Search Results (288)

A damping spacer rod is a key protective device in ultrahigh voltage transmission lines, which not only keeps the distance of split wires and limits the whipping and collision caused by the relative motion between sub-wires, but also inhibits the vibration of wires. This study aims to solve the problem of typical faults, such as loose wire clamps, that are prone to occur in damping isolation rods during long-term operation in ultra-high voltage transmission lines. Taking the spacer rod FGZ-450/34B as the object, a new high-pressure casting process for spacer rod frames is explored. The spacer rods were simulated by using the ABAQUS finite element software to predict the stress distribution and identify the dangerous sections. Based on this, the mold process was optimized to avoid die-casting defects. Meanwhile, mechanical property tests were carried out on the products produced by the two types of molds. The research finds that by optimizing the mold process, the die-casting quality of the dangerous section of the spacer rod can be effectively improved, and the best high-pressure die-casting scheme has been obtained through comparison. This research achievement provides technical support for enhancing the anti-vibration performance, anti-loosening reliability, short-circuit current thermal shock resistance, and anti-ultraviolet aging performance of damping isolation rods. It is of great significance for ensuring the stable operation of ultra-high voltage transmission lines and improving the production process level of damping isolation rods. Full article

High genetic variation in African indigenous chicken populations provides opportunities for long-term genetic improvement. This study estimated genetic parameters for economic traits based on data derived from a nucleus flock comprising two generations, derived from 40 sires and 200 dams in a line breeding program through mass selection. Body weight (BW) at different weeks was analyzed for 1370 chickens. Similarly, egg performance was evaluated on 473 hens kept for 44 weeks. Genetic parameters were estimated using a multi-trait animal model based on an average information-restricted maximum likelihood (AI-REML) algorithm in WOMBAT software. Body weight showed significant heritability (p < 0.001), ranging from 0.251 for body weight at 8 weeks of age (BW8) to 0.34 for body weight at 16 weeks of age (BW16), indicating a good genetic improvement potential. Egg production traits had low to moderate heritability (0.08–0.37). Positive genetic correlations among growth traits, particularly BW8 and body weight at 12 weeks of age, BW12 (rG = 0.94), suggest shared genetic influences and the possibility of improving multiple traits simultaneously. The genetic correlation between BW16 and the cumulative egg number varied from low and negative (−0.02) in the first two months to high (0.51) in the cumulative egg number over six months, suggesting that heavier birds lay more eggs over time. Our limited dataset based on two generations and pedigree demonstrates that BW16 with egg production has moderate heritability and strong genetic correlations that can lead to genetic progress toward the development of a dual-purpose breed, and this offers a scientific basis for breeders to develop selection indices to develop a dual-purpose breed for smallholder production systems. Full article

This article presents a systematic literature review aimed at identifying challenges and opportunities for integrating sustainability into the digital product lifecycle. The review followed the PRISMA 2020 guidelines and involved a comprehensive search across three databases—Web of Science, Scopus, and ScienceDirect—using structured Boolean queries. A total of 377 records were retrieved, and after duplicate removal and a multi-stage screening process based on predefined inclusion and exclusion criteria, 56 peer-reviewed studies were selected for analysis. These studies were examined in relation to how they addressed environmental, social, and economic dimensions throughout the digital product lifecycle and UX/UI design. Key challenges identified include high energy consumption, limited user awareness of environmental impacts, and the exclusion of vulnerable populations from digital solutions. Opportunities include the adoption of sustainable design strategies, the application of Life Cycle Assessment (LCA), co-design practices, and data-driven decision-making tools. The findings were synthesized into a conceptual framework structured across three lifecycle stages—pre-development, development, and post-development—and mapped to six sustainability requirements. This study contributes to the field by aligning digital innovation with the Sustainable Development Goals (SDGs) and offering a theoretical foundation for the development of practical frameworks and indicators that support sustainable digital product development. Full article

High-precision 6D pose estimation for pick-and-place operations remains a critical problem for industrial robot arms in manufacturing. This study introduces an analytics-based solution for 6D pose estimation designed for a real-world industrial application: it enables the Staubli TX2-60L (manufactured by Stäubli International AG, Horgen, Switzerland) robot arm to pick up metal plates from various locations and place them into a precisely defined slot on a brake pad production line. The system uses a fixed eye-to-hand Intel RealSense D435 RGB-D camera (manufactured by Intel Corporation, Santa Clara, California, USA) to capture color and depth data. A robust software infrastructure developed in LabVIEW (ver.2019) integrated with the NI Vision (ver.2019) library processes the images through a series of steps, including particle filtering, equalization, and pattern matching, to determine the X-Y positions and Z-axis rotation of the object. The Z-position of the object is calculated from the camera’s intensity data, while the remaining X-Y rotation angles are determined using the angle-of-inclination analytics method. It is experimentally verified that the proposed analytical solution outperforms the hybrid-based method (YOLO-v8 combined with PnP/RANSAC algorithms). Experimental results across four distinct picking scenarios demonstrate the proposed solution’s superior accuracy, with position errors under 2 mm, orientation errors below 1°, and a perfect success rate in pick-and-place tasks. Full article

The growing complexity of production systems in the technology sector demands advanced tools to ensure efficiency, flexibility, and cost-effectiveness. This study presents the development of a simulation model for a selective soldering line at a technology manufacturing company in Poland, created during an engineering internship. Using FlexSim 24.2 software, the real production process was replicated, including input/output queues, manual insertion (MI) stations, soldering machines, and quality control points. Special emphasis was placed on implementing dynamic process logic via ProcessFlow, enabling detailed modeling of token flow and system behavior. Through experimentation, various configurations were tested to optimize process time and the number of soldering pallets in circulation. The results revealed that reducing pallets from 12 to 8 maintains process continuity while offering cost savings without impacting performance. An intuitive operator panel was also developed, allowing users to adjust parameters and monitor outcomes in real time. The project demonstrates that simulation not only supports operational decision-making and resource planning but also enhances interdisciplinary communication by visually conveying complex workflows. Ultimately, the study confirms that simulation modeling is a powerful and adaptable approach to production optimization, contributing to long-term strategic improvements and innovation in technologically advanced manufacturing environments. Full article

This study investigates the effectiveness of the Xsens motion capture system in performing ergonomic analysis compared to traditional manual assessments by experts in the specific environment of assembly lines. A comprehensive literature review emphasizes the need to investigate the reliability of new, promising high-tech systems. The main objective was therefore to compare the Ergonomic Assessment Worksheet (EAWS) assessment approach performed with Xsens motion capture technology and Process Simulate V16 software with the manual method using EAWS digital prepared by experts in the controlled workflow. The greatest value of the research conducted lies in the novel integration of the state-of-the-art Xsens motion capture technology with the Process Simulate V16 software environment and the use of the licensed EAWS ergonomic method and Methods-Time Measurement Universal Analyzing System (MTM-UAS). The results are presented in the form of a case study. The results show a large similarity between the whole-body results and a large difference in the upper limb results, confirming the initial benefits of the Xsens equipment but also pointing to the need to verify its reliability on larger samples. The study highlights the potential of integrating Xsens motion capture data into ergonomic assessments and tuning of the assembly line to increase productivity and worker safety. Full article

In the highly competitive manufacturing environment of today, operational success depends on increasing efficiency and cutting waste. The goal of this research is to use Arena simulation software to model a CNC production system to assess and improve system performance. Three different parts are processed by the model, which also includes rework loops in which a portion of faulty products are sent back for further processing. Finding bottlenecks, evaluating important performance metrics such as output, queue lengths, waiting times, and machine utilization, and testing improvement scenarios are the primary goals. Study findings indicate that waiting times were greatly shortened and resource usage was balanced in alternative scenarios, which were accomplished by shifting workloads, line balancing, and modifying inter-arrival durations. The results demonstrate how well simulation can represent and resolve inefficiencies in intricate industrial systems. Manufacturers may optimize manufacturing processes without interfering with ongoing operations thanks to this method, which encourages educated decision-making. Full article

With the increasing demand for near real-time atmospheric water vapor monitoring, this study evaluates the performance of the open-source PRIDE PPP-AR software (version 3.0.5) for retrieving Zenith Total Delay (ZTD) and Integrated Water Vapor (IWV) over the African continent over a one-year period. PRIDE PPP-AR is compared with established PPP-AR and PPP solutions, including CSRS-PPP, IGN-PPP, and NGL and using GipsyX, ERA5, and IGS products as references. A robust methodology combining time series processing and statistical evaluation was adopted. Multiple tools were leveraged to ensure a comprehensive performance analysis of GNSS data from seven stations in Africa, where such studies remain scarce. The results show that PRIDE PPP-AR achieves ZTD accuracy comparable to GipsyX (RMSE < 6 mm, R² ≈ 0.99) and performs at a similar level to NGL and CSRS-PPP. Compared to the other solutions, PRIDE PPP-AR has an accuracy similar to CSRS-PPP and NGL, but slightly better than IGN-PPP, in line with ERA5 and IGS references. For IWV retrieval, comparisons with ERA5 indicate RMSE values of about 1.5 to 2.7 kg/m², depending on station location and climatic conditions. IWV variability tends to increase towards the equator, where the recorded fluctuations are higher than in subtropical zones. In addition, collocated radiosonde (RS) measurements in Abidjan confirm good agreement, further validating the reliability of the software. This study highlights the potential of GNSS meteorology, in providing reliable spatiotemporal IWV monitoring and indicates that the PRIDE PPP-AR is ready for the high precision meteorological applications in African regions. These results offer promising prospects for spatiotemporal studies through African multi-GNSS networks and the PRIDE PPP-AR approach. Full article

Digital agriculture has rapidly developed in the last decade in many countries where the share of agricultural production is a significant part of the total volume of gross production. Digital agroecosystems are developed using a variety of IT solutions, software and hardware tools, wired and wireless data transmission technologies, open source code, Open API, etc. A special place in agroecosystems is occupied by electronic payment technologies and blockchain technologies, which allow farmers and other agricultural enterprises to conduct commodity and monetary transactions with suppliers, creditors, and buyers of products. Such ecosystems contribute to the sustainable development of agriculture, agricultural engineering, and management of production and financial operations in the agricultural industry and related industries, as well as in other sectors of the economy of a number of countries. The introduction of crypto solutions in the agricultural sector is designed to create integrated platforms aimed at helping farmers manage supply lines or gain access to financial services. At the same time, there are risks of illegal use of computing power for cryptocurrency mining—cryptojacking. This article offers a thorough risk assessment of cryptojacking attacks on endpoint systems, focusing on identifying critical vulnerabilities within IT infrastructures and outlining practical preventive measures. The analysis examines key attack vectors—including compromised websites, infected applications, and supply chain infiltration—and explores how unauthorized cryptocurrency mining degrades system performance and endangers data security. The research methodology combines an evaluation of current cybersecurity trends, a review of specialized literature, and a controlled experiment simulating cryptojacking attacks. The findings highlight the importance of multi-layered protection mechanisms and ongoing system monitoring to detect malicious activities at an early stage. Full article

The tonal system of Cantonese is very different from that of Mandarin, which creates potential challenges for Mandarin speakers when learning Cantonese. The aim of this study was to explore second language (L2) production of Cantonese tones by advanced learners whose first language (L1) is Mandarin. Forty-one informants participated in a recording experiment to provide production data of Cantonese tones. The speech data were measured acoustically using the computer software Praat (Version 6.3.10) and were evaluated perceptually by native Cantonese speakers. The relationship between the acoustic analysis and perceptual evaluation was also explored. The acoustic and perceptual evaluations confirmed that, while the tones that the Mandarin learners of Cantonese produced were non-native-like, their production of the Cantonese T1 and T2 was good in general. Furthermore, the accuracy of the perceptual evaluations could be predicted based on the acoustic features of the L2 tones. Our findings are in line with hypotheses in current speech learning models, and demonstrate that familiar phonetic categories are easier to acquire than are unfamiliar ones. To provide a more complete picture of L2 speech acquisition, future research should investigate L2 tone acquisition using both production and perception data obtained from participants with a greater variety of L1s. Full article

In this study, a Life Cycle Assessment (LCA) was conducted to evaluate the environmental impact of osmotically dehydrated, fresh-cut, pre-packaged potatoes compared to conventional untreated ones. The case study focused on a small processing line in Naxos Island, Greece, aiming to extend shelf-life by up to 5 days. The analysis covered the full value chain, from cultivation to household consumption, considering changes in energy and material use, transport volumes, waste generation, and cultivation demand. Three scenarios were assessed: (i) conventional untreated potatoes, (ii) dehydrated potatoes using market glycerol, and (iii) dehydrated potatoes using glycerol from vegetable oil treatment. Systems and life cycle inventories (LCI) were modelled in OpenLCA v2.4 software with the ecoinvent v3.11 database, applying the Environmental Footprint (EF) method, v3.1. The selected impact categories included the following: global warming potential, water use, freshwater ecotoxicity, freshwater and marine eutrophication, energy resource use, particulate matter formation, and acidification. Results showed that applying osmotic dehydration (OD) improved environmental performance in most, but not all, categories. When market glycerol was used, some burdens increased due to glycerol production. However, using glycerol from vegetable oil treatment resulted in reductions of 25.8% to 54.9% across all categories compared to the conventional scenario. Overall, OD with alternative glycerol proved to be the most environmentally beneficial approach. Full article

Open Source Software (OSS) development is a complex socio-technical system in which collaborator attitudes influence the outcomes. This study empirically analyzes the impact of participant sentiment (positive, neutral, negative) on productivity, defined by Pull Requests (PR), Lines of Code (LoC), and interactions (as indicated by comment volume). Data on PRs, LoC, and comments, were collected from 20 top GitHub repositories. SentiStrength-SE was used to classify participant sentiment based on average comment sentiment. Appropriate nonparametric statistical and correlation analyses were performed. The results showed that contributors with positive sentiments have the highest productivity and interaction. Negative-sentiment contributors also significantly outperform the neutral group in both areas. The neutral group consistently ranks the lowest. The general patterns are as follows: positive > negative > neutral. The strongest positive correlations between productivity and interaction are observed in the positive-sentiment group. These findings empirically demonstrate that the sentiment levels of collaborators are significantly associated with OSS productivity and engagement, offering insights into socio-technical dynamics. Fostering a positive environment is a key strategy for enhancing OSS performance and sustainability. Full article

This study addresses the challenges associated with virtual–real interactions, the limitations of one-dimensional data presentation, restricted real-time functionalities, and the lack of effective models for monitoring production line status. It specifically investigates intelligent production lines for automotive wheels as the focal point of the research. This study explores the construction methodology and the application of intelligent production lines through the utilization of digital twin technology. A hierarchical design approach is employed, integrating industrial Internet of Things (IoT) technology to create a comprehensive digital twin system. This system consists of four layers: the physical production line layer, the data acquisition and processing layer, the digital twin production line layer, and the application service layer. Precise mapping from the physical production line to the digital twin model is achieved using the advanced 3D modeling and simulation software, PQ Factory, while real-time data collection and transmission are facilitated through the standardized OPC UA protocol. The effectiveness of the system is substantiated through a detailed case study. The findings demonstrate that the intelligent production line system, which leverages digital twin technology for automotive wheels, enables real-time monitoring of the production process and provides innovative solutions, along with a robust theoretical framework for comprehensive analysis, diagnosis, evaluation, optimization, prediction, and decision making in the production of automotive wheels. Full article

Pharmaceutical production typically focuses on individual drug types for each production line, which limits flexibility. However, the emergence of Industry 4.0 technologies presents new opportunities for more adaptable and customized manufacturing processes. Despite this promise, the development of innovative design techniques for pharmaceutical production equipment remains incomplete. Manufacturers encounter challenges due to rapid innovation cycles while adhering to stringent Good Manufacturing Practice (GMP) standards. Our research addresses this issue by introducing an information model that organizes the design, development, and testing of pharmaceutical manufacturing equipment. This model is based on an exploratory review of 176 articles concerning design principles in regulated industries and integrates concepts from Axiomatic Design, Quality by Design, Model-Based Systems Engineering, and the V-Model framework. Further refinement was achieved through insights from 10 industry experts. The resultant workflow-based information model can be implemented as software to enhance engineering and project management. This research offers a structured framework that enables pharmaceutical equipment manufacturers and users to collaboratively develop solutions in an iterative manner, effectively closing the gap between industry needs and systematic design methodologies. Full article

The innovative pressure device, developed to address contamination issues on Essity Slovakia’s carton production line, was successfully implemented using 3D printing technology. This approach resulted in a precise prototype that significantly reduces contamination, simplifies packaging procedures, and lessens the need for manual labor. The project entailed a comprehensive review of the current system, 3D scanning, creation of a model using SolidWorks software, and fabrication with a Trilab DeltiQ 2 printer. The outcomes demonstrate a staggering 96% decrease in contamination, elimination of downtime, and a boost in overall line efficiency. This research underscores the transformative capabilities of additive manufacturing in industrial modernization and accentuates the significance of technological advancements in enhancing efficiency, sustainability, and quality within the manufacturing industry. Full article