Iskanje po katalogu digitalne knjižnice

Opis: The issue addressed in this paper concerns the erosion of trust within supply chains, as reported by key industry stakeholders. In this context, automotive component buyers frequently rely on single-source suppliers, thereby intensifying competitive pressures on component manufacturers. Consequently, automotive component suppliers must seek to strengthen supplier relationships to enhance trust. Given the limited opportunities for differentiation, automotive component suppliers increasingly pursue alternative strategies to ensure their long-term sustainability, with a particular emphasis on value-driven supplier relationships founded on trust. Existing literature suggests that optimised supplier relationships contribute to trust-building. This study employs a quantitative approach, utilising path analysis to identify the relationship value construct exhibiting the strongest correlation with trust. The findings indicate a significant correlation between product quality and delivery, suggesting that the timely and accurate delivery of products is the most critical factor in fostering trust between buyers and suppliers. Additionally, the analysis reveals that the most statistically significant aspect of relationship value is product quality and delivery. The paper concludes with theoretical and managerial recommendations, including the implementation of a relational governance strategy within automotive supply chains to strengthen trust and enhance long-term sustainability.
Ključne besede: supply chain relationships, buyer-seller relationships, South African automotive industry, relationship governance
Objavljeno v DKUM: 28.10.2025; Ogledov: 0; Prenosov: 3
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Opis: The circular economy (CE) encourages sustainability by shifting towards business models that prolong resource use. The quantity of waste generated by electric and electronic equipment (WEEE or e-waste) is rapidly rising and is one of the fastest-growing waste streams. Our paper explores the awareness, benefits, barriers, incentives, and implementation of CE in the electric and electronic equipment (EEE) industry in Slovenia and Croatia. In the theoretical section, we review the existing literature on CE, the EEE industry in both countries, and their policy frameworks for developing CE. Based on primary research through a survey and inferential statistical analysis in the empirical section, we investigate the implementation of CE in the EEE industry in both countries. This paper identifies which CE practices companies in the EEE industry implement, how company size affects CE implementation, how companies evaluate institutional support to CE, and their plans regarding CE. The results highlight some differences between the two countries. Drawing on the empirical findings, we determine key challenges and opportunities for increasing CE adoption in this sector and formulate some European suggestions for policymakers, industry practitioners, and researchers.
Ključne besede: sustainability, circular economy, electric and electronic equipment industry, e-waste
Objavljeno v DKUM: 01.09.2025; Ogledov: 0; Prenosov: 5
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Opis: At Štore Steel Ltd., continuously cast billets (180 mm × 180 mm) are reheated and rolled after cooling to room temperature. Hot-rolled bars are controlled as they cool to room temperature in specially designed cooling chambers, minimizing residual stresses and the development of pre-existing surface and internal defects. The bar ends can be additionally covered with insulating material. The cooled, rolled bars undergo examination using automated control lines to detect surface and internal defects, which primarily originate from the casting process. Internal defects are identified using ultrasonic testing. Between January 2022 and June 2023, 1550.0 tons of 61SiCr7 rolled bars, with diameters ranging from 53 mm to 72 mm and lengths from 7010 mm to 7955 mm, were examined using ultrasonic testing. The scrap was 109.6 tons (7.07 %). After collecting data on chemical composition (C, Si, Mn, Cr, Mo, Ni content), the casting process (casting temperature, cooling water pressure and flow in the first, second, and third zones of secondary cooling, as well as the temperature difference between input and output mould cooling water), and rolled bar geometry (diameter, length), scrap modelling after ultrasonic testing was carried using genetic programming. The genetic programming model suggested reducing the length of the rolled bar. Due to length multiplication, it was possible to reduce the rolled bar length from the initial lengths of 7010-7955 mm to the current lengths of 4558-6720 mm in June 2023. Based on this adjustment, a new production of rolled bars was established. By August 2024, 1251.9 tons of 61SiCr7 rolled bars were produced with the mentioned length adjustments. These rolled bars were subsequently examined using ultrasonic testing. The scrap was reduced by nearly 14 times, amounting to only 8.1 tons (0.64 %).
Ključne besede: steel industry, rolling, long bars, ultrasonic testing, scarp, defects, modelling, genetic programming
Objavljeno v DKUM: 27.08.2025; Ogledov: 0; Prenosov: 1
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Opis: Background and Purpose: This article employs the Hugging Face keyphrase-extraction-kbir-inspec machine learning model to analyze 654 abstracts on the topic of energy efficiency in systems and control, computer science and robotics. Methods: This study targeted specific arXiv categories related to energy efficiency, scraping and processing ab - stracts with a state-of-the-art Transformer-based Hugging Face AI model to extract keyphrases, thereby enabling the creation of related keyphrase networks and the retrieval of relevant scientific preprints. Results: The results demonstrate that state-of-the-art open-source machine learning models can extract valuable information from unstructured data, revealing prominent topics in the evolving field of energy-efficiency. Conclusion: This showcases the current landscape and highlights the capability of such information systems to pinpoint both well researched and less researched areas, potentially serving as an information retrieval system or early warning system for emerging technologies that promote environmental sustainability and cost efficiency.
Ključne besede: energy efficiency, keyphase extraction, early warning system, information system, semantic network, transformer models, industry 4.0
Objavljeno v DKUM: 07.08.2025; Ogledov: 0; Prenosov: 3
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Opis: This paper presents a broad study on the application of the BERT (Bidirectional Encoder Representations from Transformers) model for multiclass text classification, specifically focusing on categorizing business descriptions into 1 of 13 distinct industry categories. The study involved a detailed fine-tuning phase resulting in a consistent decrease in training loss, indicative of the model’s learning efficacy. Subsequent validation on a separate dataset revealed the model’s robust performance, with classification accuracies ranging from 83.5% to 92.6% across different industry classes. Our model showed a high overall accuracy of 88.23%, coupled with a robust F1 score of 0.88. These results highlight the model’s ability to capture and utilize the nuanced features of text data pertinent to various industries. The model has the capability to harness real-time web data, thereby enabling the utilization of the latest and most up-to-date information affecting to the company’s product portfolio. Based on the model’s performance and its characteristics, we believe that the process of relative valuation can be drastically improved.
Ključne besede: industry classification, BERT transformer, business descriptions, multiclass text classification, AI
Objavljeno v DKUM: 01.07.2025; Ogledov: 0; Prenosov: 8
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