bluuebunny/crossref_metadata_2025 huggingface dataset:
Mineralogical and Physicochemical Characterization of Natural and Heat‐Treated Kaélé Clay Pellets for Pollutant Removal from Tannery Wastewater in Cameroon
Authors: Nko'o Ebio Guillaume , Zangue Adjia Henriette , Njimou Jacques Romain , Motue Waffo Lys Carelle , Noumi Guy Bertrand
Published: January 2025

Water pollution is a critical challenge in developing countries, including Cameroon, necessitating innovative solutions for environmental remediation. This study investigates the formulation and characterization of clay pellets derived from Kaélé clay, focusing on both natural and heat‐treated samples subjected to temperatures of 600, 800, and 1000
°C. Comprehensive mineralogical and physicochemical analyses were performed using FT‐IR, SEM ‐ EDS, TGA/DTG, XRF, and XRD techniques. Results revealed montmorillonite‐type smectite 2:1 as the predominant mineral, highlighting the potential of these clay pellets as effective adsorbents for water purification. Proposed mechanism of pollutant adsorption involves a two‐step process characterized by rapid external diffusion followed by weak interactions between pollutants and the pellet surface, influenced by pH and ionic conditions. Geochemical analysis indicated a high silica (SiO2) content of 44.01%, significant alumina (Al2O3) content of 27.77%, and lower levels of iron oxides (Fe2O3) at 4.55%, along with minimal alkaline (K2O) and alkaline earth (CaO, Na2O, MgO) contents. Rapid elimination of COD by both control and P800 pellets reached equilibrium within 30 minutes, with elimination rates of 86.09% and 98.99% for COD, respectively. This research underscores the innovative use of local clay materials for environmental applications, contributing to sustainable practices in water treatment and pollution control.
Development of Cyclic and Acyclic Fluorescent Chemosensors for Selective Detection of Ions and Biomolecules in Water
Authors: Muwal Pradeep Kumar , Saini Anoop Kumar , Choudhary Komal , Beniwal Vijay , Pani Balaram , Sirohi Siddharth , Mittal Avneesh , Kumar Rajesh , Singh Rohit
Published: January 2025

The intriguing effect of metal ions and biomolecules on various biological entities warrants developing selective and sensitive fluorescent chemosensors in water and other organic solvents. A review of comparable literature in related areas, including material chemistry, environmental science, and supramolecular chemistry, indicates that most of the research work is carried out in varying types of organic solvents. The existing chemosensor research explores the use of various organic solvents, including DMSO/H₂O, methanol, and DMF/HEPES systems, in photoinduced electron transfer (PET)‐based chemosensors. DMSO and DMF are strong polar solvents resulting in strong fluorescence emission. Additionally, dichlorobenzene and chlorobenzene are employed to form selective gels with urea compounds, further improving the sensor's functionality and selectivity. Also, parallel investigations, when carried out in water as a solvent, revealed a decrease in the binding/ detection ability of the guest analytes since the polar molecules form strongly solvated (hydrated) moieties, whereas the non‐polar molecules (or amphiphilic molecules) are found to form aggregations or self‐assemblies. The present review attempts to analyze and characterize water‐soluble fluorescent chemosensors (FCHs) into cyclic and acyclic entities as per their topological and structural architectures. In addition, various seminal examples of synthetic FCHs, included herein, provide an understanding of their rational designs, fundamental properties, supramolecular interactions, and emerging switchable properties in aqueous medium. Thus, the knowledge of the properties of these molecules with high affinity and selectivity would facilitate the synthesis of novel FCHs with potential future applications.
Metabolites in Serum Small Extracellular Vesicles Instead of Small Extracellular Vesicles‐depleted Serum Have Better Diagnostic Value for Cancers at Early Stage
Authors: Su Yun , Peng Zehong , Wang Yuning , Yang Shouzhi , Xu Xiaoyu , Liu Wanshan , Bao Qingui , Jiang Chen , Qian Kun , Fan Xianqun
Published: January 2025

Serum is one of the most commonly used biofluids for biomarker exploration. Some studies examine serum directly, while others focus on specific components like small extracellular vesicles (sEVs), which are lipid‐bilayer encapsulated particles carrying a variety of molecular cargos. However, the diagnostic value of serum sEVs versus sEVs‐depleted fractions (EV‐free serum) for early cancer detection are unclear. In the study, size exclusion chromatography (SEC) is employed to separate serum from prostate cancer (PCa) suspects into sEVs‐enriched fractions (EV) and EV‐free serum. Metabolic fingerprints are obtained using ferric nanoparticle‐assisted laser ablation/ionization mass spectroscopy (FeNPALDI‐MS), revealing heterogeneity in metabolic composition. Eleven key metabolites are identified in EV and two in EV‐free serum that differentiate PCa from benign prostatic hyperplasia. The EV key metabolites showed higher diagnostic value in PCa patients with an area under the curve (AUC) of 0.76, p < 0.05 and improved diagnostic efficacy when combined with the prostate‐specific antigen (PSA, AUC = 0.85).
Simultaneous Quantitative Determination of Five Process Relevant Impurities in Menatetrenone
Authors: Agade Suraj , Bhale Nagesh A. , Pulipati Prakash , Shaik Nagoor Meeravali , Samanthula Gananadhamu , Dikundwar Amol G.
Published: January 2025

Menatetrenone, a form of vitamin K (MK‐4) is used for various pharmaceutical and agrochemical applications. Monitoring and control of process impurities is crucial in the manufacturing of pharmaceutical‐grade Menatetranone. In this article, we report a gas chromatography (GC)‐based analytical method for the detection and quantification of trace levels of five process‐related impurities in MK‐4 originating from the starting materials and reagents. A GC‐flame ionization detector (GC‐FID)‐based method is presented for simultaneous quantitative estimation of five structurally diverse compounds, some of which are conventionally analyzed by liquid chromatography. After a series of method development trials, an optimized method with a mid‐polar column dura bond‐624 (6% cyanopropyl/phenyl and 94% polydimethylsiloxane) with initial column oven temperature 150°C, detector temperature 280°C was finalized for the separation of these impurities. The developed GC‐FID‐based method was validated for specificity, the limit of detection (LOD), the limit of quantification (LOQ), linearity, range, precision, accuracy, and robustness as relevant to the International Council for Harmonization guidelines. The method was found to be highly sensitive for all the constituents with an LOD ranging from 0.05 to 0.43 pg and a limit of quantification of 0.17–1.41 pg, as estimated by the signal‐to‐noise ratios. This is the first report of an analytical method for the simultaneous quantitative determination of five process impurities of MK‐4.
Behavior of Bolted and Plated Steel Dampers Used on Steel Cross Members Applied in RCF
Authors: Bahadir Fatih , Balik Fatih Suleyman , Emir Furkan
Published: January 2025

Steel cross members (SCMs) have been placed between the frame gaps of buildings with insufficient earthquake behavior, and many methods have been developed to strengthen these structures. The application of V‐shaped SCMs into the frame is one of these methods. The biggest problem encountered in the strength of SCMs is buckling in SCMs under the effect of axial load. This buckling in steel elements significantly reduces the contribution of the strengthening application to the reinforced concrete frame (RCF) system. In this experimental study, in strengthening made with SCMs, we aimed to prevent buckling of SCMs under the pressure load. For this purpose, four RCFs with a scale of one‐fourth scale, single span, and single storey, which can reflect the features of existing buildings with insufficient earthquake behavior, have been produced. One RCF is the specimen that we did not strengthen as a reference specimen. Other reference specimen is a specimen with a built‐in support, which is strengthened with SCMs, but no metallic damper is used at the end. The other two specimens were applied at the end of the SCMs with an M5 bolt damper and a steel C plate damper. These specimens were tested under a quasistatic cyclic lateral load while a constant axial load was applied. Because of this study, the metallic dampers formed at the ends of the SCMs made a positive contribution to preventing buckling. It has also been shown that metallic dampers and SCMs increase the initial stiffness values and energy consumption capacities of the specimens.
A Survey Study on the Current Veterinary Practice and Attitudes to Anaesthesia and Analgesia for Spay Surgery in the United Kingdom
Authors: Martino‐Boulton Joanna , Antonopoulou Iliana , Pinnock Hannah , Adami Chiara
Published: January 2025

Background

In the United Kingdom, spay surgery is routinely performed in dogs and cats by general practitioners. Data from a decade ago showed that, despite an increased attentiveness of veterinarians to peri‐operative pain compared to the past, analgesia could be further improved.

Objectives

To investigate the current veterinary practice and attitude towards anaesthesia and analgesia for spay surgery in the United Kingdom.

Methods

An electronic questionnaire composed of 57 questions organised in 6 sections was designed using the Checklist for Reporting Results of Internet E‐Surveys (CHERRIES guidelines) and distributed online via a hyperlink. Participants were recruited through both personalised email invitation and publication of the hyperlink on social media. Data were analysed with descriptive statistics, analysis of means and analysis of proportions, using commercially available software.

Results

Entries from 150 participants were used for data analysis. The proportion of participants who were confident in treating pain did differ by decade of graduation, with a lower proportion of confident colleagues graduated before 2001 (6%) and from 2021 (14%), compared to those graduated in the decades 2001–2010 (43%) and 2011–2020 (37%) (p = 0.007). Colleagues reported to implement multimodal analgesia for spay procedures of cats and dogs in 43% and 44% of cases, respectively. The proportions of participants who reportedly used locoregional blocks, mostly with lidocaine, in dogs (82%), were higher than that in cats (43%) (p < 0.001). Post‐spay surgery pain was perceived by the participants as more intense in dogs than in cats (p < 0.001).

Conclusions

Despite an overall good level of attentiveness of British veterinary professionals to feline and canine analgesia during and following spay surgery, this study identified as areas of improvements perception and assessment of feline pain and implementation of locoregional anaesthetic techniques, particularly in cats.
Caudate lobectomy of a massive hepatic cyst in a Cavalier King Charles Spaniel dog
Authors: Corbarieu Théo , Jossier Renaud , Claeys Stéphanie
Published: January 2025

A 12‐year‐old, female, entire Cavalier King Charles Spaniel was presented with a 15‐month history of abdominal distension. A computed tomography revealed a very large cystic hepatic mass (24 × 18 cm). The caudate liver lobe was removed surgically. Histopathological examination of the mass revealed necrotic tissue and evidence of haemorrhage with tissue remodelling. This was consistent with a cystic lesion, but atypical cells suggest pre‐tumoral cells. The bacterial and fungal cultures were negative. Follow‐up abdominal ultrasound 1 month after surgery showed no recurrence of the cystic lesion; nonspecific splenic nodules and regional lymphadenopathy were noted. This report details the management of a large hepatic cyst in a dog.
Good Practices in Database Generation for Benchmarking Density Functional Theory
Authors: Karton Amir , de Oliveira Marcelo T.
Published: January 2025

The hundreds of density functional theory (DFT) methods developed over the past three decades are often referred to as the “zoo” of DFT approximations. In line with this terminology, the numerous DFT benchmark studies might be considered the “safari” of DFT evaluation efforts, reflecting their abundance, diversity, and wide range of application and methodological aspects. These benchmarks have played a critical role in establishing DFT as the dominant approach in quantum chemical applications and remain essential for selecting an appropriate DFT method for specific chemical properties (e.g., reaction energy, barrier height, or noncovalent interaction energy) and systems (e.g., organic, inorganic, or organometallic). DFT benchmark studies are a vital tool for both DFT users in method selection and DFT developers in method design and parameterization. This review provides best‐practice guidance on key methodological aspects of DFT benchmarking, such as the quality of benchmark reference values, dataset size, reference geometries, basis sets, statistical analysis, and electronic availability of the benchmark data. Additionally, we present a flowchart to assist users in systematically choosing these methodological aspects, thereby enhancing the reliability and reproducibility of DFT benchmarking studies.
Experimental Validation of Virtual Torque Sensing for Wind Turbine Gearboxes Based on Strain Measurements
Authors: Bosmans Jelle , Gallas Simone , Smeets Victor , Kirchner Matteo , Geens Luk , Croes Jan , Desmet Wim
Published: January 2025

In efforts to reduce the operation and maintenance cost of wind turbines, there is an increasing interest to monitor key turbine quantities such as the torque load on the gearbox. Monitoring the torque paves the way for the calculation of remaining useful lifetime, leading to cost reductions through improved reliability and maintenance planning. In order to avoid expensive direct torque sensors, this paper investigates the potential of virtual torque sensing, a technique based on 3 basic components: first, a set of non‐intrusive sensors installed on the gearbox. Three groups of strain gauges on the gearbox as well an angular encoder are considered in this paper. Second is a physics‐based model, capable of predicting the response of aforementioned sensors. These models are constructed with a purposeful balance between accuracy and computational cost. Model validation and updating are performed to ensure efficient and accurate prediction of the sensor output. Finally, an augmented extended Kalman filter (AEKF) is used to combine the measured response with predictions from the model to infer the gearbox input torque. Since a key factor determining the performance of the AEKF is the tuning of the AEKF covariance matrices, multiple methods are introduced to systematically tune the covariance matrices. Experimental validation results show that the virtual torque sensor can detect the load torque with a normalized mean absolute error (NMAE) between 3.41% and 7.47%, depending on the sensor set. The influence of the amount of sensors used and the tuning method are also investigated.
Wind Speed Probability Distribution Based on Adaptive Bandwidth Kernel Density Estimation Model for Wind Farm Application
Authors: Chau Tin Trung , Nguyen Thu Thi Hoai , Nguyen Linh , Do Ton Duc
Published: January 2025

Wind speed variables play an important role in exploiting wind power. However, they are fluctuating and random. Therefore, understanding their characteristics and properties is necessary to improve exploitation efficiency. This research investigates various wind speed distribution models, both parametric and nonparametric, to estimate wind speed probability density (WSPD). The distribution models are implemented on various wind speed datasets with distribution characteristics of varying complexity. The assessment of goodness of fit includes statistical tests including Cramér‐von Mises (CvM), Anderson‐Darling (A‐D), Kolmogorov‐Smirnov (K‐S), and chi‐square (), along with indices correlated as mean absolute percent error (MAPE). The study highlights that the adaptive bandwidth kernel density estimation (AKDE) distribution model based on the nearest neighbor estimation (NNE) has superior goodness of fit performance. Wind turbine power curves are applied to calculate and compare expected, distribution‐based, and empirical power output. In addition, the difference between the power output estimated from the AKDE distribution and the estimate from the empirical wind speed is almost zero, so this estimated power is reliable and can be used as a reference for planning or evaluating wind farm efficiency.
Olive Sector Integrated Artificial Intelligence and Modern Technologies: Model for Palestine
Authors: Hanieh Ahmed Abu , Hasan Afif Akel
Published: January 2025

Olive sector in Palestine suffers from serious problems starting from cultivation process passing through oil extraction process ending with final treatment. Most of the processes depend on old traditional ways away from modern technologies. The main focus of this paper is to put forward some basis and roadmap for implementing artificial intelligence and new technological components in olive sector processes. The hilly nature of Palestine prevents using heavy duty mechanical instruments for harvesting. Most of olive trees are planted on hilly terrains hence requiring the use of light weight hand-held harvesting tools. Soil moisture and nutrition elements can be determined through sensors to decide the necessity to add fertilizers. Olive fruits can be tested to check the oil content and quality before harvesting and extraction process. The final produced virgin oil can be turned to extra virgin oil by implementing further treatment processes where modern technologies are implemented. Modern technologies can also be integrated in post processes of olive sector like touristic wood works, soap manufacturing, olive fruit pickling, and other oil-based food products.
Criteria-Driven Comparison of Hydrogen, Charcoal and Liquefied Petroleum Gas as Cooking Fuels Based on a Systematic Literature Review
Authors: Sturm Lukas , Severengiz Semih , Salokhe Dhanashri Satish , Bhatia Gaurav
Published: January 2025

Green Hydrogen could be used as a sustainable cooking fuel, especially in countries of the global south in which cooking with carbon-based, or biomass fuels is prevalent. This paper presents a criteria based assessment of the sustainability of cooking with hydrogen in comparison to charcoal and liquefied petroleum gas. The research methodology adopts a systematic literature review to provide a comprehensive overview of the research. Based on this, a morphological analysis is conducted to display possible hydrogen cooking scenarios. A chosen hydrogen scenario is then subjected to a sustainability assessment and compared with the aforementioned conventional cooking methods. The findings of this paper reveal that while hydrogen presents itself as a potential alternative, it is currently not a more sustainable option. Despite its lower climate change impact when compared to liquefied petroleum gas and charcoal, hydrogen falls short in several other sustainability aspects, such as investment costs, marine and freshwater eutrophication or safety concerns related to the usage of the energy source.
Innovating Blended Learning Model for Professional Education in Manufacturing
Authors: Krajnik Peter , Hoier Philipp , Laakso Sampsa
Published: January 2025

Advancements in technology and the increasing prevalence of digitalization in industry require a new approach to professional education. The primary objective is to enhance the skills of working professionals, ensure content is relevant to industry needs, increase learner engagement, and optimize learner and instructor efficiency. To achieve these goals, a new methodology is proposed, utilizing constructive alignment, outcome-based education, and blended learning strategies. This approach incorporates asynchronous digital learning, synchronous online lectures, and interactive debriefing sessions, providing an engaging blend of self-paced learning and active, instructor-led experiences. Evaluation results show an improved course structure and a positive learning experience, despite initial implementation challenges. While not exclusively designed for sustainable manufacturing education, this approach offers innovative learning pathways and has the flexibility to integrate specific modules, such as those related to sustainability. Based on evaluation feedback and measurable learner outcomes, ongoing refinements to this model suggest a promising shift in the approach to professional education within the manufacturing sector.
Developing a Framework for Sustainable Education in a Production Engineering Study Program
Authors: Mintchev Maxim , Eingartner Valentin , Muschard Bernd , Oertwig Nicole
Published: January 2025

Given the current challenges faced by the world regarding climate change and the goals outlined by the United Nations in their Agenda 2030 for Sustainable Development, sustainability is increasingly gaining importance in education and industry. To be able to tackle the challenges of responsible consumption and production, societies need to prepare highly skilled and responsibly thinking engineers, who are fit for the market while also contributing actively to the transformative change towards sustainable economies and societies. The international master program Global Production Engineering (GPE) at Technische Universität Berlin aims to impart knowledge on production, engineering, and management with a major focus on sustainability. In this paper, policies of universities locally and worldwide are reviewed and lecturers of GPE are surveyed to determine which sustainability topics and approaches are integrated in their lectures and in the curriculum. From this, a framework for competence building for sustainable development in the economy is developed. The program is then reviewed and found to be teaching some of the core competencies outlined by the Education for Sustainable Development, albeit with a clear potential for improvement. To address this, corrective measures are proposed.
Quantifying the Carbon Footprint of Events: A Life Cycle Assessment-Based Framework for Evaluating Impact of Location and Timing
Authors: Atescan-Yuksek Yagmur , Paddea Sanjooram , Jackson Sharon , Jolly Mark , Salonitis Konstantinos
Published: January 2025

This research proposes a Life Cycle Assessment-based framework to quantify the carbon footprint of events, considering the event's location and timing. The framework aims to standardise environmental impact calculations through inventory analysis. To validate it, a comparative analysis on conducting an event in different locations and time periods, while maintaining similar scale and nature is conducted. The assessment includes emissions from attendee transport, accommodation, food and drink, and venue. Additionally, it considers emission reductions resulting from attendees not using their personal household resources. This accounts for the actual additional emissions released into the atmosphere as a consequence of the event. The results highlight variations in emissions across different consumption categories based on the selected location and timing. By providing this information, the LCA-based framework provides valuable guidance for event organizers and policymakers to assess event environmental impacts and promote sustainability.
Developing a Novel Eco-design Approach for Disassembly Based on Fuzzy Sustainable QFD, Customer Segmentation and Circularity
Authors: Tang Hermès , Keivanpour Samira
Published: January 2025

Design for Disassembly (DfD) is a challenging concept that facilitates the disassembly of products for refurbishing and reusing their components. In the context of circular economy, DfD minimizes value loss at the end of product’s life and remanufacture costs and maximizes environmental benefits. Therefore, DfD considers technical, environmental financial and social factors, but they are rarely integrated. Today, many studies state that the use of Quality Function Deployment (QFD) approach as a decision support tool helps to make choice by promoting one criterion over one another. However, a systematic approach should also consider uncertainties associated with DfD such as technical features, the recovered parts, the disassembly process, and the optimal disassembly sequence due to the product complexity. The current paper analyzes and compares different QFD approaches in the literature review and then provides a new Fuzzy Sustainable QFD (FS-QFD) methodology, which integrates the three pillars of sustainability. Finally, it shows the effectiveness of the suggested approach through a numerical example.
Enabling Aircraft Recycling Through Information Sharing and Digital Assistance Systems
Authors: Keiser Dennis , Pupkes Birte , Otto Thorsten , Reiß Matthias , Poggensee Matthias , Rehsöft Sonja , Terno Antje , Ernits Rafael Mortensen , Freitag Michael
Published: January 2025

Due to the environmental targets of the aviation industry, opportunities for optimization are being explored along the entire life cycle of commercial aircraft. In this context, the recycling of aircraft is increasingly the focus in the aviation industry. Previous research work has therefore examined the overarching recycling process. However, current approaches to improve and increase the aircraft recycling are not sufficient to achieve the defined goals. Based on this motivation, this paper presents first the general challenges of aircraft recycling. Subsequently, the paper shows a conceptual framework whose focus is on the lifecycle phases as well as on its stakeholders and its data. Furthermore, a first conceptual data sharing architecture for the implementation of the approach is introduced. The operationalization in the form of a user interface for a digital assistance system which makes the data available to a recycler in a structured way concludes this paper.
Simulation of an Integrated Manufacturing Remanufacturing System
Authors: Paul Magdalena , von der Horst Teresa , Kerkhoff Felix , Reinhart Gunther
Published: January 2025

In the ongoing European pursuit of a circular economy, remanufacturing has been identified as a crucial strategy for both waste reduction and the attainment of material self-reliance. Remanufacturing offers a promising solution to extend component lifespan and achieve circularity by disassembling, reprocessing, and reassembling returned products to match newly manufactured ones. However, complexities and costs pose significant obstacles, particularly for small and medium-sized enterprises (SMEs), where integrating remanufacturing into existing manufacturing systems can be a solution. The goal of this work is to show how an integrated remanufacturing system can be simulated with conventional software and that the integration could be beneficial for an SME. An approach is suggested and a simulation is conducted on the integration of manufacturing and remanufacturing of water meters. The results of the use case show that for the remanufacturing of water meters, integrating the used products into different points of the manufacturing system could increase the system’s output in general.
Methodology for a Holistic Analysis and Optimization of the Circularity of Products
Authors: Neumann Dominik , Vielhaber Michael
Published: January 2025

Circular economy (CE) is one of the key concepts to improve sustainability through reducing resource dependency and scarcity but increasing resource efficiency. Currently there are no holistic methods to analyze and assess product and material cycles systematically, which would however be a prerequisite to further improve CE. Thus, this contribution presents a methodology for assessing the circularity of products along their whole life cycle. In this way, the greatest potentials for improving circularity can be identified and then iteratively optimized. The methodology is founded on a bottom-up approach and consists of three phases. At the beginning in the data collection phase, all necessary data is gathered and stored in a digital product passport. The key data needed for the assessment are material data (e.g., origin, recycled or primary), energy used, working time from humans and machines, transport routes and involved processes with required tools. In the following evaluation phase, various circularity indicators and a detailed profile of the evaluated product are created. The results are interpreted in the third phase and requirements are derived from the product profile with the indicators to improve the circularity of the product. The methodology is demonstrated on the use case of a spice grinder.
Elaboration of an Operational Methodology for the Development of a Collaboration Platform for the Reuse of Tools and Tool Components
Authors: Schuh Günther , Lukas Gerret , Haase Bernd , Calchera Riccardo
Published: January 2025

Environmental sustainability is becoming increasingly important for tool and die making companies. Tools and tool components are often discarded because they are no longer needed for their original application, although they are often still good to use. Despite the need for environmental sustainability, the concept of circular economy, especially reuse, is not applied. This paper deals with the elaboration of an operational methodology for the development of a collaboration platform for the reuse of tools and tool components.

The analysis of existing methodologies for the development of collaboration platforms that incorporate environmental sustainability and reuse, shows the need for the development of a specific methodology for tooling. In addition, the market demand for tooling and tool components, the environmental impact of tooling reuse, and potential revenue streams for the platform demonstrate the industry need. The methodology includes a specific approach in each phase and includes determined methods and standards to implement it. Overall, the results of each phase of the developed methodology enable the user to develop a platform with a circular economic and waste reduction orientation. Further research is needed for validation as well as practical implementation and further improvement of the methodology for developing collaborative platforms.
Boosting Resource Efficiency and Circular Economy of the Manufacturing Companies in Finland
Authors: Salminen Katri , Kostia Silja , Ijas Mika , Siivonen Jere , Kiviniemi Erkki , Aho Markus
Published: January 2025

Increased resource efficiency and circular economy among manufacturing industry could help to turn sustainability into economic value while simultaneously supporting policy objectives set to decrease CO2 emissions. Overall, this will require changes in organizational strategies, fast uptake of new technologies and skilled workforce. The paper investigates the status of the Finnish manufacturing industry in the uptake of both practices in product design and production, development and future needs in resource efficiency and circular economy in terms of research, skills and investments. A total of 38 Finnish manufacturing companies (18 small and medium size enterprises) answered the survey. The results show that overall Finnish industry considers that the uptake of resource efficiency and circular economy is in at a good level. However, respondents were able to identify several enablers and barriers that could further facilitate the transition towards sustainable manufacturing. Finally, the paper investigates collaboration needs of the manufacturing companies with research organisations and universities in several different sustainable manufacturing technologies such as material efficiency. In the discussion part a collaboration model between a Finnish university and regional manufacturing industry companies is represented and regional testbeds supporting twin transition will be discussed in detail.
Development of a Maintenance Framework for Addressing Power Outage in South Africa
Authors: Behrens Thembeka , Daniyan Ilesanmi , Ale Felix , Ayodeji Sesan Peter
Published: January 2025

In recent times, South Africa has been experiencing power outages, which has significant effect on businesses and economic wellbeing of the nation. To address this challenge, this study develops a maintenance framework that power-generating industries in South Africa can implement. Primary data was collected from company X that is a major subsidiary of the power generating industry in South Africa to probe the root causes of power outages in recent times. The analysis of the data obtained was carried out using Pareto chart. The results obtained identified delay in maintenance operations as one of the possible causes of power outages. The rework job was observed to be tardy by 50 days. This length of days is critical enough to cause power outage. To address this, a framework was developed to assist in effective scheduling of maintenance activities. Hence, this work provides an insight into the possible causes of power outages in South Africa and how they can be mitigated to avoid load shedding.
Sustainable Manufacturing for SMEs: An Agile Readiness Model of Decarbonization Through Theory and Practice
Authors: Tang Xiaohui , Yang Shun , Qian Yanwen , Thiede Sebastian
Published: January 2025

Decarbonization is a critical area as companies work to meet the environmental mandates associated with their environmental, social, and governance (ESG) commitments. It provides significant potentials for the sustainable manufacturing of Small and medium-sized enterprises (SMEs) to match the demands from the downstream value chain. However, SMEs find themselves not ready to take the first step due to a lack of sufficient professional resources. This paper presents a literature review and practical investigation to find out the root causes of decarbonization issues with regard to SMEs. As novel countermeasure, an agile readiness model with consideration of production and environment engineering is developed which allows collectively identifying the current status and targeted performance. Finally, the proposed approach is validated through a case study with industrial partners (in developed countries like Germany and The Netherlands, and emerging countries like China).
System Boundaries, Data Sources and Assessment Methods in the Ecological Evaluation of Complex Assembly Products
Authors: Funk Felix , Franke Jörg
Published: January 2025

Life Cycle Assessment (LCA) has become the most popular method for assessing the environmental impact of products. It is internationally standardized by ISO 14040 and ISO 14044, which outline the general methodology, steps, and issues to be considered. While the standards ensure a consistent general understanding of the method, it does not provide explicit recommendations on the decisions to be made when conducting an LCA. These decisions include, in particular, the definition of system boundaries, the prioritization of data sources, and the selection of appropriate assessment methods. For some industries, particularly raw materials and process goods, the gap has mostly been filled by industry standards. The vast number of manufactured goods that are the result of complex assemblies originating from multi-tiered supply chains still lack such industry standards. This work addresses the issue by conducting a thorough literature review on the subject. As a result of the literature review, methodological gaps are identified and quasi-standards are derived from previous studies, thus providing general guidance for future LCA of complex assembly products.
Towards Real-Time Condition Monitoring of Electroplating Plants
Authors: Lindner M. , Duckstein R. , Mennenga M. , Herrmann C.
Published: January 2025

For securing a high-quality plating process, one of the main challenges in electroplating is the dosing of electrolytes. The optimal dosing and the related demand for resources do not only influence the coating quality but can also have a high environmental and economic relevance. Currently, the condition monitoring approaches related to dosing are mostly model-based and are seldom real-time capable. Therefore, a concept for real-time data-based condition monitoring of electrolytes is proposed. The paper discusses the challenges of pre-processing and modeling time series data with machine learning algorithms and quality requirements and availability of data within the electroplating process. Moreover, the usage of neural networks for condition monitoring of time series data is presented and discussed in a case study with a focus on anomaly detection. With this example, the applicability of a data-based approach for dynamic prediction of electrolyte chemicals is presented and evaluated.
Planning and Control of Value Creation Networks in Timber Construction
Authors: Orozco Sebastian , Oertwig Nicole , Feldhaus Annika , Eingarnter Valentin , Mintchev Maxim , Kohl Holger
Published: January 2025

Almost 40 percent of the global carbon emissions are caused by the construction and building sector. Additionally, the production of traditional building materials like concrete and steel requires a large amount of energy. The demand for residential buildings is increasing none the less and can potentially be met by utilizing more sustainable materials like timber in construction. However, timber construction is still connected to a rather manual value creation chain and analog information transfer. To make the process more time- and energy efficient, this paper proposes a framework for the value creation system of urban timber construction from the forest to the city. The three-leveled framework, based on the principles of Industry 4.0, connects the urban development planning with the vertical networking of digital technologies and the horizontal networking in the value chain. The framework is implemented to a dashboard using Microsoft Power BI to demonstrate the close relations of the layers.
Technologies and Concepts for E-Waste Treatment in Urban Secondary Raw Material Factories
Authors: Meyer Kolja , Görgens Severin J. , Persch Christoph , Dröder Klaus , Herrmann Christoph
Published: January 2025

Supply chains for cities are currently challenged due to geopolitical conflicts and general resource scarcity of substantial raw materials. One currently discussed strategy to reduce the dependency of external supply is a relocalization of production facilities to cities enabling local secondary raw material extraction integrated in Circular Economy value creation chains. Urban regions offer the potential for the installation of circular and secondary raw material factories because of the concentration of waste- and byproducts, which can reduce transport efforts. The installation of urban factories is however highly dependent on the economic feasibility as well as the acceptance of the local environment. One critical source for the retrieval of critical raw materials are e-wastes. The current retrieval of these critical raw materials from e-wastes is connected to high spatial requirements and production volumes. These characteristics would hamper an installation in urban areas. Current literature provides different approaches with the intention to adapt e-waste treatment to these special conditions. To assess which of these are suitable for utilization in urban environments, this paper provides an analysis of their possibility to generate an urban fit. To do so, criteria containing ecologic, social, and economic, technological indicators are defined and an assessment of the suitability is conducted.
Optimal Design of Pipeline Networks for Inter-plant Water and Energy Integration
Authors: Piccoli Renzo O. , Trucco Diego J. , Presser Demian J. , Cafaro Diego C.
Published: January 2025

The concentration of specific industries in relatively small areas exists in many countries. This characteristic incentivizes cooperation and facilitates the optimal use of common resources. That is the case of the cluster of crop and chemical manufacturing industries in the center of Argentina, next to the Parana River. All of these plants are closely linked to the use of water streams in associated processes. The objective of this work is to minimize the overall costs of water and energy consumption through the optimal design of an inter-plant pipeline network. This is achieved by considering the daily availability and demand of hot water at each node over time, while ensuring that all pipelines are capable of reversing flows, if needed, at the expense of specific equipment and operating costs. The optimization model developed in this work can be categorized as a MILP formulation that considers fluid dynamics variables, temperatures, energy and flow in order to properly determine the pipeline diameters. The construction and operation of water pipelines in concentrated industrial regions can leverage positive impacts on the sustainable use of natural resources. In contrast to previous contributions, explicit consideration of flow reversals offers benefits that can significantly reduce investment costs.
Empirical Investigation into the Drivers of Green Manufacturing Technologies
Authors: Shukla Ganesh Prasad , Gupte Pranav
Published: January 2025

Global manufacturing sectors are progressively using state-of-the-art green technologies (GTs) to alleviate the detrimental effects of production on the environment. Adoption of GTs is motivated by a number of variables referred to as drivers. Although a variety of drivers and GTs are described in the literature, few models demonstrate the intricate relationships that occur between them. Although there are evidences that drivers might be distinctive for every particular GT in a given business, there is a dearth of empirical study on how and to what extent the drivers are influencing the adoption and implementation of GTs. To address these gaps, this study first categorizes drivers and GTs based on existing literature. Subsequently, a theoretical framework is developed grounded in natural resource-based view (NRBV), establishing the link between adoption of specific GTs and their potential drivers through the development of enabling key resources. A case study of an Indian steel manufacturing company is conducted to empirically test the framework by analyzing various implemented green initiatives. Observed compliances and deviations to the framework are examined. Additionally, this research offers valuable insights to manufacturing managers for GT selection and recommends avenues for future research in this domain.
Optimizing GHG-Emissions in Milling by Integrating Electricity Mix Data into Manufacturing Parameter Decisions
Authors: Karnapp Sebastian Felix , von Elling Magnus , Sarikaya Erkut , Weyand Astrid , Weigold Matthias
Published: January 2025

Industry is responsible for approximately 25% of global greenhouse gas (GHG) emissions, contributing substantially to climate change. Sustainable manufacturing has therefore become a significant topic of discussion, resulting in a better understanding of key GHG emitters in milling processes. This paper investigates the influence of different compositions of the German electricity mix on the CO2-eq. Emissions of a milled steel disc defined by the Product Carbon Footprint (PCF). Using more wind and solar energy reduces CO2-eq. Emissions significantly in comparison to an energy mix almost without green energy types. The cradle-to-gate PCF of the investigated steel workpiece ranges from 8.44 to 11.91 kg CO2-eq., corresponding to a 41.18% increase caused solely by alternations in the energy mix composition. Feed rate was selected as the parameter for the optimization of the PCF, suggesting maximizing the feed rate to shorten production times. Emissions directly attributable to the milling process can be reduced by 11.59% and 16.93%, respectively in the two scenarios. Expected increase in cost and varying surface quality due to increased tool wear were not part of this investigation. This approach demonstrates the potential for environmentally sustainable manufacturing strategies by integrating electricity mix data into manufacturing parameter decisions.
Data-Driven Approach for a Continuous Information Flow in a Closed-Loop Supply Chain
Authors: Letzgus Celine , Kirsch Jennifer Alica , Bauernhansl Thomas
Published: January 2025

Due to the large variety of actors, channels, and materials involved, the processes of the circular economy are very complex. This complexity makes it difficult to maintain consistent data quality throughout the supply chain. Circular processes can only be applied extensively if enough data, for example supplier information, is available. Data and information from suppliers, manufacturers, end-users, and recyclers are not shared transparently through circular processes. One reason is the insufficient support from IT systems for data exchange between the different parties. To improve data exchange, a product-independent process view of the closed-loop supply chain based on the supply chain operations reference model is introduced in this work. Then, an approach is presented to improve data quality in closed-loop supply chain processes through data-based models. The human-in-the-loop method is used to capture data and enable integration of this approach in IT systems for closed-loop supply chains. Therefore, a more transparent data flow laying the foundation for improved data quality throughout the supply chain can be achieved.
Digital Technologies Enabling Resilience in Manufacturing Networks
Authors: Koutrakis Nikolaos-Stefanos , Magnanini Maria Chiara , Uhlmann Eckart , Polte Julian , Pei Eujin , Psarommatis Foivos , Brintrup Alexandra
Published: January 2025

Unforeseen events have the potential to cause disruptions throughout the entire manufacturing value chain, ranging from interruptions in production processes on the shop floor level to shutdowns in the supply chain and logistics. These disruptions increase the necessity for the establishment of manufacturing networks that prioritize cooperation and circularity to strengthen resilience, predict and counteract such impacts. This paper provides an overview of the main digital technologies required to create a resilient and sustainable manufacturing network and the implementation of the Manufacturing as a Service (MaaS) approach. For each digital technology, a synthetic characterization is provided, with respect to requirements, exemplary applications and involved standards. Challenges on the use of such technologies are presented and suggestions for future developments on the integration and deployment of digital technologies with the aim of achieving resilience in manufacturing networks is described.
Deep Learning-Based Optical Character Recognition for Identifying On-Label Printed Part Numbers of Used Automotive Parts: A Comparative Study of Open Source and Commercial Methods
Authors: Schlüter Marian , Tepper Christian , Briese Clemens , Kroeger Ole , Vicente-Garcia Raul , Krüger Jörg
Published: January 2025

This paper explores the use of deep learning-based optical character recognition (OCR) to identify part numbers for used automotive parts. It compares open source and advanced AI methods to commercial tools from Google, Amazon, and Microsoft. The study finds that fine-tuned open source models outperform commercial services, especially for complex part numbers unrelated to any language structure. The preferred open source method, MaskedTextSpotter, is fine-tuned with image data from old vehicle and electrical parts, captured by a smartphone and 2D barcode scanner. Additionally, a new data augmentation method, CharChan, is introduced, replacing detected characters with random examples for better character recognition. The experiments demonstrate the efficacy of deep learning-based OCR for automotive part number identification.