Search Results (68)

Small and medium-sized enterprises (SMEs) face unique challenges that can be effectively addressed through the adoption of data mining and business intelligence (BI) tools. This systematic literature review scrutinizes the deployment and efficacy of BI and data mining technologies across SME sectors, assessing their impact on operational efficiency, strategic decision-making, and market competitiveness. Therefore, drawing from a methodologically rigorous analysis of 93 scholarly articles published between 2014 and 2024, the review elucidates the evolving landscape of BI tools and techniques that have shaped SME practices. It reveals that advanced analytics such as predictive modeling and machine learning are increasingly being adopted, though significant gaps remain, particularly shaped by economic factors. The utilization of BI and data mining enhances decision-making processes and enables SMEs to adapt effectively to market dynamics. Despite these advancements, SMEs encounter barriers such as technological complexity, high implementation costs, and substantial skills gaps, impeding effective utilization. Our review, grounded in the analysis of business intelligence tools used indicates that dashboards (31.18%) and clustering techniques (10.75%) are predominantly utilized, highlighting their strategic importance in operational settings. However, a considerable number of studies (66.67%) do not specify the BI tools or data mining techniques employed, pointing to a need for more detailed methodological transparency in future research. The predominant focus on the ICT and manufacturing sectors underscores the industrial context sector specific applicability of these technologies, with ICT accounting for 45.16% and manufacturing 22.58% of the studies. We advocate for targeted educational programs, development of user-friendly and cost-effective BI solutions, and strategic partnerships to facilitate knowledge transfer and technological empowerment in SMEs. Empirical research validating the impacts of BI and data mining on SME performance is crucial, providing a directional pathway for future academic inquiries and policy formulation. Full article

The productivity of the construction industry is about half that of the manufacturing industry, and the labor shortage in the construction industry is serious; therefore, improving productivity using information and communication technology (ICT) is an urgent issue. In addition, in civil engineering works, the number of projects that handle multiple types of soil and sand is increasing due to the recycling of construction waste soil; thus, traceability management is important to ensure quality. This paper presents a system that uses sensing on soil-transporting dump trucks and ICT to record which soil was piled up where with the aim of improving the efficiency of traceability management in earthwork construction. This system automatically creates traceability data by linking sensing data and data from the compaction management system via an application. This eliminates the need to record and manage the earthwork location, which was previously required manually to create traceability data, and reduces the labor and manpower required for traceability management. The created traceability data are automatically assigned attribute information such as the construction date and soil information; consequently, they can be used to check the construction history in the future. Full article

Indium phosphide (InP) semiconductor technology is being explored for radiofrequency (RF) applications, targeting frequencies exceeding 100 GHz, to support the next generation of 6G communication systems. When taking into account sustainability in designing this future generation, growing concerns are emerging regarding the environmental impact of communication networks and the reliance on raw materials for the production of Information and Communication Technologies (ICTs). The extraction, processing, and manufacturing of such materials and semiconductor technologies result in environmental impacts, but these impacts remain insufficiently documented. Firstly, this study evaluates the environmental impacts of manufacturing indium phosphide (InP) wafers based on industrial data and those of InP-based heterojunction bipolar transistors (HBTs) based on early-stage research data. Secondly, this study attempts to highlight the challenges posed by the increasing demand for high-tech solutions, involving raw materials, by evaluating the potential demand for indium for RF 6G applications, with a deployment scenario. Full article

The robots that entered the manufacturing sector in the second and third Industrial Revolutions (IR2 and IR3) were designed for carrying out predefined routines without physical interaction with humans. In contrast, IR4* robots (i.e., robots since IR4 and beyond) are supposed to interact with humans in a cooperative way for enhancing flexibility, autonomy, and adaptability, thus dramatically improving productivity. However, human–robot cooperation implies cognitive capabilities that the cooperative robots (CoBots) in the market do not have. The common wisdom is that such a cognitive lack can be filled in a straightforward way by integrating well-established ICT technologies with new AI technologies. This short paper expresses the view that this approach is not promising and suggests a different one based on artificial cognition rather than artificial intelligence, founded on concepts of embodied cognition, developmental robotics, and social robotics. We suggest giving these IR4* robots designed according to such principles the name CoCoBots. The paper also addresses the ethical problems that can be raised in cases of critical emergencies. In normal operating conditions, CoCoBots and human partners, starting from individual evaluations, will routinely develop joint decisions on the course of action to be taken through mutual understanding and explanation. In case a joint decision cannot be reached and/or in the limited case that an emergency is detected and declared by top security levels, we suggest that the ultimate decision-making power, with the associated responsibility, should rest on the human side, at the different levels of the organized structure. Full article

The presented paper examines the integration of Artificial Intelligence (AI) in the management of smart cities, focusing on the Silesian and Lesser Poland Voivodships in Poland. This research addresses a notable gap in the analysis of regional AI strategies within urban management, providing a comparative analysis of AI implementation in these two distinct regions. The Silesian Voivodship, with its emphasis on traditional industries such as manufacturing and energy, contrasts with the broader approach of the Lesser Poland Voivodship, which includes applications in life sciences and ICT. The paper explores how AI technologies enhance urban efficiency, sustainability, and livability through practical applications in traffic management, healthcare, energy efficiency, and environmental management. It highlights the importance of a human-centric approach in smart city development, emphasizing inclusivity, transparency, and ethical considerations. The paper also delves into the socio-technical dynamics of AI deployment, illustrating how these technologies can transform urban environments while ensuring that the benefits are equitably distributed and that urban developments are sustainable and resilient. By analyzing specific case studies, the authors aim to provide empirical evidence and insights that contribute to the academic and practical understanding of AI’s role in smart cities, ultimately advocating for the design of AI applications that prioritize human well-being and environmental health. Full article

South Africa’s economic growth has been slow since the 1980s due to inefficiencies in the manufacturing, mining and quarrying, ICT, electricity, gas, and water sectors. This article uses the theoretical framework and growth rates to identify key reasons for this slowdown. Key issues include inefficiencies within the gross fixed capital formation (GFCF) and inadequate infrastructure, primarily due to government behavior. This article used secondary data to perform the desktop analysis. To promote economic growth, the South African government and allied stakeholders should consider increasing investments in public infrastructure and financing research and development. This article argues that economic growth is driven by government expenditure, easy access to financing, and technological advancements. To promote economic growth, a comprehensive approach is needed, including tax breaks, loan guarantees, and pro-business legislation. Full article

Industry 4.0 integrates the intelligent networking of machines and processes through advanced information and communication technologies (ICTs). Despite advancements, small mechanical manufacturing enterprises face significant challenges transitioning to ICT-supported Industry 4.0 models due to a lack of technical expertise and infrastructure. These enterprises commonly encounter variable production volumes, differing priorities in customer orders, and diverse production capacities across low-, medium-, and high-level outputs. Frequent issues with machine health, glitches, and major breakdowns further complicate optimizing production scheduling. This paper presents a novel production management approach that harnesses bio-inspired methods alongside Internet of Things (IoT) technology to address these challenges. This comprehensive approach integrates the real-time monitoring and intelligent production order distribution, leveraging advanced LoRa wireless communication technology. The system ensures efficient and concurrent data acquisition from multiple sensors, facilitating accurate and prompt capture, transmission, and storage of machine status data. The experimental results demonstrate significant improvements in data collection time and system responsiveness, enabling the timely detection and resolution of machine failures. Additionally, an enhanced genetic algorithm dynamically allocates tasks based on machine status, effectively reducing production completion time and machine idle time. Case studies in a screw manufacturing facility validate the practical applicability and effectiveness of the proposed system. The seamless integration of the scheduling algorithm with the real-time monitoring subsystem ensures a coordinated and efficient production process, ultimately enhancing productivity and resource utilization. The proposed system’s robustness and efficiency highlight its potential to revolutionize production management in small-scale manufacturing settings. Full article

In recent years, there has been a heightened focus on multiplex porosity due to its significant adverse impact on the mechanical properties of aluminum alloy components produced through wire arc additive manufacturing (WAAM). This study investigates the impacts of the process parameters and dimension parameters on the relative densities of WAAM 2219 aluminum alloy components by conducting experiments and investigates the changes in high relative density process windows with different dimension parameters. The findings reveal a hierarchy in the influence of various parameters on the relative density of the 2219 aluminum alloy: travel speed (TS), wire feed speed (WFS), the number of printed layers (L), interlayer cooling time (ICT), and theoretical length of weld (TLW). A series of data for analysis was produced through a designed experiment procedure, and on the basis of this, by integrating the data augmentation method with the eXtreme Gradient Boosting (XGBoost) algorithm, the relationship among the process parameters, dimension parameters, and relative density was modeled. Furthermore, through leveraging the established model, we analyzed the changes in the optimized process window corresponding to a high relative density with the L. The optimal windows of WFS and TS change when the L reaches a certain value. In contrast, the optimal window of ICT remains consistent despite an increase in the L. Finally, the relative density and mechanical properties of the formed 20-layer specimens within the model-derived window were verified. The relative density of the specimens within the window reached 98.77%, the ultimate tensile strength (UTS) reached 279.96 MPa, and the yield strength (YS) reached 132.77 MPa. This work offers valuable insights for exploring the process window and selecting process parameters through a more economical and faster approach in WAAM aluminum components. Full article

The rapid growth of digital trade has had a profound impact on global economies, revolutionizing trading practices and facilitating trade expansion. The purpose of this paper is to explore the digital partnership between Korea and the European Union (EU) and its implications for their shared agenda in digital trade to theorize the dynamics of digital trade. A case study method is used to explore trade between Korea and the EU with in-depth descriptive analysis. Digital trade-flow statistics were analyzed to develop the case for Korea and EU digital trade and derive implications for both countries. The findings were generalized by discussing the relevant literature and data from other countries to identify the wider implications. The analysis was focused on the areas of information and communication technology and e-commerce. The findings suggest uncovered trade imbalances, such as Korea’s surplus of ICT goods exports and the EU’s dominant position in online trade. There is an influence of supply chain dynamics, specifically the presence of Korean manufacturers’ production units in countries like Vietnam, and the same dynamics have shaped Korea’s actual place in the supply of ICT goods to the European market. While the digital partnership was established to align regulatory frameworks and foster trust, transparency, and harmonization in the digital domain, it has failed to adequately reflect the importance of digital trade. Although both sides are motivated to collaborate on the harmonization of digital trade rules, there have been instances where the partners’ interests diverge. It is concluded that some political and economic factors may hinder the effectiveness of the digital partnership, unless concrete measures that go beyond traditional bilateral policymaking approaches are implemented. It is therefore recommended to emphasize the need to enhance the efficacy of the digital partnership by taking bolder actions to develop digital trade. Full article

Robotics and automation have been a growing area within K–12 educational institutions for the past decade. Across secondary educational institutions, students are introduced to robotics in classes, after-school clubs, and competition leagues through various educational platforms, vendors, and kits. Robotics was initially implemented in schools to help drive more interest in STEM through hands-on application of mechanical, electrical, structural, and computer engineering concepts. Recently, the trend of K–12 robotics has become very niche, focusing more on mobile robotics or robotics competitions. Because of this trend, students have limited exposure to emerging technological advances, such as those found in Industry 4.0. Exciting technological areas, such as digital twins, are not covered in curricula, and this lack of exposure negatively influences the direction of student interest in the “T” and “E” of STEM, with many students never pursuing computer science, technology, or robotics in higher education. The primary goal of this research is to provide a methodology to expose secondary students to Industry 4.0 technologies by leveraging accessible technologies, such as Unity and the Robot Operating System (ROS), to develop a low-cost, high-fidelity digital twin of a pick-and-place robot in a smart warehouse operation. This digital twin prototype will help students to learn about Industry 4.0 trends, such as next-generation automation systems, digital twins, digital manufacturing, intelligent automation, and additive manufacturing, using ROS–Unity integration and hardware accessible to secondary schools to simulate a pick-and-place robotic application. By harnessing the accessibility of Unity and ROS to create a low-cost digital twin prototype for a secondary school, this research has a secondary goal of improving the pipeline of students interested in pursuing STEM-related learning in higher education, thereby ensuring a future STEM workforce that can research, design, develop, operate, and maintain the systems and technologies of Industry 4.0. Full article

Dimensional accuracy of selective laser melting (SLM) parts is one of manufacturers’ major concerns. The additive manufacturing (AM) process is characterized by high-temperature gradients, consolidation, and thermal expansion, which induce residual stress on the part. These stresses are released by separating the part from the baseplate, leading to plastic deformation. Thermo-mechanical finite elements (FE) simulation can be adopted to determine the effect of process parameters on final geometrical accuracy and minimize non-compliant parts. In this research, a geometry for process parameter calibration is presented. The part has been manufactured and then analyzed with industrial computed tomography (iCT). An FE process simulation has been performed considering material removal during base plate separation, and the computed distortions have been compared with the results of the iCT, revealing good accordance between the final product and its digital twin. Full article

This study aims to investigate the impact of ICT capital services on economic growth and energy efficiency in China at both national and industrial levels during the period 2000–2020. To achieve this aim, this study introduces a measurement method for capital services, explores ICT’s contributions to economic growth, and analyzes the impact of ICT on energy efficiency. The empirical results of this study indicate that although the ICT capital services scale is relatively small, accounting for only 8.87% of the total in 2020, its growth rate is faster than that of non-ICT capital services, and the distribution of ICT capital services varies widely among different industries. Additionally, based on the economic growth decomposition framework, this study finds that the contribution of ICT capital services to economic growth is 6.95% on average. It is significantly higher in certain industries, such as Financial industry; Information transmission, software and information technology services; Construction; and Manufacturing compared to others. The total factor energy efficiency (TFEE) reveals that industries with higher energy consumption have lower energy efficiency, while the panel regression model illustrates that the development of ICT has a positive impact on improving energy efficiency, with variability across industries. Overall, the findings of this study provide crucial scientific evidence and policy implications for promoting the development of ICT and integrating it with various industries, which can significantly contribute to boosting economic growth and energy efficiency. Full article

For rapidly developing smart manufacturing, Industrial ICT Systems (IICTSs) have become critical to safe and reliable production, and effective monitoring of complex IICTSs in practice is necessary but challenging. Since such monitoring data are organized generally as semi-structural logs, log parsing, the fundamental premise of advanced log analysis, has to be comprehensively addressed. Because of unrealistic assumptions, high maintenance costs, and the incapability of distinguishing homologous logs, existing log parsing methods cannot simultaneously fulfill the requirements of complex IICTSs simultaneously. Focusing on these issues, we present LogParser, a deep learning-based framework for both online and offline parsing of IICTS logs. For performance evaluation, we conduct extensive experiments based on monitoring log sets from 18 different real-world systems. The results demonstrate that LogParser achieves at least a 14.5% higher parsing accuracy than the state-of-the-art methods. Full article

Information and communication technology (ICT) companies strive for ceaseless innovation to remain competitive while facing the challenge of maximizing firm value (FV) with limited resources, and increasing the interests of shareholders. However, capital structures have a considerable effect on FV, and the literature still disagrees with the optimum structure in specific industries and countries. Therefore, this study evaluates the FV of ICT companies in terms of profitability efficiency using data envelopment analysis. In addition, this study applies a Tobit regression and Kruskal-Wallis one-way ANOVA to identify the impact of leverage, liquidity, and firm size, which are major capital structure factors influencing FV. The analysis yields three main results. First, in the ICT industry, small and medium companies tend to have better profitability efficiency than companies of other sizes. Second, only small and medium ICT manufacturing companies’ profitability efficiency is positively impacted by the current ratio. Third, only mid-sized service companies’ profitability efficiency is positively impacted by the debt-equity ratio. The results have policy and practical implications for improving the FV of ICT companies. Full article

The Internet of Things (IoT) and smart manufacturing (SM) are mutually reinforcing. The establishment of IoT-based common facilities for SM is the premise of building SM system. Industrial IoT (IIoT) infrastructure for SM refers to common facilities based on IoT that support SM in industries or sectors, and plays a dominant role and faces severe challenges in the intelligence of SM. The infrastructure is independent of the products and production process in a specific factory. This paper develops conceptual and capability frameworks of IIoT infrastructure from a unified perspective of IIoT-related SM industries. These frameworks reflect relationships between IIoT and SM with in-depth relationships among basic facilities of IIoT infrastructure and lay the foundation of SM. In this paper the common characteristics and high-level requirements with respect to the different IoT layers of IIoT infrastructure are analyzed, and the capability framework and relevant capabilities of IIoT infrastructure are summarized according to the characteristics and requirements. In order to help service providers implement their systems to meet the needs of SM, the existing and newly developed IIoT infrastructure are integrated partially or in whole according to the intelligence level, so as to provide technical guidance for stakeholders to apply emerging ICTs to SM. Full article