Intelligent Manufacturing Technology in the Steel Industry of China: A Review

A study of the impact of digital technology on industrial ecologisation in the Yellow River Basin of China

The Yellow River Basin is an important ecological barrier and economic core area in China, with problems such as fragile ecological environment and ecosystem degradation, and promoting industrial ecological transformation in resource cities is an important way to protect and improve the ecological and logical environment of the Yellow River Basin. Using panel data of 35 resource-based cities in the Yellow River Basin from 2012 to 2021, the impact of digital technology on industrial colonisation is empirically explored. The study finds (1) digital technology has a driving effect on the industrial ecological transformation of resource-based cities in the Yellow River Basin, and can be a new production tool to stimulate economic vitality; there is obvious regional heterogeneity in the impact of digital technology on industrial ecology, which significantly promotes the industrial ecological transformation of mid-stream and declining resource-based cities, and the facilitating effect is more obvious for declining resource-based cities. (2) From the moderating effect, fiscal decentralisation positively moderates the non-linear relationship between digital technology and industrial ecology. (3) From the perspective of threshold effect, the impact of digital technology on industrial ecologisation has a double threshold effect based on fiscal decentralisation, i.e. at the early stage of digital technology development, a reasonable degree of fiscal decentralisation can significantly promote the industrial ecological transformation of resource cities, but after the development of digital technology to a certain extent, the impact of fiscal decentralisation on industrial ecologisation will be gradually weakened, and will even bring negative effects to industrial transformation. Therefore, improving the development system of digital technology, giving the government moderate financial autonomy, and at the same time adhering to the local conditions and exploring the ecological development road in line with the characteristics of resource cities in the Yellow River Basin have positive significance for the industrial ecological transformation of resource cities in the Yellow River Basin.

A Self-Supervised Model Based on CutPaste-Mix for Ductile Cast Iron Pipe Surface Defect Classification

Online surface inspection systems have gradually found applications in industrial settings. However, the manual effort required to sift through a vast amount of data to identify defect images remains costly. This study delves into a self-supervised binary classification algorithm for addressing the task of defect image classification within ductile cast iron pipe (DCIP) images. Leveraging the CutPaste-Mix data augmentation strategy, we combine defect-free data with enhanced data to input into a deep convolutional neural network. Through Gaussian Density Estimation, we compute anomaly scores to achieve the classification of abnormal regions. Our approach has been implemented in real-world scenarios, involving equipment installation, data collection, and experimentation. The results demonstrate the robust performance of our method, in both the DCIP image dataset and practical field application, achieving an impressive 99.5 AUC (Area Under Curve). This presents a cost-effective means of providing data support for subsequent DCIP surface inspection model training.

Linking circular economy model and green supply chain practices to shape environmental performance: case of Vietnam

The circular economy (SE) is the foremost element for environmental improvement that reduces wastage and enhances production. This aspect requires the focus of new researchers and experienced policymakers. Hence, the current research examines the impact of SE practices such as internal environmental management (IEM), eco-design, and internal recovery on the SE targeted performance, such as environmental performance in Vietnam. The research also investigates the moderating role of environmental-oriented supply chain (SC) practices such as green purchases among IEM, eco-design, internal recovery, and environmental performance in Vietnam. The research collected the data from the respondents using survey questionnaires. The research also investigates the association among variables using smart-PLS. The outcomes revealed that the IEM, eco-design, and internal recovery are positively associated with environmental performance. The outcomes also exposed that the green purchases significantly moderates among IEM, eco-design, internal recovery, and environmental performance. The research guides the regulators in establishing regulations related to achieve the high SE targeted performance, such as environmental performance using circular economy practices such as IEM, eco-design, and internal recovery.