Search results

The purpose of this paper is to develop a topology optimization algorithm considering natural frequencies.

To incorporate natural frequency as design criteria of shell-infill structures, two types of design models are formulated: (1) type I model: frequency objective with mass constraint; (2) type II model: mass objective with frequency constraint. The interpolation functions are constructed by the two-step density filtering approach to describe the fundamental topology of shell-infill structure. Sensitivities of natural frequencies and mass with respect to the original element densities are derived, which will be used for both type I model and type II model. The method of moving asymptotes is used to solve both models in combination with derived sensitivities.

Mode switching is one of the challenges faced in eigenfrequency optimization problems, which can be overcome by the modal-assurance-criterion-based mode-tracking strategy. Furthermore, a shifting-frequency-constraint strategy is recommended for type II model to deal with the unsatisfactory topology obtained under direct frequency constraint. Numerical examples are systematically investigated to demonstrate the effectiveness of the proposed method.

In this paper, a topology optimization method considering natural frequencies is proposed by the author, which is useful for the design of shell-infill structures to avoid the occurrence of resonance in dynamic conditions.

This thesis deeply studies the impact mechanism of digital service trade on the high-quality development of the manufacturing industry from the aspects of technological innovation and industrial structure.

In this thesis, 40 countries from 2010 to 2020 were selected as samples, and the panel fixed-effect model and intermediary effect model were used to empirically analyze the impact path of digital service trade on the high-quality development of global manufacturing.

Overall, digital service trade has a positive impact on the high-quality development of the global manufacturing industry. Through the analysis of the intermediary effect mechanism, it is found that digital service trade can further positively affect the high-quality development of the global manufacturing industry by promoting technological innovation and industrial structure upgrading.

Based on the empirical results, targeted countermeasures and suggestions are given in this paper.

Through the test of national heterogeneity, it is found that in developing countries, digital service trade mainly acts on the high-quality development of the manufacturing industry by promoting industrial structure upgrading.

In developed countries, digital service trade mainly promotes the high-quality development of manufacturing through technological innovation; from the perspective of industry heterogeneity, the three service industries of information and communication technology (ICT), other business services and property have the intermediary effect of technological innovation and industrial structure.

This manuscript suggests that trade in digital services should be promoted as a national trade priority.

Supply chains, as prototypical uncertain systems, are crucial for national security and socioeconomic development. Grey system theory (GST) is an effective tool for addressing uncertainties and has played a pivotal role in related research within the supply chain domain. This study aims to systematically summarize the research achievements and knowledge structures pertaining to GST in supply chain studies. Current and potential research hotspots are also analyzed.

CiteSpace is used to conduct a bibliometric analysis of 1,617 articles sourced from the Web of Science (WOS). The analysis aims to summarize the current state of research and the knowledge structure in the field. A strategic diagram incorporating two data indicators, namely, novelty and concern, is constructed based on keyword clustering to identify and analyze current and potential research hotspots.

Studies utilizing GST to guide supply chain practices have attracted the interest of scholars from 205 research institutions across 85 countries and regions globally, which earned recognition from 183 high-level academic journals. In this field, the School of Economics and Management at Nanjing University of Aeronautics and Astronautics stands out as a core research institution, with Professor Deng Julong, who is the founder of GST, being the most frequently cited scholar. Current research hotspots are complex equipment supply chains, drivers and challenges in supply chain management, supply chain risk management, closed-loop supply chain and supply chain operation in the big data era. In addition, emerging research hotspots include digital and intelligent logistics technology, sustainable supplier management, determinants and flexibility of supply chain contracts, supply chain strategy, purchase management, grey prediction of demand and consumption, grey forecasting and economy efficiency, China-specific issues and grey model construction.

The bibliometric analysis reveals the current state and knowledge structure of research in this field. Previous studies on research hotspots have primarily relied on subjective judgments, which lacked empirical data support. This study constructs a strategic diagram incorporating two data indicators, namely, novelty and concern, to provide a more objective and reliable analysis of research hotspots.

The purpose of this paper is to present a detection method based on computer vision for automatic flexible printed circuit (FPC) defect detection.

This paper proposes a new method of watershed segmentation based on morphology. A dimensional increment matrix calculation method and an image segmentation method combined with a fuzzy clustering algorithm are provided. The visibility of the segmented image and the segmentation accuracy of a defective image are guaranteed.

Compared with the traditional one, the segmentation result obtained in this study is superior in aspects of noise control and defect segmentation. It completely proves that the segmentation method proposed in this study is better matches the requirements of FPC defect extraction and can more effectively provide the segmentation result. Compared with traditional human operators, this system ensures greater accuracy and more objective detection results.

The extraction of FPC defect characteristics contains some obvious characteristics as well as many implied characteristics. These characteristics can be extracted through specific space conversion and arithmetical operation. Therefore, more images are required for analysis and foresight to establish a more widely used FPC defect detection sorting algorithm.

This paper proposes a new method of watershed segmentation based on morphology. It combines a traditional edge detection algorithm and mathematical morphology. The FPC surface defect detection system can meet the requirements of online detection through constant design and improvement. Therefore, human operators will be replaced by machine vision, which can preferably reduce the production costs and improve the efficiency of FPC production.

Unlike traditional industries, the e-cigarette is an epoch-making innovative product originating in China and occupying an absolute competitive advantage in the international market. The traditional A-U model describes the laws and characteristics of technological innovation in developed countries. In contrast, the inverse A-U model depicts the process of “secondary innovation” in late-developing countries through digestion and absorption. This paper aims to find out that if the e-cigarette, as a “first innovation” industry in a late-developing country, conform to the A-U model or conform to the “inverse A-U model”.

This paper takes the patent data of e-cigarettes from 2004 to 2021 as the research object, and uses Python’s Jieba segment words to divide product innovation and process innovation, and then uses statistical analysis methods to conduct empirical analyses on these data.

Thus, an improved A-U model suitable for the e-cigarette industry is proposed. In this model, product innovation in the e-cigarette industry appeared earlier than process innovation, but the synchronous development of product and process innovation is not lagging. The improved A-U model in the e-cigarette industry is not only different from the traditional A-U model but also does not conform to the inverse A-U model.

It is conducive to expanding and clarifying the theoretical contribution and applicable boundaries of the A-U model and has sparked thinking and exploration of the A-U model in e-cigarettes and emerging industries.

On this basis, suggestions on the development path and countermeasures of the e-cigarette industry are put forward.

Based on the e-cigarette industry, this paper takes patents as the research object and provides the method of dividing product innovation and process innovation, and proposes an A-U model suitable for the e-cigarette industry on this basis. By comparing the traditional A-U model with the inverse A-U model in latecomer countries, the background and causes of e-cigarette A-U model heterogeneity are analyzed from different stages and overall morphology. Based on this, the heterogeneity characteristics of e-cigarette innovation are summarized and sorted out.

The purpose of this paper is to study the functionality of additively manufactured (AM) parts, mainly depending on their dimensional accuracy and surface finish. However, the products manufactured using AM usually suffer from defects like roughness or uneven surfaces. This paper discusses the various surface quality improvement techniques, including how to reduce surface defects, surface roughness and dimensional accuracy of AM parts.

There are many different types of popular AM methods. Unfortunately, these AM methods are susceptible to different kinds of surface defects in the product. As a result, pre- and postprocessing efforts and control of various AM process parameters are needed to improve the surface quality and reduce surface roughness.

In this paper, the various surface quality improvement methods are categorized based on the type of materials, working principles of AM and types of finishing processes. They have been divided into chemical, thermal, mechanical and hybrid-based categories.

The review has evaluated the possibility of various surface finishing methods for enhancing the surface quality of AM parts. It has also discussed the research perspective of these methods for surface finishing of AM parts at micro- to nanolevel surface roughness and better dimensional accuracy.

This paper represents a comprehensive review of surface quality improvement methods for both metals and polymer-based AM parts.