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A real-time production scheduling method for semiconductor back-end manufacturing process becomes increasingly important in industry 4.0. Semiconductor back-end manufacturing process is always accompanied by order splitting and merging; besides, in each stage of the process, there are always multiple machine groups that have different production capabilities and capacities. This paper studies a multi-agent based scheduling architecture for the radio frequency identification (RFID)-enabled semiconductor back-end shopfloor, which integrates not only manufacturing resources but also human factors.

The architecture includes a task management (TM) agent, a staff instruction (SI) agent, a task scheduling (TS) agent, an information management center (IMC), machine group (MG) agent and a production monitoring (PM) agent. Then, based on the architecture, the authors developed a scheduling method consisting of capability & capacity planning and machine configuration modules in the TS agent.

The authors used greedy policy to assign each order to the appropriate machine groups based on the real-time utilization ration of each MG in the capability & capacity (C&C) planning module, and used a partial swarm optimization (PSO) algorithm to schedule each splitting job to the identified machine based on the C&C planning results. At last, we conducted a case study to demonstrate the proposed multi-agent based real-time production scheduling models and methods.

This paper proposes a multi-agent based real-time scheduling framework for semiconductor back-end industry. A C&C planning and a machine configuration algorithm are developed, respectively. The paper provides a feasible solution for semiconductor back-end manufacturing process to realize real-time scheduling.

Most of the current literature investigates workplace-based formal and informal learning separately; thus, the relationship between these two types of learning remains unclear. This study aims to fill this research gap, drawing on self-determination theory to bridge teachers’ formal and informal learning and uncover the relationship between the two.

The participants of the study are 1,886 primary and secondary in-service teachers in China. Structural equation modeling and bootstrapping are used to test the proposed model.

The study reveals complicated influencing mechanisms of formal learning on different types of informal learning among in-service teachers. Teachers’ basic psychological needs, satisfaction and challenge-seeking behavior are found to play crucial mediating roles in this process.

First, this study suggests that different configurations of intervention strategies should be formulated depending on the foci for improving teachers’ learning. Second, this study indicates that only highlighting the importance of reflection, which is the approach currently used, is not sufficient to improve teachers’ daily reflective practice. Third, there is an urgent need to design training programs to improve teachers’ abilities to purposefully expand their job boundaries, which could not only benefit teachers’ performance but also contribute to school improvement. For policymakers and school principals, we suggest that more attention be given to the satisfaction of teachers’ basic needs.

This study contributes to the literature on workplace learning by connecting formal and informal learning and elucidating how teachers’ reported formal learning influences their informal learning activities via varied paths. The findings have implications for continuous professional development policy and training programs in the workplace.

The purpose of this study is to solve the problem of longer dead-time in the rear bridge leg switches and lower efficiency in the Four-Switch Buck-Boost LLC Resonant Converter.

The paper adopts time-domain analysis to derive the time-domain expression for optimal dead time, analyzing the conditions for achieving soft switching of the transistors. It further explores the relationship between the dead time of the bridge arm switching transistors and the input/output of the converter under different operating conditions. Specifically, the dead time of the upper bridge arm transistors increases with the converter input voltage and decreases with the output current. In contrast, the dead time of the lower bridge arm transistors is independent of the converter output current and decreases with increasing converter input voltage.

By simulating and constructing a 500 W experimental prototype, experimental results indicate that designing the dead time of the switch according to the optimal dead time proposed in this paper significantly improves efficiency when the converter operates from heavy load to full load. When the transformer takes minimum input, maximum input and intermediate bus voltage inputs respectively, its peak efficiency is increased by 0.6%, 1.7% and 1.1%, respectively, compared to the traditional four-switch Buck–Boost LLC resonant converter.

Experimental validation confirms the correctness of the optimal dead time design and analyzes the impact of different operating conditions of the converter on the dead time. This is of significant importance for the rational design of switch dead times and the enhancement of converter efficiency.

This paper aims to analyze the spatiotemporal heterogeneity of regional total factor productivity (TFP) growth and explores how haze pollution and different levels of new-type urbanization affect China’s economic growth.

This paper constructs an index for evaluating the TFP growth of China’s 31 provinces by integrating slack-based measures and the Global Malmquist (GM) productivity index. Meanwhile, the panel threshold estimation method is used to examine the complex relationships among haze pollution, new-type urbanization and TFP growth.

The results reflect conspicuous spatiotemporal heterogeneity in TFP growth in China. Interestingly, the influence of haze pollution on TFP growth is limited by the “critical mass” of new-type urbanization in China. When new-type urbanization does not cross the first threshold, haze pollution has a negative but non-significant effect on TFP growth. When new-type urbanization crosses the first threshold but not the second, haze pollution has a significant positive impact on TFP growth. When new-type urbanization crosses the second threshold, haze pollution significantly and positively affects TFP growth with the strongest positive effect.

This study innovates by combining haze pollution and TFP growth and proposing an integrated framework from the perspective of new-type urbanization, providing insight into how different degrees of new-type urbanization impact the mechanism between haze pollution and TFP growth. Using panel data in China and emphasizing green development, a sustainable economy and new-type urbanization, this study contributes to the current studies on haze pollution and economic development based on developed countries.

Based on the construal level theory, the purpose of this study is to prove the effect of interaction between construal level and visual crowding on consumers' buying intention. The study tries to explain the reasons behind the different buying intention toward visual crowding among consumers with different construal level.

This study was conducted through two situational simulation experiments. The main data analysis methods are ANOVA and bootstrap analysis.

(1) the matching of construal level and visual crowding has a significant effect on consumers’ buying intention. (2) Perceptual fluency mediates the interaction between the construal level and visual crowding on buying intention.

This study measures consumers' buying intention through situational experiments but does not measure consumers' buying behavior through real scenarios.

According to the study conclusions, consumers prefer visually crowded packaging that matches their construal level. Enterprises should consider the impact of the construal level on the effect of packaging stimulation.

This study enriches the theory related to construal level and highlights the mediating role of perceptual fluency. The addition of perceptual fluency explains the mechanism by which visual crowding affects consumers' buying intention. This extends the research on the antecedents and effects of perceptual fluency.

This study innovatively introduces visual crowding into packaging and matches visual crowding to construal level, explaining why different consumers buy different visually crowded packaging.