Advanced Industrial Research Articles

Geographic Distribution Characteristics and Influencing Factors for Industrial Heritage Sites in Italy Based on GIS

A comprehensive understanding of industrial legacy, considering its social, economic, and environmental aspects, is crucial for its preservation. This study scrutinizes 120 industrial heritage sites, investigating spatial–temporal patterns and influential factors. The aim is to provide a scientific basis for the conservation and management of the Italian industrial heritage. (1) The research underscores Italy’s industrial legacy’s tendency for clustering and uneven dispersion, prominently concentrated in the northern regions while notably sparse in the south. (2) Geographical advantages, a history of advanced industrialization, higher economic levels, greater population density, and supportive policies foster a concentration of industrial development and greater diversity of heritage types in the North. (3) The recommendations advocate for tailored conservation and management strategies tailored to the distinct characteristics of Italian industrial history. These strategies advocate for increased public involvement, reinforced legislative protection, and the promotion of tourism and cultural education to sustainably develop heritage assets. The findings and methodologies of this study can effectively identify the causes of the formation of the Italian industrial heritage, thereby offering a broader perspective to bolster its preservation and administration. It also provides a valuable reference for global industrial heritage preservation and management strategies.

A new type of high flexural strength micro-nano-composite ceramic tool material Ti(C,N)/WC/ZrO2 for integrated micro milling cutter

Ti(C,N) composites are widely applied in various advanced manufacturing industries. However, the intrinsic brittleness and relatively high metal content for Ti(C,N) composites significantly limit their further applications, especially in high-temperature and high-speed machining conditions. Herein, a new type of high flexural strength micro-nano-composite ceramic tool material Ti(C,N)/WC/ZrO2 for integrated micro milling cutter which will be used to mill difficult-to-machine material such as titanium alloy was proposed and developed successfully by hot press sintering technique under vacuum. The Ti(C,N) composites with low metal phase strengthened by nano-3Y-ZrO2 and micro-WC particles, the effect of compositions and sintering parameters on the mechanical properties and microstructure of the composite ceramic materials were systematically investigated. The results demonstrated that the Ti(C,N) composites with low metal phase containing 15 wt% nano-3Y-ZrO2 and 15 wt% micro-WC, sintered at 32 MPa and 1500 °C for 45 min had the optimal mechanical properties under vacuum and the flexural strength, Vicker's hardness, fracture toughness and relative density were 1501 ± 86 MPa, 19.97 ± 0.43GPa, 7.25 ± 0.76 MPa.m1/2 and 99.55%, respectively. Meanwhile, the superior mechanical properties of the Ti(C,N) composites with low metal binder phase could be achieved when sintered at higher temperatures and longer holding times compared to conventional cerments. Moreover, the toughening and strengthening mechanisms for Ti(C,N) composites with low metal phase are the synergistic effects of crack bridging, crack branching, crack deflection, pinning effect, particle pull-out, intragranular microstructure, transgranular and intergranular fracture. These toughening and strengthening mechanisms and the solid solution effects generated by the joint action of oxides and carbides could remarkably improve the properties for the Ti(C,N) composites. In this study, a novel insight on developing high-property Ti(C,N) composites was proposed, and it will make a significant contribution to material synthesis and design, application for cutting tools and composite ceramics investigations.

Laser Shock Peening: Fundamentals and Mechanisms of Metallic Material Wear Resistance Improvement.

With the rapid development of the advanced manufacturing industry, equipment requirements are becoming increasingly stringent. Since metallic materials often present failure problems resulting from wear due to extreme service conditions, researchers have developed various methods to improve their properties. Laser shock peening (LSP) is a highly efficacious mechanical surface modification technique utilized to enhance the microstructure of the near-surface layer of metallic materials, which improves mechanical properties such as wear resistance and solves failure problems. In this work, we summarize the fundamental principles of LSP and laser-induced plasma shock waves, along with the development of this technique. In addition, exemplary cases of LSP treatment used for wear resistance improvement in metallic materials of various nature, including conventional metallic materials, laser additively manufactured parts, and laser cladding coatings, are outlined in detail. We further discuss the mechanism by which the microhardness enhancement, grain refinement, and beneficial residual stress are imparted to metallic materials by using LSP treatment, resulting in a significant improvement in wear resistance. This work serves as an important reference for researchers to further explore the fundamentals and the metallic material wear resistance enhancement mechanism of LSP.

Preliminary Study of the Effect of pH on Ce, Nd, La, Pr Recovery from REOH Concentrate

The separation of uranium, thorium, and rare earth elements (REE) from monazite sand was carried out using the PLUTHO pilot plant facility. The REEs were produced in the form of hydroxide concentrates (REOH). Further separation process must be carried out to obtain high-purity elements for application in advanced industries such as polisher material for hard materials, infrared protective glass, and Ni-metal hydride batteries. The Major Element of REEs are Cerium (Ce), Lanthanum (La), Neodynium (Nd), and Praseodymium (Pr). Those elements can be separated by various methods such as fractional precipitation, extraction, ion exchange, and others. This research was carried out using the Fractional Precipitation method. Rare earth elements have chemical properties that permit ready dissolution and easy precipitation. The fractional precipitating reagent commonly used is NH4OH because it will not contaminate the precipitate due to the volatility of NH3. The parameter used in this preliminary study was pH from 4 to 9. The separation process was started with the dissolution of the REOH concentrate in a solution of HNO3 to obtain RE nitrate. After the dissolution process, oxidation and precipitation were carried out by the addition of KMnO4 as an oxidizing agent and Na2CO3 as a precipitating agent at pH 4 to obtain high recovery efficiency of cerium. The precipitation was pH varies continued by pH adjustment using NH4OH starting from pH 4 to pH 9 to separate La, Nd, and Pr. The analysis of Ce, La, Nd, and Pr concentration was carried out using ICP-OES. The optimum pH recovery for Ce, Nd, and Pr was found at pH 4 with a concentration of 19986.4 ppm, 3532.34 ppm, and 3796.81 ppm, respectively, while at pH 8.5 for La with a concentration of 5846.59 ppm.

High technology and economic statecraft: the emergence of techno-economic statecraft in South Korea

Abstract This study identifies the core of Korea’s economic statecraft as (1) diversification of the supply chain of high-tech industries to proactively mitigate vulnerability to economic coercion, (2) the pursuit of technological sovereignty to increase self-sufficiency in advanced technologies, (3) governance reforms to strengthen supply chain resilience, and (4) industrial policies to enhance the competitiveness of advanced industries. The four strategies mentioned above all have in common that they are predicated on the strategic utilization of high technology. Based on these traits, I define Korea’s new economic security strategy as techno-economic statecraft. Korea’s techno-economic statecraft has two features. First, Korea utilizes high technology as a nexus between economy and security. Second, Korea uses high technology as a nexus to link domestic and foreign policies.

Thermal-Mechanical and Microstructural Simulation of Rotary Friction Welding Processes by Using Finite Element Method.

Rotary friction welding is one of the most crucial techniques for joining different parts in advanced industries. Experimentally measuring the history of thermomechanical and microstructural parameters of this process can be a significant challenge and incurs high costs. To address these challenges, the finite element method was used to simulate thermomechanical and microstructural aspects of the welding of identical superalloy Inconel 718 tubes. Numerical simulation results were used to compute essential mechanical and metallurgical parameters such as temperature, strain, strain rate, volume fraction of dynamic recrystallization, and grain size distribution. These parameters were subsequently verified using experimental test results. The Johnson-Avrami model was utilized in the microstructural simulation to convert thermomechanical parameters into metallurgical factors, employing a FORTRAN subroutine. The calculated thickness of the recrystallization zone in the wall was 480 and 850 μm at the tube wall's center and edge, respectively. These values were reported from experimental measurements as 500 and 800 μm, respectively. The predicted grain size changes from the center to the edge of the wall thickness, near the weld interface, ranged from 2.07 to 2.15 μm, comparable to the experimental measurements ranging from 1.9 to 2.2 μm. Various curves are also presented to explore the correlation between thermomechanical and microstructural parameters, with the experimental results revealing predictable microstructure evolutions correlated with thermomechanical changes.

Do the G20 Countries' Increased Economic Growth, Foreign Direct Investment, Industry Value-added, and Population Change Contribute to CO2 Emissions?

Economic development plays a crucial role in contributing to CO2 emissions. Therefore, this research aims to investigate environmental degradation caused by economic activities within the scope of G-20 Countries, which comprise the largest economies and advanced industries. The primary objective of this study is to deliver an empirical study of gross domestic product, foreign direct investment, industry value-added, and population on CO2 emissions in G20 Countries. Using panel data from 2000-2022, the research found a positive correlation between GDP and CO2 emissions. Meanwhile, by utilizing GDP squared, the existence of the Environmental Kuznet Curve (EKC) theory was identified. The EKC theory indicates a significant negative correlation between GDP squared and CO2 emission. This is attributed to several factors, including increased public awareness of environmental protection and technological advancements in developed countries, contributing to improved energy efficiency. For the variables of FDI and population, a negative correlation with CO2 was found. On the other hand, the value-added industry shows a positive and significant correlation with CO2 emissions.

CARDIAC BIOMETRICS AND PERCEIVED WORKLOAD REGRESSION ANALYSIS USING RANDOM FOREST REGRESSOR IN COGNITIVE MANUFACTURING TASKS

Workload is crucial in managing and maintaining good performance of human resources and allocations. In an advanced manufacturing industry, human job functions had shifted to cognitive tasks. Thus, cognitive workload evaluation should be used to monitor worker’s workload in optimal condition. Most common tool of cognitive workload tools are perceived measurement, like NASA – TLX questionnaire. Despite of its sensitivity to capture workload felt by the workers, this subjective measurement was prone to bias. Objective measurement utilizing biometrics data of the human body during working state was useful to eliminate bias. Cardiac biometrics were one of the many that were closely related to mental activity changes. The objective of this study was to understand the relationship of cardiac biometrics to perceived workload as an indicator of cognitive workload analysis. The study utilized four biometrics, heart rate, HRV low frequency power, total frequency power and ratio of low and high frequency power, were used to analyzed a one hour long cognitive based study case. The study case was designed in a manufacturing planning context referring to manufacturing aptitude tests, to induce cognition process on 30 participants. The biometrics and NASA – TLX score result of all the participants, were then calculated as effect size standardization before input into random forest regressor model to analyze relationship between cardiac biometrics and perceived workload. The result found a moderate relationship between the two (r2 = 0.576). Features importance also showed the most impactful feature to the model is the effect size of frequency power ratio. However, it is recommended to always consider evaluating multiple cardiac biometrics in workload analysis to ensure good model performance.

Selection of Industry 4.0 technologies for Lean Six Sigma integration using fuzzy DEMATEL approach

PurposeThis study aims to explore the integration of Industry 4.0 technologies with lean six sigma practices in the manufacturing sector for enhanced process improvement.Design/methodology/approachThis study used a fuzzy decision-making trial and evaluation laboratory approach to identify critical Industry 4.0 technologies that can be harmonized with Lean Six Sigma methodologies for achieving improved processes in manufacturing.FindingsThe research reveals that key technologies such as modeling and simulation, artificial intelligence (AI) and machine learning, big data analytics, automation and industrial robots and smart sensors are paramount for achieving operational excellence when integrated with Lean Six Sigma.Research limitations/implicationsThe study is limited to the identification of pivotal Industry 4.0 technologies for Lean Six Sigma integration in manufacturing. Further studies can explore the implementation challenges and the quantifiable benefits of such integrations.Practical implicationsIntegrating Industry 4.0 technologies with Lean Six Sigma enhances manufacturing efficiency. This approach leverages AI for predictive analysis, uses smart sensors for energy efficiency and adaptable robots for flexible production. It is vital for competitive advantage, significantly improving decision-making, reducing costs and streamlining operations in the manufacturing sector.Social implicationsThe integration of Industry 4.0 technologies with Lean Six Sigma in manufacturing has significant social implications. It promotes job creation in high-tech sectors, necessitating advanced skill development and continuous learning among the workforce. This shift fosters an innovative, knowledge-based economy, potentially reducing the skills gap. Additionally, it enhances workplace safety through automation, reduces hazardous tasks for workers and contributes to environmental sustainability by optimizing resource use and reducing waste in manufacturing processes.Originality/valueThis study offers a novel perspective on synergizing advanced Industry 4.0 technologies with established Lean Six Sigma practices for enhanced process improvement in manufacturing. The findings can guide industries in prioritizing their technological adoptions for continuous improvement.

Study on the Mechanism and Path of Synergistic Development of Manufacturing and Service Industries in the Greater Bay Area of Guangdong, Hong Kong and Macao

The paper explores the level of synergistic agglomeration of the advanced manufacturing industry and logistics service industry in the Greater Bay Area from 2015 to 2018 through the spatial Gini coefficient and industrial agglomeration index. The results of the study show that the level of agglomeration and specialization of individual industries in some manufacturing industries in the Greater Bay Area is relatively high, and individual industries in the logistics industry have formed a certain scale of agglomeration, but there is still a certain gap compared with the manufacturing industry, and the level of agglomeration needs to be improved. Finally, it puts forward suggestions to promote the development of a synergistic agglomeration of the advanced manufacturing industry and logistics industry in the Greater Bay Area.

Hollow metal tubes for efficient electron manipulation using terahertz surface waves.

Compact electron sources have been instrumental in multidiscipline sciences including fundamental physics, oncology treatments, and advanced industries. Of particular interest is the terahertz-driven electron manipulation that holds great promise for an efficient high gradient of multi-GeV/m inside a regular dielectric-lined waveguide (DLW). The recent study relying on terahertz surface waves has demonstrated both high terahertz energy and improved coupling efficiency with the DLW. However, the large energy spread pertaining to the laser-induced electron pulse impedes the practical use of the system. Here, we propose a scheme for extending the idea of surface-wave-driven electron manipulation to mature electron sources such as commercial direct-current and radio-frequency electron guns. By using a simple hollow cylinder tube for electron transmission, we show that the electron energy modulation can reach up to 860 keV, or compress the electron pulse width to 15 fs using a 2.9 mJ single-cycle terahertz pulse. The trafficability of the hollow tube also allows for a cascade of the system, which is expected to pave the way for compact and highly efficient THz-driven electron sources.

THE COUNTRIES OF WESTERN ASIA IN THE PROCESSES OF INTERNATIONAL LABOR MIGRATION: FEATURES OF THE XXI CENTURY

The countries of Western Asia simultaneously act as centers of attraction in the processes of international labor migration, and countries, which let their citizens travel abroad to find work (are labor migrants). We analyze the situation in the field of international labor migration in 14 countries of Western Asia, excluding the former republics of the USSR, such as Armenia, Azerbaijan and Georgia, which are now included by international organizations in the group of countries in the region. The situation in the field of labor migration in the region is being updated in connection, firstly, with the growth of the economies of the countries of the Cooperation Council of the Arab States of the Persian Gulf (GCC) and, in general, some stabilization of the socio-economic and political situation in the West Asian region, secondly, with the trends to overcome the restrictions that took place due to the spread of coronavirus infection in the world and in the region, and, thirdly, with the region's attempts to transform the national economy and implement new advanced industries and productions based on innovation and digitalization. It is important to study the experience of the GCC countries in the field of labor migration in order to increase the efficiency and reduce the costs of MMRS in the Russian Federation. The article attempts to analyze the situation in the field of international labor migration in Western Asia, and primarily in the GCC, which actively accept labor from other states of the region and non-regional powers. The author concludes that the region will retain its role as a receiving center for foreign labor in the future on the basis of an adequate policy of the recipient countries. The geography of the countries of origin of immigrants also generally remains unchanged. The research period covers 2000–2022. The author used traditional methods of economic analysis to conduct the research. The sources of statistical information were data from international databases, primarily UNCTAD, as well as regional reports of international organizations.

Strategic Analysis of Profit Structure and Quality Improvement in Digital Transformation of Advanced Manufacturing Industries

Abstract Digital transformation is the engine to promote the high-quality development of the advanced manufacturing industry. This paper constructs a measurement model for the development level of digital transformation in the advanced manufacturing industry and proposes a measurement method for the development level of digital economy and digital transformation in the advanced manufacturing industry. The data are preprocessed through text mining, the vertical and horizontal pull-out grade method is used to determine the weights and calculate the final measurement value, and the time weights are obtained with the help of the nonlinear programming method to realize the measurement of the development level of the digital economy. Use the maximum-minimum value method to process the data related to digital transformation, utilize the entropy value method to calculate the index weights, and calculate the digital transformation development level through the linear weighting function method. The representative provinces of each region are selected to analyze the digital transformation of the advanced manufacturing industry in the east, middle, and west regions of China. The composite index of the digital economy development level in the East, Central, and West is 0.62, 0.45, and 0.37, respectively. The value of the digital transformation development level of Guangdong, Shandong, and Sichuan in 2023 reaches 0.9857, 0.3949, and 0.3747, respectively, ranking in the top three, whereas Jilin and Guizhou are only 0.1479 and 0.1128, and the level of digitalization of China’s advanced manufacturing industry is marked by obvious geographical imbalance.

Exploring the Criticality of Natural Resources Management and Technological Innovations for Ecological Footprint in the OECD Countries

ABSTRACT: The urgent imperative to confront the complex interplay between managing natural resources and fostering technological innovation, particularly in OECD countries, has become a focal point in global conversations. It is abundantly clear that critical issues such as the rampant overexploitation of our natural resources, insufficient embrace of sustainable practices, and the profound repercussions of technological advancements on our ecological footprint demand meticulous scrutiny and comprehensive action. This scrutiny is vital to guide the formulation of judicious policies and strategies capable of addressing these complex challenges. The challenges faced by OECD countries, distinguished by their advanced industrialization, and elevated standards of living, are further compounded by the depletion of natural resources resulting from extensive economic activities. The extraction and utilization of resources, encompassing water, minerals, and energy, emerge as significant contributors to ecological degradation. The heightened demand for raw materials to sustain technological industries has precipitated the overexploitation and depletion of natural resources, manifesting in activities such as mining, deforestation, and other extraction processes, leading to habitat destruction and biodiversity loss. Furthermore, the manufacturing and utilization of technology, particularly within industries heavily reliant on non-renewable energy sources, have been substantial contributors to pollution and greenhouse gas emissions. The study assesses the dynamic relationship between natural resources, economic growth, and technological innovation with respect to ecological footprints. It analyses the annual data series of a panel of 20 organisation for economic cooperation and development countries using the second-generation cointegration panel and cross-sectional autoregressive distributed lag methodology. The results of the slope coefficient confirm the existence of slope heterogeneity among countries. Furthermore, it affirms the long-term relationship among variables. Overall, the findings highlight the importance of effective utilisation of resources while investing in technological innovation to attain sustainable development goals.

The semi-quantitative analysis of hole defects in metal additive manufacturing components using LIBS

The method of segmented feature selection combined with spectral line intensity ratio was employed to improve the semi-quantitative analysis results of LIBS metal AM component hole defects.

Managing innovations in the energy sector through the adaptation of the experience of the rocket and space industry

In the modern world, energy is one of the most important sectors of the economy, on which the well-being and development of society directly depend. However, traditional energy management models no longer correspond to rapidly changing market conditions and technological progress. In this regard, there is an urgent need to find new, innovative approaches to managing this industry. In this article, it is proposed to use the experience of space-rocket industry (SRI) to manage innovations in the energy sector SRI is one of the most advanced industries where the latest technologies and management methods are used. The industry has a well- developed culture of innovation, which allows it to constantly develop and improve. The article discusses the basic principles of innovation management in SRI and suggests their adaptation to the energy sector. The advantages and possibilities of using the experience of SRI in this area are analyzed.

The Role of Carbon Fiber Composite Materials in Making Electric Aircraft a Reality

As the aerospace industry seeks sustainable alternatives to traditional aviation, electric aircraft have emerged as a promising solution to reduce carbon emissions and reliance on fossil fuels. Central to this transition is the development and integration of advanced materials that enhance the performance and efficiency of these next-generation aircraft. Compound materials possess various significant abilities, including the capability to withstand fatigue, resist corrosion, and manufacture lightweight components with minimal compromise to reliability, among others. Nanocomposites constitute a subset of materials within compounds, recognized for their superior mechanical properties compared to standard composite materials. The utilization of nanocomposites in the aerospace sector is presently encountering a research gap, primarily in identifying future application scopes. This paper reviews the critical role of carbon fiber composites and nanocomposites in electric aviation, highlighting their transformative impact on aircraft design, battery integration, and overall sustainability. By offering unparalleled strength-to-weight ratios, superior thermal management, and innovative structural possibilities, these materials significantly advance the capabilities of electric aircraft. Furthermore, it discusses the advancements in material technology, including high-temperature composites, hybrid composites, and nanocomposite materials, and addresses the challenges and future directions in composite application. The paper underscores the pivotal role of composite materials in achieving a greener, more efficient, and technologically advanced aerospace industry, marking a significant step towards sustainable air transportation.

Development of Fine-Tuned Retrieval Augmented Language Model specialized to manual books on machine tools

This paper aims to reduce potential human errors and loads that arise from the lack of novice human operators and different interfaces in advanced machine tool industries. A digital assistant using generative artificial intelligence is designed to answer questions about machine terminologies, and operation sequences happening in an alarm state. Combining Fine-Tuning, Retrieval Augmented Generation, and Prompt Engineering, it solves problems of common-purpose large language models. The proposed system is implemented on a local server and connected to a mobile device. It shows increasing quantitative accuracy from 51% to 79% and 84% in the fine-tuned and retriever model, and the qualitative score increases from 21 to 25 in the retriever model.

Exploring the Application of Financial Indicator Prediction Models in Optimizing Tax Burden

Abstract As economic globalization progresses unceasingly, the financial activities of enterprises are increasingly complex, paralleled by a concomitant increase in the intricacy of tax laws and regulations. Consequently, the tax risks faced by enterprises are becoming more pronounced. To predict the financial status of enterprises, a logistic regression model is created by combining relevant financial indicators. Considering the large amount of enterprise financial sample data, a Lasso-Logistic regression model is constructed, and the ADMM algorithm optimizes the model to improve the model's prediction accuracy. Finally, after using the ROC curve to test the validity of the constructed financial index prediction model, the A-share listed companies in the advanced manufacturing industry are taken as the research object of empirical analysis to analyze the relationship between the impact of financial indexes on tax burden. The regression equation for the standardization of tax burden is tax risk = -0.02341+0.03572 VAT effective tax burden +0.15451 income tax effective tax burden +0.21118 current ratio -0.26875 total asset turnover +0.06574 current sales revenue +0.02432 current cost of goods sold +0.13681 gearing ratio + 0.23708 Fixed Assets Change Ratio - 0.26895 Asset Size. Based on the analysis results, this paper proposes three optimization strategies for tax burden.

A DE Novo multi criteria heterogeneous group decision making approach for green performance assessment of CNC machine tools

In the contemporaneous sustainable manufacturing scenario and fourth industrial revolutions, requirements of most cutting-edge CNC machine tools are indispensable for finished products with high accuracy, precision and green complaints in particular. Such requirements have impelled the advanced manufacturing industries to evaluate and choose the proper CNC machine tools for best customized performances. In the face of proper and effective green evaluation, this paper incorporates a heterogeneous expert group based decision framework considering multiple significant technical and green criteria by assessing relative importance of diverse conflicting criteria having substantial contribution in performance analysis of CNC machine tools. As a demonstration of the suggested mathematical model, three real life decision making problems related to 3 axes-CNC machine tools based on the collected quantitative and linguistic data from catalogues, manufacturer’s portals, questionnaires, customer reviews etc. are established. The calculated findings are close to those obtained by previous researchers as well as are verified by well-established techniques. Besides, sensitivity and statistical analysis are performed to examine the robustness and stability of the ranking orders of the alternatives as well as to investigate the efficacy and consistency of the proposed method. Hence thus proposed formulated MCDM approach proves to be a highly effective and reliable decision making tool for choosing the most suitable CNC machine tools.