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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.

This study aims to solve the premature failure of the rubber stator due to wear, reduce the frictional resistance moment of the screw pump to solve the problem of a model of Daqing oilfield screw pump oil recovery system shutdown after the difficult start.

For the first time, the rotor surface of a screw pump was treated with dot-matrix texture to study the effect of dot matrix texture on the tribological performance of the stator-rotor friction subsets of screw pump. Reciprocating friction tests with different texture morphologies (S-shape, double tongue) and angular parameters (0°, 45° and 90°) were conducted at 10% of the texture area and pump silicone grease.

When point texture was added to the surface of the rotor sample, the friction coefficient and wear quantity of the sample were lower than those of the surface without texture treatment, and the double tongue 0° combination showed the best tribological properties. At this time, the average coefficient of friction and wear is reduced by 22.8% and 62%, 28.6% and 64.8%.

The introduction of texture can effectively improve the tribological performance of progressive screw pumps, and this paper provides important theoretical and experimental support for the design of progressive screw pumps in practical applications.

To improve the apparel e-customized system and meet consumers’ personalized requirement in the e-customization, the purpose of this paper is to develop an e-customized co-design system on garment design (ECS-GD) that enables users to co-design garment and communicate with stakeholders.

The e-customized co-design system mainly consists of function and modular structure, communication and evaluation modular. Based on the evolutionary algorithm and fuzzy theory, the e-customized system model is proposed with a presentation of garment interface. Based on the parameters of skirts, technical sketches, fabrics, color, patterns, comments and scores, the decision is made by consumers.

For the system to be effective, the system was conducted by multi-individuals co-work (consumers, designers, manufacturers and experts). The data flow was congruent to the design knowledge. The expert evaluation and communication were involved in the proposed system.

The limitation of this study is that the system is not tested in experiments. The model, main function and data flow are proposed in this study, which is important in the e-customized co-design system development.

Compared to the e-shopping and garment recommendation, the proposed ECS-GD is a good approach to improve the existing e-customized system and a well solution to help consumers with design knowledge recommending, professional suggestions and evaluations. Besides, the sketches and knowledge recommendation are provided to consumers which is a learning process.

The purpose of this paper is to research the morphologies of the oxide films formed on the internal surfaces of water wall tubes in a 600 MW furnace at 300° while using CPT, CT, AVT(R) and AVT(O) water chemistry. In these water chemistry conditions, a layer of oxide film spontaneously forms in the furnace wall which could prevent corrosions in boiler water directly contact with the inner tube and reduce the probability of tube perforation.

The different morphologies, specific functions and distribution in the oxide film were identified by electrochemical workstation, XRD, SEM and EDAX.

It is concluded that metal surface was rugged and had deep corrosion in CPT. Ions penetrated into the oxides of large particles with gaps and intergranular corrosion occurred in CT conditions. In AVT(R), the oxide film uniformly covered on the metal surface played a protective role, but could be easily washed away by solution. The oxide film formed in AVT(O) was similar to AVT(R), but the difference is that large solid particles of Fe₂O₃ cover the outermost oxide film, which prevents the oxide film from being taken away by the flowing solution. In consequence, the degree of corrosion sustained by the tube walls is lowest in the case of AVT(O).

The results can provide reference for reducing the high temperature corrosion of metal in the actual operation.

The purpose of this paper is to investigate the relationship between corporate governance and earnings opacity in China.

Two corporate governance mechanisms form the basis of the analysis: 1) the board of directors and 2) the external audit function. OLS regression analysis is employed on a large sample from 2000 to 2014 with 20,235 firm-year observations.

Corporate governance is found to be associated with reduced levels of earnings opacity for Chinese listed companies. Furthermore, the association between corporate governance and reduced levels of earnings opacity strengthened after the implementation of various key reforms.

Chinese regulators are advised to proceed with caution as not all Western approaches to corporate governance are transferrable to the Chinese setting.

This study contributes to the literature by analyzing broad latent constructs of corporate governance in addition to individual observable dimensions in order to reveal that various key reforms have been successful in strengthening the link between governance and reporting quality for Chinese listed companies.

The railway signal equipment failure diagnosis is a vital element to keep the railway system operating safely. One of the most difficulties in signal equipment failure diagnosis is the uncertainty of causality between the consequence and cause for the accident. The traditional method to solve this problem is based on Bayesian Network, which needs a rigid and independent assumption basis and prior probability knowledge but ignoring the semantic relationship in causality analysis. This paper aims to perform the uncertainty of causality in signal equipment failure diagnosis through a new way that emphasis on mining semantic relationships.

This study proposes a deterministic failure diagnosis (DFD) model based on the question answering system to implement railway signal equipment failure diagnosis. It includes the failure diagnosis module and deterministic diagnosis module. In the failure diagnosis module, this paper exploits the question answering system to recognise the cause of failure consequences. The question answering is composed of multi-layer neural networks, which extracts the position and part of speech features of text data from lower layers and acquires contextual features and interactive features of text data by Bi-LSTM and Match-LSTM, respectively, from high layers, subsequently generates the candidate failure cause set by proposed the enhanced boundary unit. In the second module, this study ranks the candidate failure cause set in the semantic matching mechanism (SMM), choosing the top 1st semantic matching degree as the deterministic failure causative factor.

Experiments on real data set railway maintenance signal equipment show that the proposed DFD model can implement the deterministic diagnosis of railway signal equipment failure. Comparing massive existing methods, the model achieves the state of art in the natural understanding semantic of railway signal equipment diagnosis domain.

It is the first time to use a question answering system executing signal equipment failure diagnoses, which makes failure diagnosis more intelligent than before. The EMU enables the DFD model to understand the natural semantic in long sequence contexture. Then, the SMM makes the DFD model acquire the certainty failure cause in the failure diagnosis of railway signal equipment.

The forest products processing industry is a key component of the forestry economy, and the level of companies’ operating efficiency directly affects its profitability and market competitiveness.

In order to deeply study the operation status of forest product processing industry, this paper takes the panel data of 70 listed forest product processing companies from 2015 to 2022 as the basis, and adopts BBC, CCR and DEA-Malmquist models to measure the operating efficiency of these companies. Meanwhile, the Tobit model is applied to deeply explore the impact of innovation input on operating efficiency.

The results of the paper show that: (1) the overall operating efficiency of listed forest product processing companies performs well, and the improvement of technology level promotes the growth of total factor productivity; (2) innovation input plays a significant positive role in listed forest product processing companies, which positively affects the operating efficiency.

A scientific and reasonable evaluation of the operating efficiency of listed forest product companies is of great practical significance to the development of the forestry industry The study of forest product processing industry is of key significance to the social economy.

This paper explores the improvement of production and operation efficiency of forest products processing enterprises for the purpose of in-depth analysis of the current situation of China's forest products processing enterprises, which is conducive to improving the innovation and operation efficiency of China's forest products processing enterprises, and realizing the high-quality development of China's forest products processing industry.

This study aims to explore the audit quality supplied by the Big 4, large indigenous Chinese (LIC) and five largest second-tier international network (Tier 2) audit firms in China during the second phase of their audit market development.

Ordinary least squares regression is used on an archival sample of firm-year observations. Endogeneity and self-selection bias are addressed by creating a propensity score matched sample and using two-stage regression with the inverse Mills’ ratio.

Strong evidence is found for higher levels of actual audit quality for the Big 4 relative to both LIC and Tier 2 audit firms. Weak evidence is found regarding the audit quality superiority of Tier 2 relative to LIC audit firms. Furthermore, the actual audit quality differential between the Big 4 relative to the LIC and Tier 2 firms widens after adopting International Financial Reporting Standards, which is contrary to the intention of Chinese regulators.

To the best of the authors’ knowledge, this is the first known empirical study to trisect Big N and non-Big N audit firm proxies into the Big 4, LIC and Tier 2. Currently, only qualitative studies have fully appreciated the unique regulatory roles of these three firm structures in developing China’s audit market, which reflect tensions between reliance on foreign expertise and self-determination. In addition, this study adds to the ongoing global dialogue on Tier 2 as an alternative to the Big 4 and the benefits of international accounting network membership.