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This study aimed to identify a specific taxonomy of entry modes for international construction contractors and to develop a decision-making mechanism based on case-based reasoning (CBR) to facilitate the selection of the most suitable entry modes.

According to the experience orientation of the construction industry, a CBR entry mode decision model was established, and based on successful historical cases, a two-step refinement process was carried out to identify similar situations. Then the validity of the model is proved by case analysis.

This study identified an entry mode taxonomy for international construction contractors (ICCs) and explored their decision-making mechanisms. First, a two-dimension model of entry mode for ICCs was constructed from ownership and value chain dimensions; seven common ICC entry modes were identified and ranked according to market commitment. Secondly, this study reveals the impact mechanism of the ICC entry mode from two aspects: the external environment and enterprise characteristics. Accordingly, an entry mode decision model is established.

Firstly, sorting out the categories of entry mode in the construction field, which provide an entry mode list for ICCs to select. Secondly, revealing the impact mechanism of ICC entry mode, which proposes a systematic decision-making system for the selection of ICC entry mode. Thirdly, constructing a CBR entry mode decision-making model from an empirical perspective, which offers tool support and reduces transaction costs in the decision-making process.

The study on entry modes for ICCs is still in the preliminary exploratory stage. The authors investigate the entry mode categories and decision-making mechanisms for ICCs based on Uppsala internationalization process theory. It widens the applied scope of Uppsala and promotes cross-disciplinary integration. In addition, the authors creatively propose a two-stage retrieval mechanism in the CBR model, which considers the order of decision variables. It refines the influence path of the decision variables on ICCs' entry mode.

In this work, the authors aim to provide a set of convenient methods for generating training data, and then develop a deep learning method based on point clouds to estimate the pose of target for robot grasping.

This work presents a deep learning method PointSimGrasp on point clouds for robot grasping. In PointSimGrasp, a point cloud emulator is introduced to generate training data and a pose estimation algorithm, which, based on deep learning, is designed. After trained with the emulation data set, the pose estimation algorithm could estimate the pose of target.

In experiment part, an experimental platform is built, which contains a six-axis industrial robot, a binocular structured-light sensor and a base platform with adjustable inclination. A data set that contains three subsets is set up on the experimental platform. After trained with the emulation data set, the PointSimGrasp is tested on the experimental data set, and an average translation error of about 2–3 mm and an average rotation error of about 2–5 degrees are obtained.

The contributions are as follows: first, a deep learning method on point clouds is proposed to estimate 6D pose of target; second, a convenient training method for pose estimation algorithm is presented and a point cloud emulator is introduced to generate training data; finally, an experimental platform is built, and the PointSimGrasp is tested on the platform.

Mg-Al powder mixture was used to manufacture Mg-Al alloy by laser powder bed fusion (LPBF) process. This study aims to investigate the influence of initial Al content and processing parameters on the formability, microstructure and consequent mechanical properties of the laser powder bed fused (LPBFed) component.

In this study, Al powder with different weight ratio ranged from 3 to 9 per cent was mixed with pure Mg powder, and the powder mixture was processed using different LPBF parameters. Microstructure and compressive properties of the LPBFed components were examined.

It was found that the presence of Al significantly modified the microstructure and improved the mechanical properties of the LPBFed components. Higher volume of ß-Al12Mg17 precipitates was produced at higher initial Al content and higher laser energy density. For this reason, the a-Mg was significantly refined and the compressive strength was improved. The highest yield compressive strength achieved was 279 MPa when using Mg-9 Wt. % Al mixture.

This work demonstrates that LPBF of Mg-Al powder mixture was a viable way to additively manufacture Mg-Al alloy. Both Al content and processing parameters can be modified to control the microstructure and mechanical properties of the LPBFed components.

The purpose of this study is to investigate the flexible dynamic characteristics about hydro-viscous drive providing meaningful insights into the credible speed-regulating behavior during the soft-start.

A comprehensive dynamic transmission model is proposed to investigate the effects of key parameters on the dynamic characteristics. To achieve a trade-off between the transmission efficiency and time proportion of hydrodynamic and mixed lubrication, a multi-objective optimization of friction pair system by genetic algorithm is presented to obtain the optimal combination of design parameters.

Decreasing the engagement pressure or the ratio of inner and outer radius, increasing the lubricating oil viscosity or the outer radius will result in the increase of time proportion of hydrodynamic and mixed lubrication, as well as the transmission efficiency and its maximum value. After optimization, main dynamic parameters including the oil film thickness, angular velocity of the driven disk, viscous torque and total torque show remarkable flexible transmission characteristics.

Both the dynamic transmission model and multi-objective optimization model are established to analyze the effects of main design parameters on the dynamic characteristics of hydro-viscous flexible drive.

During the 3D printing process, the model needs to add a support structure to ensure structural stability. Excessive support structure reduces printing efficiency and results in material cost. A flexible support platform for 3 D printing has been designed. It can form an external support structure to replace the original support structure. This paper aims to study the influence of a model’s build orientation on properties when the model is printed on the platform, aiming to provide users with suitable solutions.

A fitness function for estimating the support structure with a support length is constructed. The particle swarm optimization (PSO) algorithm is modified and applied to find the build orientation that minimizes the support structure. However, when the model is printed on the platform, the build orientation of the minimum support structure enhances the complexity of the working path, resulting in an increase of printing time, which needs to be avoided. This paper applies a multi-objective particle swarm optimization (MOPSO) algorithm to minimize the support structure while minimizing printing time. The Pareto solution is obtained by the algorithm.

It is found that the model that has the cantilever structure can reduce more support structure after optimization on the platform, when there is surface quality requirement. When there is no limit, the modified algorithm can minimize the support structure of each model. Considering support structure and printing time, the MOPSO algorithm can easily get optimization results to guide the practical work.

This paper optimizes the model’s build orientation on the flexible support platform by PSO, thereby reducing material cost and improving work efficiency.

The purpose of the paper is to assess the state of the business development services (BDS) market in Chengdu, with a view to identifying demand and/or supply side deficiencies, which public policy might help to address.

The data are drawn from two surveys undertaken in Chengdu between November 2005 and January 2006.

The research shows there are small firms that are active users of BDS, reflecting the emergence of non‐state owned enterprises in the city. The survey also shows evidence of unfulfilled latent demand, with a particular reference to sales and marketing advice and helping firms to access sources of finance. In addition, the survey of BDS providers shows that some are sensitive to the needs of small firms, although the latter are typically under‐represented in their client base.

The findings suggest that the BDS market in Chengdu is underdeveloped from a small business perspective, which can be illustrated by pointing to both demand‐ and supply‐side deficiencies. It can be argued that this is an important policy issue, if small enterprises are to fulfil their potential contribution to local economic development, particularly in relation to the development of non‐local sales.

This research adopts an “evidence‐based” approach to inform policy development.

Additive manufacturing based on arc welding is a fast and effective way to fabricate complex and irregular metal workpieces. Thin-wall metal structures are widely used in the industry. However, it is difficult to realize support-free freeform thin-wall structures. This paper aims to propose a new method of non-supporting thin-wall structure (NSTWS) manufacturing by gas metal arc welding (GMAW) with the help of a multi-degree of freedom robot arm.

This study uses the geodesic distance on the triangular mesh to build a scalar field, and then the equidistant iso-polylines are obtained, which are used as welding paths for thin-wall structures. Focusing on the possible problems of interference and the violent variation of the printing directions, this paper proposes two types of methods to partition the model mesh and generate new printable iso-polylines on the split meshes.

It is found that irregular thin-wall models such as an elbow, a vase or a transition structure can be deposited without any support and with a good surface quality after applying the methods.

The experiments producing irregular models illustrate the feasibility and effectiveness of the methods to fabricate NSTWSs, which could provide guidance to some industrial applications.

The main purpose of this paper is to create a suitable structure based on neutrosophic numbers to evaluate the safety performance in construction projects in such a way that the shortcomings can be highlighted with the reasoned measurement and possible strategies can be recommended.

Data envelopment analysis (DEA), which is a useful tool for performance appraisal, along with neutrosophic logic, which is one of the most complete tools for handling uncertainty phenomenon, has been used to evaluate the safety performance of construction projects. With this hybrid model, a new strategy is considered as an indicator for safety performance and comparisons are made between different units.

A total of 35 Chinese organizations with construction projects lasting between 1.5 and 2 years were selected for comparison. After processing the data into neutrosophic numbers and using the NN-DEA model, it can be found that projects that pay more attention to safety issues such as training and equipment are more efficient.

Since in the real world, there are uncertainties with different contradictions, and neutrosophical data can handle many of these challenges, using DEA model with neutrosophic numbers to evaluate the performance of construction projects from a safety perspective, can provide significantly better results. Therefore, considering that no study has been presented in this field so far, the authors will deal with this topic.

The project Climbing Robot Cell for Fast and Flexible Manufacture of Large Scale Structures seeks to modernise and take into the future the technology of the manufacture of large fixed welded structures. It creates a transportable manufacturing cell consisting of a team of cooperating climbing robot work tools whose activities are coordinated and integrated through a central intelligence. The purpose of this paper is to present a wheeled robot, called NDT robot, designed for the real time inspection of long weld lines simultaneously with the welding process.

Neodymium permanent magnets are used for adhesion, which are capable of producing a maximum adhesion pressure of 4 × 104 Nm⁻² at a 20 mm air gap. The strong neodymium magnets give the robot a high payload carrying capability. The arrangement of the magnet array increases its performance at large air gaps so that the robot has excellent capability to overcome obstacles, such as weld caps. The design of the wheeled robot with two sections jointed by a hinge joint has the advantage of high speed and good manoeuvrability, as well as working on curved surfaces and transferring between angled adjoining surfaces.

The NDT robot has been developed with the capability of climbing on steel walls carrying the specified payload and the ability to overcome the obstacles. The robot is also able to climb on curved surfaces with excellent manoeuvrability, and transfer between angled adjoining surfaces.

The arrangement of the magnet array enables the robot to retain a strong holding force at big air gap, so that the ability of the robot to overcome obstacles and work on curvatures is strengthened. The two‐section design improves the robot's performance on curvatures and enables it to transfer between angled adjoining surfaces.

This paper aims to consider a problem of assembly sensitivity in a multi-station assembly process. The authors focus on the assembly process of aircrafts, which includes cabins and inertial navigation system (INSs), and establish the assembly process state space model for their assembly sensitivity research.

To date, the process-related errors that cause large variations in key product characteristics remains one of the most critical research topics in assembly sensitivity analysis. This paper focuses on the unique challenges brought about by the multi-station system: a system-level model for characterizing the variation propagation in the entire process, and the necessity of describing the system response to variation inputs at both station-level and single fixture-level scales. State space representation is used to describe the propagation of variation in such a multi-station process, incorporating assembly process parameters such as fixture-locating layout at individual stations and station-to-station locating layout change.

Following the sensitivity analysis in control theory, a group of hierarchical sensitivity indices is defined and expressed in terms of the system matrices in the state space model, which are determined by the given assembly process parameters.

A case study of assembly sensitivity for a multi-station assembly process illustrates and validates the proposed methodology.