux leakage defect contour imaging method in qualitative and quantitative way respectively, which provides a new idea for the research of defect recognition.

A three-dimensional magnetic sensor is made to adapt the diameter range of small diameter pipeline, and based on it, a small-diameter pipeline defect detection system is built to collect and display the magnetic flux leakage signal.

The existing literature has been mainly focused on local problems but without an overall framework for studying the top-level planning of intelligent construction from a systematic perspective. The purpose of this paper is to fill this gap.

This research adopts a deductive research approach.

This research proposes a reference architecture and related business scenario framework for intelligent construction based on the existing theory and industrial practice.

The main contribution of this research is to provide a useful reference to the Chinese government and industry for formulating digital transformation strategies, as well as suggests meaningful future research directions in the construction industry.