Search Results (985)

The selection of an appropriate technological process is essential to achieve optimal results in manufacturing companies. This affects quality, efficiency and competitiveness. In the modern industry, multi-criteria decision-making (MCDM) methods are increasingly used to evaluate, optimize and solve various manufacturing challenges. In this review article, existing methodologies and patents related to optimization and decision making are investigated. The main characteristics and applications of the methods are outlined. The purpose of this article is to provide a systematic review and evaluation of the main MCDM methods used in industrial practice, including through an analysis of relevant methodologies and patents. The methodology involves a structured literature and patent review, focusing on applications of widely used MCDM techniques such as the AHP (analytic hierarchy process), ANP (analytic network process), FUCOM (full consistency method), TOPSIS (technique for order preference by similarity to ideal solution), and VIKOR (višekriterijumsko kompromisno rangiranje). The analysis outlines each method’s strengths, limitations and areas of applicability. Special attention is given to the potential of the FUCOM for process evaluation in manufacturing. The findings are intended to guide researchers and practitioners in selecting appropriate decision-making tools based on specific industrial contexts and objectives. In conclusion, from the comparative analysis made, the methodologies reveal their advantages and disadvantages as well as limitations that arise in their application. Full article

The Internet of Medical Things (IoMT) is the latest advancement in the Internet of Things (IoT). Researchers are increasingly drawn to its vast potential applications in secure healthcare systems. The growing use of internet-connected medical device sensors has significantly transformed healthcare, necessitating the development of robust methodologies to assess their integrity. As access to computer networks continues to expand, these sensors have become vulnerable to a wide range of security threats, thereby compromising their integrity. To prevent such lapses, it is essential to understand the complexities of the operational environment and to systematically identify technical vulnerabilities. This paper proposes a unified hesitant fuzzy-based healthcare system for assessing IoMT sensor integrity. The approach integrates the hesitant fuzzy Analytic Network Process (ANP) and the hesitant fuzzy Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS). In this study, a hesitant fuzzy ANP is employed to construct a comprehensive network that illustrates the interrelationships among various integrity criteria. This network incorporates expert input and accounts for inherent uncertainties. The research also offers sensitivity analysis and comparative evaluations to show that the suggested method can analyse many medical device sensors. The unified hesitant fuzzy-based healthcare system presented here offers a systematic and valuable tool for informed decision-making in healthcare. It strengthens both the integrity and security of healthcare systems amid the rapidly evolving landscape of medical technology. Healthcare stakeholders and beyond can significantly benefit from adopting this integrated fuzzy-based approach as they navigate the challenges of modern healthcare. Full article

This study quantifies ship-type performance indicators by training intelligent agents to evaluate and score vessels. The Analytic Hierarchy Process (AHP) is then applied to assess the internal consistency of the collected data, ensuring its authenticity and validity. Subsequently, the entropy weight method is employed to objectively determine the significance of each indicator in ship-type decision-making. Finally, COSCO (China COSCO Shipping Corporation Limited) Shipping’s capacity gap reflects the results of the methodology: the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) technique ranks all feasible ship-type combinations, presenting their relative merits through quantitative results. A standardized grading system is further proposed to evaluate these combinations systematically. Ultimately, the 10 most suitable solutions are identified—none achieving the theoretical maximum rating of Grade 10—demonstrating room for improvement in vessel performance. Full article

This article introduces an algorithm that uses a U-Net architecture to determine vertical ground surface displacements from unmanned aerial vehicle (UAV)-photogrammetry point clouds, offering an alternative to traditional ground filtering methods. Unlike conventional ground filters that rely on point cloud classification, the proposed approach employs heteroscedastic regression. The U-Net model predicts the conditional expected values of the elevation corrections, aiming to reduce the impact of vegetation on determined ground surface elevations. Concurrently, it estimates the logarithm of the elevation correction variance, allowing for direct quantification of the uncertainty associated with each elevation correction value. The algorithm was evaluated using three metrics: the root mean square error (RMSE) of vertical displacements, the percentage of nodes with determined displacement values, and the percentage of outliers among those values. Performance was assessed using the technique for order of preference by similarity to ideal solution (TOPSIS) method and compared against several ground-filter-based algorithms across four datasets, each including at least two time intervals. In most cases, the U-Net-based approach demonstrated a slight performance advantage over traditional ground filtering techniques. For example, for the U-Net-based algorithm, for one of the test datasets, the RMSE of the determined subsidences was 6.1 cm, the percentage of nodes with determined subsidences was 80.5%, and the percentage of outliers was 0.2%. For the same case, the algorithm based on the next best model (SMRF) allowed an RMSE of 7.7 cm to be obtained; for 77.3% of nodes, the subsidences were determined; and the percentage of outliers was 0.3%. Full article

Due to the exceptional corrosion resistance, chemical stability, and dense microstructure, carbon-based thin films are extensively employed in hydrogen energy systems. This study employed magnetron sputtering to fabricate amorphous carbon (a-C) films on SS316L substrates, aiming to improve the corrosion resistance of bipolar plates (BPs) in proton exchange membrane fuel cells (PEMFCs). Using a Taguchi design, the effects of working pressure, sputtering power, substrate bias, and deposition time on film properties were systematically examined and optimized. Films were examined via field emission scanning electron microscopy (FE-SEM), contact angle measurements, and electrochemical tests. Comprehensive evaluation by the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method identified optimal conditions of 1.5 Pa pressure, 150 W radio frequency (RF) power, −250 V bias voltage, and 60 min deposition, yielding dense, uniform films with a corrosion current density of 1.61 × 10⁻⁶ A·cm⁻² and a contact angle of 106.36°, indicative of lotus leaf-like hydrophobicity. This work enriches the theoretical understanding of a-C film process optimization, offering a practical approach for modifying fuel cell bipolar plates to support hydrogen energy applications. Full article

In a dynamic and uncertain environment, maintaining a high level of business process (BP) reliability represents a key long-term objective for organizations. The manufacturing process, as the most critical business process in manufacturing enterprises, is emphasized due to its potential to cause significant disruptions across other BPs if it fails. This paper proposes a two-stage model. In the first stage, failures leading to lean waste are evaluated and ranked using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) combined with interval-valued intuitionistic fuzzy numbers (IVIFNs), referred to as IF-TOPSIS. The model is grounded in the Failure Mode and Effect Analysis (FMEA) framework. In the second stage, a modified fuzzy logic system with IVIFN-based rules is applied to determine the risk level of the manufacturing process. This approach is based on the property of symmetry in the decision-making process, ensuring that criteria are treated in a balanced manner and inference rules are applied consistently. A case study based on real-life data demonstrates that the obtained results identify measures that can enhance business strategy and reduce failure rates. Thus, the model is validated and shown to contribute to lean waste reduction. It can be concluded that the proposed methodology provides clear and practical guidance to enterprise management, as well as to all sectors and individuals involved in ensuring a reliable manufacturing process, for defining failure priorities and implementing preventive measures. Full article

Water resource carrying capacity is a key measure of sustainability, commonly employed to evaluate how well water resources can sustain economic and social growth. With China’s rapid economic growth and modernization, water resources in certain regions are now being used at or beyond their sustainable threshold. This study evaluates the present state of water resource carrying capacity in Taizhou City, located in southeastern China. Using relevant data from 2012 to 2022 on society, economy, water resources, and ecology, the weights of the evaluation indicators were determined using both the entropy weight method and principal component analysis. Subsequently, a comprehensive evaluation model for water resource carrying capacity was developed by applying the TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) method. The comprehensive proximity index for water resource carrying capacity in Taizhou City averaged 0.4864 between 2012 and 2022, indicating a moderate level overall but exhibiting a declining trend, suggesting an approaching threshold of utilization limits. The range was between 0.3461 and 0.7143. In 2017, the comprehensive proximity index was 0.3461 (low water resource carrying capacity level, with water resources already suffering damage and various subsystems developing uncoordinatedly). However, the comprehensive proximity index for water resource carrying capacity improved significantly from 2018 to 2022. A combination of rising industrial water demand and a decrease in both the absolute volume and proportional allocation of water for ecological purposes drove the overall decline in the progress rate in 2017. Taizhou City has formulated strict water resource management policies and measures, resulting in a decrease in indicators such as industrial water consumption, residential water consumption, and industrial wastewater discharge, as well as an increase in indicators such as ecological water consumption and ecological water utilization rate. As a result, the comprehensive water resource carrying capacity saw a notable rise during 2018–2019. The study results provide a reference for the rational use of water resources in Taizhou City and are of certain significance for promoting the coordinated economic and social development of Taizhou City. Full article

The development of digital technology has changed various aspects of life, including in the financial sector. One of the innovations that has received a significant amount of attention is the PayLater service. Generation Z, as a generation born in the digital era, has a unique consumption pattern. Members of Generation Z tend to look for financial solutions that are fast, practical, and accessible through technology. This study aims to provide guidance for Generation Z (age 20–28 years) in choosing the PayLater application that best suits their needs and financial situation. Using the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method, this study evaluates the effectiveness of several popular PayLater applications. Data were collected through an online questionnaire aimed at potential users who already had a monthly income. The criteria used in the assessment include the average transaction value, difficulty in paying installments, data security and privacy, ease of application access, and interest rates. The results of the analysis show that Shopee PayLater has the highest preference score, making it the best choice for Generation Z. This research is expected to contribute to improving financial literacy and helping Generation Z to make better decisions regarding financial services in the digital era. Full article

Building fires are considered major disasters because of their significant effects on people, property, and the environment. This understanding has led to increased attention on developing preventive measures, particularly through the creation of effective methods for assessing fire risk. However, the effectiveness of these methods relies heavily on detailed physical and functional information of the building and data-driven decision-making. Building Information Modeling (BIM) has proven effective in representing structures, even in three dimensions. When integrated with Geographic Information Systems (GIS), it enhances spatial intelligence, leading to improved decision-making through robust multi-criteria approaches. Hence, this study develops a framework to assess fire risk in an indoor environment that deploys a BIM-based GIS and Multi-Criteria Decision-Making; this is specifically known as Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The developed framework consists of four steps: identifying fire risk parameters, calculating weights, conducting spatial fire risk assessments, and visualizing the results, where the developed concepts are tested and validated. According to the significant findings, the developed framework estimates that 18% of building rooms are at moderate risk, while the compared model identifies only 1%. This considerable difference could potentially arise from the detailed data structure of BIM and the spatial insights gained from GIS. By implementing the designed framework, key fire risk factors can be identified in three dimensions, accompanied by a comprehensive quantitative evaluation platform for fire risks within indoor environments. Full article

Long-term renovation strategies (LTRSs) play a central role in achieving the European Union’s objective of a climate-neutral building stock by 2050. In Poland, the challenge is particularly acute: a majority of the building stock was constructed before 1990 and does not even meet basic thermal performance standards. In view of the state of the buildings in Poland and the assumptions made about obtaining the necessary energy parameters in the coming years, it is necessary to undertake thermal modernization measures. The purpose of the paper is to assess the economic efficiency of the variants of modernization of building stock in Poland, taking into account the constraints related to improving energy efficiency. Additionally, the article also points out the problem of discrepancies resulting from climate zones that may significantly affect the final primary energy results (on average, 5–15%). In order to achieve the objectives, the paper focuses on the analysis of energy sources. According to the overall score in the analytic hierarchy process (AHP) method, the best solutions, with a global priority of 0.46, are renewable energy sources (RESs). The evaluation of selected fuel types in the 2055 perspective, using the technique for order preference by similarity to ideal solution (TOPSIS) method, indicate favorable environmental performance by sources based on electricity, i.e., air-source heat pumps, ground-source heat pumps, and electric heating, which achieved the highest relative closeness to the ideal solution. Heat pump systems can reduce energy consumption by 26–41% depending on the building and heat pump type. The final analysis in the paper concerns different options for thermal modernization of a model single-family house, taking into account different energy sources and stages of thermal modernization work. The scenario involves the simultaneous implementation of all renovation measures at an early stage, resulting in the lowest investment burden over time and the most favorable economic performance. Full article

The specificity of the business of agro-food companies is that their products have little or no impact on the environment. However, environmental pollution of these products is caused by the use of packaging. Therefore, it is necessary to apply the principles of the circular economy in the business of companies. Applying green packaging that has little or no impact on the environment helps in preserving the environment. Companies usually purchase packaging from suppliers and therefore, it is necessary to choose the right supplier from which to purchase green packaging to support the implementation of the circular economy. The aim of this research is to select a green packaging supplier for company X in order to influence the development of a circular economy in the company’s business. Based on this, the following research question is considered in this paper: how can the selection of a green packaging supplier influence the implementation of a circular economy at company X? The research covers ten criteria used in this selection, with which eight suppliers were observed. Because every decision-making process in the economy is characterized by risk and insecurity that affects the uncertainty in decision-making, an intuitionistic fuzzy set (IFS) was used. Determining the importance of weights was performed directly based on the ratings of the decision-maker (DM) and the steps of the SiWeC (Simple Weight Calculation) method, as well as using the Entropy method. The compromise results of these methods showed that the most important criteria for assessing the life cycle of packaging are transparency and ethics in business. The ranking of suppliers was carried out using the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method and its results showed that supplier 5 is the first choice for establishing long-term cooperation in the procurement of green packaging. Full article

The Sanqi–pine agroforestry (SPA) system is considered a sustainable agroforestry model. However, empirical studies that clearly elucidate the impact of Sanqi cultivation on soil fertility and the heavy metal content within the SPA system are still lacking. This study established monoculture Pinus armandii (MPA) and SPA systems to conduct a comparative analysis of dynamic changes in soil physicochemical properties and the heavy metal content of Sanqi and pine over one year (with semi-monthly sampling), followed by a comprehensive evaluation of soil fertility and heavy metal pollution. Following the land use conversion from MPA to SPA, there was a notable increase in soil moisture (SM), total nitrogen (TN), and nitrate nitrogen (NO₃⁻-N) levels within Sanqi soil. Conversely, total potassium (TK), ammonium nitrogen (NH₄⁺-N), plumbum (Pb), and chromium (Cr) levels experienced a significant reduction. In the case of pine soil, soil moisture (SM), pH levels, and ammonium nitrogen (NH₄⁺-N) content exhibited an increase. However, soil organic carbon (SOC), total phosphorus (TP), total potassium (TK), zinc (Zn), manganese (Mn), plumbum (Pb), and chromium (Cr) contents all significantly decreased. The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) demonstrated that Sanqi cultivation not only significantly enhanced soil fertility for Sanqi rather than pine but also reduced the heavy metal content in the soil of both Sanqi and pine within the SPA system. Furthermore, the Nemerow pollution index for both Sanqi and pine soils has decreased, transitioning the pollution status from relatively safe to safe. This suggests that the introduction of Sanqi promotes the sustainable development of the SPA system. Full article

Low-Altitude and Slow-Speed Small (LSS) targets pose significant challenges to air defense systems due to their low detectability and complex maneuverability. To enhance defense capabilities against low-altitude targets and assist in formulating interception decisions, this study proposes a new threat assessment algorithm based on multisource data fusion under visible-light detection conditions. Firstly, threat assessment indicators and their membership functions are defined to characterize LSS targets, and a comprehensive evaluation system is established. To reduce the impact of uncertainties in weight allocation on the threat assessment results, a combined weighting method based on bias coefficients is proposed. The proposed weighting method integrates the analytic hierarchy process (AHP), entropy weighting, and CRITIC methods to optimize the fusion of subjective and objective weights. Subsequently, Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and Dempster–Shafer (D-S) evidence theory are used to calculate and rank the target threat levels so as to reduce conflicts and uncertainties from heterogeneous data sources. Finally, the effectiveness and reliability of the two methods are verified through simulation experiments and measured data. The experimental results show that the TOPSIS method can significantly discriminate threat values, making it suitable for environments requiring rapid distinction between high- and low-threat targets. The D-S evidence theory, on the other hand, has strong anti-interference capability, making it suitable for environments requiring a balance between subjective and objective uncertainties. Both methods can improve the reliability of threat assessment in complex environments, providing valuable support for air defense command and control systems. Full article

As urban buildings become increasingly dense, indoor personnel are often exposed to noise disturbances from adjoining rooms which can reduce working efficiency and affect mental health. Closing the door is one of the ways to reduce noise transmission, but it can cause a decrease in indoor air circulation. This paper investigates the sound insulation effect and air ventilation performance of a door in a partially open state by numerical simulation. To acquire the effect of sound insulation, an acoustic–structural solver is employed to calculate the sound transmission losses with different door opening angles in the frequency domain. To evaluate the ventilation performance, the mass flow rates across door opening are calculated by computational fluid dynamics. The simulation results confirm the trade-off relation between the sound insulation effect and the ventilation performance. To calculate the effect of noise and ventilation on work efficiency, a comprehensive evaluation index workplace environmental score (WES) was introduced and calculated by the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. A clear sound insulation effect corresponds to an opening angle (θ_d) of less than 15° with minimum air ventilation. Good ventilation performance could be obtained when the door opening angle is larger than 45°, while the sound insulation effect is negligible. A good compromise between the sound insulation effect and the air ventilation performance is found to be in the range of θ_d = 15°~25°, which provides practical recommendations in daily routines. Full article

This paper examines the risks linked to E-business collaboration between China and West Africa, with particular emphasis on Ghana as a pivotal digital commerce centre. This research employs the Hesitant Fuzzy Best–Worst Method (HF-BWM) to systematically identify and prioritise the institutional, technological, sociocultural, and legal issues affecting cross-border e-business operations. This study combines Transaction Cost Theory (TCT), the Technology Acceptance Model (TAM), and Commitment–Trust Theory to create a comprehensive framework for analysing the interplay of these risks and their effects on transaction costs and company sustainability. The findings indicate that institutional risks constitute the most substantial obstacles, with deficient digital transaction legislation and inadequate data governance recognised as the principal drivers of uncertainty and increased transaction costs. The research indicates that these institutional challenges necessitate immediate focus, as they immediately affect corporate operations, especially in international digital commerce. Technological risks, such as cybersecurity vulnerabilities, insufficient IT skills, and deficiencies in digital infrastructure, were identified as the second most critical factors, leading to considerable operational disruptions and heightened expenses. Sociocultural hazards, such as language difficulties and varying consumer behaviours, were recognised as moderate concerns that, although significant, exert a weaker cumulative impact than technological and institutional challenges. Eventually, legal risks, especially concerning cybercrime legislation and the protection of intellectual property, were identified as substantial complicators of e-business activities, increasing the intricacy of legal compliance and cross-border contract enforcement. The results underscore the imperative for regulatory reforms, investments in cybersecurity, and methods for cultural adaptation to alleviate the identified risks and promote sustainable growth in China–West Africa e-business relationships. This study offers practical insights for governments, business leaders, and investors to effectively manage the intricate risk landscape and make educated decisions that foster enduring collaboration and trust between China and West Africa in digital trade. Full article