Search results

This research seeks to undertake a comparative study of Chinese distribution centers (DCs) with UK DCs in order to explore the relationship between the supply chain, logistics and distribution functions, and the gap between the countries. The study has been undertaken in light of Chinese corporate standardization programs in distribution channels. The main goal of the standardization programs has been to create efficient supply chains to be able to control the flow of information, capital, product and other resources. The focus of the study was Fujian Province where the standardization program has meant that functional areas such as marketing and distribution are measured by key performance indicators (KPI), under specific evaluation keys. The study highlights benchmarked KPIs where supply chain entrepreneurship can be brought to bear.

The method used in this research is quantitative via a small scale sample. Questionnaires were sent to Chinese DCs in Fujian Province with additional quantitative information sought through telephone follow‐up.

The data have been analyzed and compared to UK DCs for inventory level, order lead‐times, customer segmentation, value‐added activities, and floor area utilization. DCs are a long way from internationally competitive best practice across complex product categories. This provides opportunity for entrepreneurial third party inventory storage and management. DCs also exhibits low transportation efficiency due to low vehicle loading factors, also affecting DC order lead‐time efficiency and value‐added activities. There is opportunity here for entrepreneurial activity in offering efficient (lean) and responsive (agile) third party transport services. There is also evidence of poor process management implying opportunity for the application of entrepreneurial consulting capability to resource and reengineer end‐end process chains.

The research generalisability is limited due its small scale sample in a single Chinese province.

Despite a modernization program the implications of this study are that Chinese DCs are not ready for traditional international competition, but in the short‐term entrepreneurs may be able to design sustainable lean and agile supply chains that are at least as good as those in the UK.

The study's originality is its comparative benchmark of Chinese with UK DCs.

Continuous annealing (CA) units usually lack a physical shapemeter; consequently, real-time display and closed-loop control of the strip shape are impossible to achieve.

A shape model for the CA process is established in this study. Specifically, a virtual shapemeter and closed-loop control system based on the advanced parameter acquisition system and information transmission of CA units are developed in C++ programming language. This system realises real-time dynamic shape display, closed-loop control and shape prediction by collecting raw data of steel coils and parameters during CA.

Field test results show that the shape predicted by the virtual shapemeter coincides with the measured shape by over 90 per cent, which fully meets the precision requirement of industrial applications.

Moreover, shape quality is effectively improved without increasing hardware investments.

This paper aims to present a set of processes for obtaining the global spraying trajectory of a cold spraying robot on a complex surface.

The complex workpiece surfaces in the project are first divided by triangular meshing. Then, the geodesic curve method is applied for local path planning. Finally, the subsurface trajectory combination optimization problem is modeled as a GTSP problem and solved by the ant colony algorithm, where the evaluation scores and the uniform design method are used to determine the optimal parameter combination of the algorithm. A global optimized spraying trajectory is thus obtained.

The simulation results show that the proposed processes can achieve the shortest global spraying trajectory. Moreover, the cold spraying experiment on the IRB4600 six-joint robot verifies that the spraying trajectory obtained by the processes can ensure a uniform coating thickness.

The proposed processes address the issue of different parameter combinations, leading to different results when using the ant colony algorithm. The two methods for obtaining the optimal parameter combinations can solve this problem quickly and effectively, and guarantee that the processes obtain the optimal global spraying trajectory.

The application of thermal barrier coatings (TBCs) allows aero-engine blades to operate at higher temperatures with higher efficiency. The preparation of the TBCs increases the surface roughness of the blade, which impacts the thermal cycle life and thermal insulation performance of the coating. To reduce the surface roughness of blades, particularly the blades with small size and complex curvature, this paper aims to propose a method for industrial robot polishing trajectory planning based on on-site measuring point cloud.

The authors propose an integrated robotic polishing trajectory planning method using point cloud processing technical. At first, the acquired point cloud is preprocessed, which includes filtering and plane segmentation algorithm, to extract the blade body point cloud. Then, the point cloud slicing algorithm and the intersection method are used to create a preliminary contact point set. Finally, the Douglas–Peucker algorithm and pose frame estimation are applied to extract the tool-tip positions and optimize the tool contact posture, respectively. The resultant trajectory is evaluated by simulation and experiment implementation.

The target points of trajectory are not evenly distributed on the blade surface but rather fluctuate with surface curvature. The simulated linear and orientation speeds of the robot end could be relatively steady over 98% of the total time within 20% reduction of the rest time. After polishing experiments, the coating roughness on the blade surface is reduced dramatically from Ra 7–8 µm to below Ra 1.0 µm. The removal of the TBCs is less than 100 mg, which is significantly less than the weight of the prepared coatings. The blade surface becomes smoothed to a mirror-like state.

The research on robotic polishing of aero-engine turbine blade TBCs is worthwhile. The real-time trajectory planning based on measuring point cloud can address the problem that there is no standard computer-aided drawing model and the geometry and size of the workpiece to be processed differ. The extraction and optimization of tool contact points based on point cloud features can enhance the smoothness of the robot movement, stability of the polishing speed and performance of the blade surface after polishing.

During the process of the robotic grinding and polishing operations on aero-engine blades, the key problem of calibration error lies in fixture error and uneven margin. To solve this problem, this paper aims to propose a novel method to achieve rapid online calibration of the workpiece coordinate system through laser-based measurement techniques.

The authors propose a calibration strategy based on point cloud registration algorithm. The main principle is presented as follows: aero blade mounted on clamping end-effector is hold by industry robot, the whole device is then scanned by a 3D laser scanner to obtain its surface point cloud, and a fast segmentation method is used to acquire the point cloud of the workpiece. Combining Super4PCS algorithm with trimmed iterative closest point, we can align the key points of the scanned point cloud and the sampled points of the blade model, thus obtaining the translation and rotation matrix for calculating the workpiece coordinate and machining allowance. The proposed calibration strategy is experimentally validated, and the positioning error, as well as the margin distribution, is finally analyzed.

The experimental results show that the algorithm can well accomplish the task of cross-source, partial data and similar local features of blade point cloud registration with high precision. The total time spent on point cloud alignment of 100,000 order of magnitude blade is about 4.2 s, and meanwhile, the average point cloud alignment error is reduced to below 0.05 mm.

An improved point cloud registration method is proposed and introduced into the calibration process of a robotic system. The online calibration technique improves the accuracy and efficiency of the calibration process and enhances the automation of the robotic grinding and polishing system.

H₂O, CO₂ and CO are three main species in combustion systems which have high volume fractions. In addition, soot has strong absorption in the infrared band. Thus, H₂O, CO₂, CO and soot may take important roles in radiative heat transfer. To provide calculations with high accuracy, all of the participating media should be considered non-gray media. Thus, the purpose of this paper is to study the effect of non-gray participating gases and soot on radiative heat transfer in an inhomogeneous and non-isothermal system.

To solve the radiative heat transfer, the fluid flow as well as the pressure, temperature and species distributions were first computed by FLUENT. The radiative properties of the participating media are calculated by the Statistical Narrow Band correlated K-distribution (SNBCK), which is based on the database of EM2C. The calculation of soot properties is based on the Mie scattering theory and Rayleigh theory. The radiative heat transfer is calculated by the discrete ordinate method (DOM).

Using SNBCK to calculate the radiative properties and DOM to calculate the radiative heat transfer, the influence of H₂O, CO₂, CO and soot on radiation heat flux to the wall in combustion system was studied. The results show that the global contribution of CO to the radiation heat flux on the wall in the kerosene furnace was about 2 per cent, but that it can reach up to 15 per cent in a solid fuel gasifier. The global contribution of soot to the radiation heat flux on the wall was 32 per cent. However, the scattering of soot has a tiny influence on radiation heat flux to the wall.

This is the first time H₂O, CO₂, CO and the scattering of soot were all considered simultaneously to study the radiation heat flux in combustion systems.

Prefabricated technology is gradually being applied to the construction of subway stations due to its characteristic of mechanization. However, the prefabricated subway station in China is in the initial stage of development, which is prone to construction safety issues. This study aims to evaluate the construction safety risks of prefabricated subway stations in China and formulate corresponding countermeasures to ensure construction safety.

A construction safety risk evaluation index system for the prefabricated subway station was established through literature research and the Delphi method. Furthermore, based on the structure entropy weight method, matter-element theory and evidence theory, a hybrid evaluation model is developed to evaluate the construction safety risks of prefabricated subway stations. The basic probability assignment (BPA) function is obtained using the matter-element theory, the index weight is calculated using the structure entropy weight method to modify the BPA function and the risk evaluation level is determined using the evidence theory. Finally, the reliability and applicability of the evaluation model are verified with a case study of a prefabricated subway station project in China.

The results indicate that the level of construction safety risks in the prefabricated subway station project is relatively low. Man risk, machine risk and method risk are the key factors affecting the overall risk of the project. The evaluation results of the first-level indexes are discussed, and targeted countermeasures are proposed. Therefore, management personnel can deeply understand the construction safety risks of prefabricated subway stations.

This research fills the research gap in the field of construction safety risk assessment of prefabricated subway stations. The methods for construction safety risk assessment are summarized to establish a reliable hybrid evaluation model, laying the foundation for future research. Moreover, the construction safety risk evaluation index system for prefabricated subway stations is proposed, which can be adopted to guide construction safety management.

Laser powder bed fusion (LPBF) can be used to fabricate complex extrusion die without the limitation of structures. Layer-by-layer processing leads to differences in microstructures and wear properties. This study aims to investigate the microstructure evolution and effects of tungsten carbide (WC) on the wear properties of LPBF-printed 18Ni300.

Economical spherical granulation-sintering-deoxygenation (GSD) WC-reinforced 18Ni300 steel matrix composites were produced by LPBF from powder mixtures of WC and 18Ni300. The effects of WC contents on anisotropic microstructures and wear properties of the composites were investigated.

The relative density is more than 99% for all the composites except 25% WC/18Ni300 composite. The grain sizes distributed on the top cross-section are smaller than those on the side cross-section. After adding WC particles, more high-angle grain boundaries and larger Schmid factor generate, and deformed grains decrease. With increasing WC contents, the hardness first decreases and then increases but the wear volume loss decreases. The side cross-section of the composite has higher hardness and better wear resistance. The 18Ni300 exhibits adhesive wear accompanying with abrasive wear, while plowing and fatigue wear are the predominant wear mechanisms of the composites.

Economical spherical GSD WC particles can be used to improve the wear resistance. The novel WC/18Ni300 composites are suitable for the application under the abrasive wear condition with low stress.

The traditional vision system cannot automatically adjust the feature point extraction method according to the type of welding seam. In addition, the robot cannot self-correct the laying position error or machining error. To solve this problem, this paper aims to propose a hierarchical visual model to achieve automatic arc welding guidance.

The hierarchical visual model proposed in this paper is divided into two layers: welding seam classification layer and feature point extraction layer. In the welding seam classification layer, the SegNet network model is trained to identify the welding seam type, and the prediction mask is obtained to segment the corresponding point clouds. In the feature point extraction layer, the scanning path is determined by the point cloud obtained from the upper layer to correct laying position error. The feature points extraction method is automatically determined to correct machining error based on the type of welding seam. Furthermore, the corresponding specific method to extract the feature points for each type of welding seam is proposed. The proposed visual model is experimentally validated, and the feature points extraction results as well as seam tracking error are finally analyzed.

The experimental results show that the algorithm can well accomplish welding seam classification, feature points extraction and seam tracking with high precision. The prediction mask accuracy is above 90% for three types of welding seam. The proposed feature points extraction method for each type of welding seam can achieve sub-pixel feature extraction. For the three types of welding seam, the maximum seam tracking error is 0.33–0.41 mm, and the average seam tracking error is 0.11–0.22 mm.

The main innovation of this paper is that a hierarchical visual model for robotic arc welding is proposed, which is suitable for various types of welding seam. The proposed visual model well achieves welding seam classification, feature point extraction and error correction, which improves the automation level of robot welding.

At present, the enzyme washing process is widely used in hemp garment in the industry. However, it has many disadvantages. First, it is inefficient and labor-intensive, which can only be produced in small quantities and will take much time for workers to check. Second, its cost is high. The strength loss of the garment is up to 20 percent, with a bad damage. Presently, the enzyme washing process of the gray fabric is not industrialized. The purpose of this paper is to obtain a stable and efficient process for the enzyme washing of the gray fabric.

The whiteness, weight loss rate, strength, dyeing property and fabric style of enzyme washed gray fabrics were studied.

The results showed that the enzyme treated fabric has soft handle, smooth surface, good elasticity and high levelness, as well as low strength reduction rate under the optimized condition of bath ratio of 1:12, cellulase dosage of 0.3 percent, pectinase dosage of 1 g/L, treatment temperature of 55°C, treatment time of 80 min and pH of 6.

First, the process is environment friendly, green and sustainable and, second, it will make the industrialization of the enzyme washing process of gray fabrics, with a high commercial value.