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This paper aims to investigate the electrochemical corrosion behavior of a five-layer Al alloy composites (4343/4047/3003/4047/4343) with a thickness of 0.2 mm in NaCl solution.

Electrochemical impedance spectroscopy, polarization curve and morphology analyses were used to study the corrosion behavior of the Al alloy composites from cross-sectional and plane directions.

The corrosion resistance of the surface from the plane direction was higher than that from the cross sections. Si-enrich particles were observed in the outer 4047/4343 layer, and AlFeCuMnBi phases were identified in the core 3003 layer. The galvanic coupling between the Si-enrich particle and the Al matrix accelerated the dissolution Al matrix.

This work lays the experimental foundation for corrosion mechanism of the Al alloy composite plate.

Before the turn of the century, taking overseas students was more about a diplomatic issue dominated by the state in China, for which reason this section is relatively independent within the higher education system. However, evidence from a series of new policy documents and their impacts suggests that international student mobility (ISM) has been intensively shaped by the central government in the desire to promote its national strategy, namely the belt and road initiative. ISM policy, although with a significant proportion marketized, was introduced for a clear purpose of cultural diplomacy. The paper aims to discuss these issues.

Looking beyond the debate of market-driven vs state-dominated, this paper attempts to provide a thorough understanding of this changing pattern based on examination of key changes of policy statements along with official data analysis.

This paper argues that the new pattern must be understood against a context of a hierarchy of higher education institutes in contemporary China: a sector led by a small number of prestigious universities generously funded by the central government with a large number of ordinary universities underfunded and eager to generate income. Prestigious institutes enroll international students to satisfy performance indicators listed by policies like “Double First-rate”; other universities, benefiting from the reputation and momentum generated by the top ones, take self-funded students for profit.

By making good use of both performance indicators and market motives, the country managed to move a state-dominated ISM policy in the twentieth century into the existing state-steering marketization model and made China a major destination for overseas study.

This paper aims to identify important factors in green public procurement (GPP) implementation and then to clarify how these factors affect GPP implementation.

The authors applied the Delphi method first and then conducted a focused and constrained multiple case study at 18 government procurement centers across China.

The authors identified four clusters of factors for successful GPP implementation: more clear, consistent and operational policy goals; a nation-wide green procurement campaign to enhance social capital and cultural resources; promoting staff’s ethics, professionalism, capacity and knowledge; and establishing checks and balances among organizations involved in the whole purchasing process.

GPP can significantly improve environmental protection and sustainable development.

Based on key insights from systems theory and agency theory, the authors emphasize that GPP implementation must take down its own functional silos and adopt a process approach across organizational tiers to synchronize human resource based and inter-organizational capabilities into a unified whole through information sharing, communications and collaboration.

The purpose of this study which resulted in this work is to propose an optimization method of sensors distribution for structural impact localization.

This paper presents a multi-objective optimization study of a novel sensors distribution technique, where two optimization objective functions are considered: sensors number and sensors location optimization performance index. In addition, the finite element analysis, the time-frequency transform and the principal component analysis are combined to quantize the above objective functions. The non-dominated sorting genetic algorithm II (NSGA-II) is used to acquire Pareto solutions.

The effectiveness of this method is validated through a prototype laboratory called the piezoelectric intelligent structure where promising results are obtained.

An optimization method of this novel sensors distribution technique is built and produced a set of efficiency solutions for the real-world problem of impact localization where two conflicting objectives are involved.

The purpose of this paper is to study China's strategy of purchasing resource commodities in international markets, what the Chinese government can do to change the current disorderly import system and how China can build purchase alliances to win in international bargaining.

A narrative inquiry is used to analyze China's strategy of purchasing resource commodities in international markets, and a game theory model is employed to study different manufacturers’ attitudes toward united negotiation and purchase alliances and the influence of government regulation on their attitude.

The paper finds that the “paradox of China's great market” in importing resource commodities is due to the constant increase of China's demand and China's disorderly import system. Government regulation will influence manufacturers’ attitudes toward united negotiation and purchase alliances. Purchase alliances may be the only effective strategy that can help China avoid price risk in international markets, because Chinese corporations cannot control foreign mines and the Chinese futures market cannot mature in a limited, short period.

The analysis in the paper lacks sufficient theory and experiences. The game theory model is very simple and is not directly linked with purchase alliances. Owing to literature constraints, there are few foreign experiences about building purchase alliances.

This paper advises the Chinese government and corporations what to do about the high import price of resource commodities and how to build purchase alliances to win in international bargaining, for example improving import regulations, recomposing the united negotiation group, forming a responsibility system and so on.

The paper forms an integrated agenda for China to build purchase alliances for importing resource commodities, and most policies could be carried out by the Chinese government immediately.

As an advanced manufacturing method, additive manufacturing (AM) technology provides new possibilities for efficient production and design of parts. However, with the continuous expansion of the application of AM materials, subtractive processing has become one of the necessary steps to improve the accuracy and performance of parts. In this paper, the processing process of AM materials is discussed in depth, and the surface integrity problem caused by it is discussed.

Firstly, we listed and analyzed the characterization parameters of metal surface integrity and its influence on the performance of parts and then introduced the application of integrated processing of metal adding and subtracting materials and the influence of different processing forms on the surface integrity of parts. The surface of the trial-cut material is detected and analyzed, and the surface of the integrated processing of adding and subtracting materials is compared with that of the pure processing of reducing materials, so that the corresponding conclusions are obtained.

In this process, we also found some surface integrity problems, such as knife marks, residual stress and thermal effects. These problems may have a potential negative impact on the performance of the final parts. In processing, we can try to use other integrated processing technologies of adding and subtracting materials, try to combine various integrated processing technologies of adding and subtracting materials, or consider exploring more efficient AM technology to improve processing efficiency. We can also consider adopting production process optimization measures to reduce the processing cost of adding and subtracting materials.

With the gradual improvement of the requirements for the surface quality of parts in the production process and the in-depth implementation of sustainable manufacturing, the demand for integrated processing of metal addition and subtraction materials is likely to continue to grow in the future. By deeply understanding and studying the problems of material reduction and surface integrity of AM materials, we can better meet the challenges in the manufacturing process and improve the quality and performance of parts. This research is very important for promoting the development of manufacturing technology and achieving success in practical application.

It was verified that the micro-texture in the front and back of the tool at the same time had a positive effect on improving the milling behavior and surface quality of the tool. The purpose of this study is to explore the rationality of simultaneous placement of micro-textures on the front and rear surfaces of ball-end milling cutters, analyze the influence of micro-texture parameters on tool milling behavior and workpiece surface quality, reveal its internal mechanism, and obtain the best micro-texture parameters by optimization.

First, the mechanism of micro-texture is studied based on the energy loss model. Second, the orthogonal experiment is designed to analyze the influence of micro-texture parameters on tool milling behavior and reveal its mechanism by combining simulation technology and cutting experiment. Finally, the parameters are optimized based on the artificial bee colony algorithm.

The results show that the simultaneous placement of micro-texture on the rake face and flank face of the tool has a positive effect on improving the milling behavior and surface quality of the tool. Taking milling force, tool wear and surface roughness as the evaluation criteria, the optimal parameter combination is obtained: the rake face micro-texture diameter is 50 µm, the distance from the micro-texture is 200 µm and the distance from the cutting edge is 110 µm; the diameter of the micro-textured flank is 40 µm, the distance from the micro-texture is 170 µm and the distance from the cutting edge is 130 µm.

Taking milling force, tool wear and surface roughness as the evaluation criteria, the optimal parameter combination is obtained: the rake face micro-texture diameter is 50 µm, the distance from the micro-texture is 200 µm and the distance from the cutting edge is 110 µm; the diameter of the micro-textured flank is 40 µm, the distance from the micro-texture is 170 µm and the distance from the cutting edge is 130 µm, which provides theoretical support for the further study of the micro-textured tool.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-01-2023-0022/

This paper aims to describe a three-dimensional mathematical and numerical model based on finite volume method to simulate the fluid dynamics in weld pool, droplet transfer and keyhole behaviors in the laser-MIG hybrid welding process of Fe36Ni Invar alloy.

Double-ellipsoidal heat source model and adaptive Gauss rotary body heat source model were used to describe electric arc and laser beam heat source, respectively. Besides, recoil pressure, electromagnetic force, Marangoni force, buoyancy as well as liquid material flow through a porous medium and the heat, mass, momentum transfer because of droplets were taken into consideration in the computational model.

The results of computer simulation, including temperature field in welded plate and velocity field in the fusion zone were presented in this article on the basis of the solution of mass, momentum and energy conservation equations. The correctness of elaborated models was validated by experimental results and this proposed model exhibited close correspondence with the experimental results with respect to weld geometry.

It lays foundation for understanding the physical phenomena accompanying hybrid welding and optimizing the process parameters for laser-MIG hybrid welding of Invar alloy.

Porosity is a commonly analyzed defect in the laser-based additive manufacturing processes owing to the enormous thermal gradient caused by repeated melting and solidification. Currently, the porosity estimation is limited to powder bed fusion. The porosity estimation needs to be explored in the laser melting deposition (LMD) process, particularly analytical models that provide cost- and time-effective solutions compared to finite element analysis. For this purpose, this study aims to formulate two mathematical models for deposited layer dimensions and corresponding porosity in the LMD process.

In this study, analytical models have been proposed. Initially, deposited layer dimensions, including layer height, width and depth, were calculated based on the operating parameters. These outputs were introduced in the second model to estimate the part porosity. The models were validated with experimental data for Ti6Al4V depositions on Ti6Al4V substrate. A calibration curve (CC) was also developed for Ti6Al4V material and characterized using X-ray computed tomography. The models were also validated with the experimental results adopted from literature. The validated models were linked with the deep neural network (DNN) for its training and testing using a total of 6,703 computations with 1,500 iterations. Here, laser power, laser scanning speed and powder feeding rate were selected inputs, whereas porosity was set as an output.

The computations indicate that owing to the simultaneous inclusion of powder particulates, the powder elements use a substantial percentage of the laser beam energy for their melting, resulting in laser beam energy attenuation and reducing thermal value at the substrate. The primary operating parameters are directly correlated with the number of layers and total height in CC. Through X-ray computed tomography analyses, the number of layers showed a straightforward correlation with mean sphericity, while a converse relation was identified with the number, mean volume and mean diameter of pores. DNN and analytical models showed 2%–3% and 7%–9% mean absolute deviations, respectively, compared to the experimental results.

This research provides a unique solution for LMD porosity estimation by linking the developed analytical computational models with artificial neural networking. The presented framework predicts the porosity in the LMD-ed parts efficiently.

Risk analysis is a critical investigation field for many sectors and organizations to maintain the information management reliable. Since mining is one of the riskiest sectors for both workers and management, comprehensive risk analysis should be carried out. The purpose of this paper is to explore comprehensively the undesired events that may occur during a particular process with their main reasons and to perform a risk analysis for these events, by developing a risk analysis methodology. For performing risk analysis, discovering and defining the potential accidents and incidents including their root causes are important contributions of the study as distinct from the related literature. The fuzzy approach is used substantially to obtain the important inferences about the hazardous process by identifying the critical risk points in the processes. In the scope of the study, the proposed methodology is applied to an underground chrome mine and obtaining significant findings of mining risky operations is targeted.

Fault tree analysis and fuzzy approach are used for performing the risk analysis. When determining the probability and the consequences of the events which are essential components for the risk analysis, expressions of the heterogeneous expert group are considered by means of the linguistic terms. Fault tree analysis and fuzzy approach present a quiet convenience solution together to specify the possible accidents and incidents in the particular process and determine the values for the basis risk components.

This study primarily presents a methodology for a comprehensive risk analysis. By implementing the proposed methodology to the underground loading and conveying processes of a chrome mine, 28 different undesired events that may occur during the processes are specified. By performing risk analysis for these events, it is established that the employee’s physical constraint while working with the shovel in the fore area, the falling of materials on employees from the chute and the scaling bar injuries are the riskiest undesired events in the underground loading and conveying process of the mine.

The proposed methodology provides a confidential and comprehensive method for risk analysis of the undesired events in a particular process. The capability of fault tree analysis for specifying the undesired events systematically and the applicability of fuzzy approach for converting the experts’ linguistic expressions to the mathematical values provide a significant advantage and convenience for the risk analysis.

The major contribution of this paper is to develop a methodology for the risk analysis of a variety of mining accidents and incidents. The proposed methodology can be applied to many production processes to investigate the dangerous operations comprehensively and find out the efficient management strategies. Before performing the risk analysis, determining the all possible accidents and incidents in the particular process using the fault tree analysis provides the effectiveness and the originality of the study. Also, using the fuzzy logic to find out the consequences of the events with experts’ linguistic expressions provides an efficient method for performing risk analysis.