Search results for: efficient production

Authors: Shuhua Lai, Kairui Chen

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In this paper, we present a fast and efficient mesh coarsening algorithm for 3D triangular meshes. Theis approach can be applied to very complex 3D meshes of arbitrary topology and with millions of vertices. The algorithm is based on the clustering of the input mesh elements, which divides the faces of an input mesh into a given number of clusters for clustering purpose by approximating the Centroidal Voronoi Tessellation of the input mesh. Once a clustering is achieved, it provides us an efficient way to construct uniform tessellations, and therefore leads to good coarsening of polygonal meshes. With proliferation of 3D scanners, this coarsening algorithm is particularly useful for reverse engineering applications of 3D models, which in many cases are dense, non-uniform, irregular and arbitrary topology. Examples demonstrating effectiveness of the new algorithm are also included in the paper.

Keywords: coarsening, mesh clustering, shape approximation, mesh simplification

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Authors: Shengnan Chen, Shuhua Wang

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Successful production of hydrocarbon from unconventional tight oil reserves has changed the energy landscape in North America. The oil contained within these reservoirs typically will not flow to the wellbore at economic rates without assistance from advanced horizontal well and multi-stage hydraulic fracturing. Efficient and economic development of these reserves is a priority of society, government, and industry, especially under the current low oil prices. Meanwhile, society needs technological and process innovations to enhance oil recovery while concurrently reducing environmental impacts. Recently, big data analysis and artificial intelligence become very popular, developing data-driven insights for better designs and decisions in various engineering disciplines. However, the application of data mining in petroleum engineering is still in its infancy. The objective of this research aims to apply intelligent data analysis and data-driven models to exploit unconventional oil reserves both efficiently and economically. More specifically, a comprehensive database including the reservoir geological data, reservoir geophysical data, well completion data and production data for thousands of wells is firstly established to discover the valuable insights and knowledge related to tight oil reserves development. Several data analysis methods are introduced to analysis such a huge dataset. For example, K-means clustering is used to partition all observations into clusters; principle component analysis is applied to emphasize the variation and bring out strong patterns in the dataset, making the big data easy to explore and visualize; exploratory factor analysis (EFA) is used to identify the complex interrelationships between well completion data and well production data. Different data mining techniques, such as artificial neural network, fuzzy logic, and machine learning technique are then summarized, and appropriate ones are selected to analyze the database based on the prediction accuracy, model robustness, and reproducibility. Advanced knowledge and patterned are finally recognized and integrated into a modified self-adaptive differential evolution optimization workflow to enhance the oil recovery and maximize the net present value (NPV) of the unconventional oil resources. This research will advance the knowledge in the development of unconventional oil reserves and bridge the gap between the big data and performance optimizations in these formations. The newly developed data-driven optimization workflow is a powerful approach to guide field operation, which leads to better designs, higher oil recovery and economic return of future wells in the unconventional oil reserves.

Keywords: big data, artificial intelligence, enhance oil recovery, unconventional oil reserves

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Authors: Omuvwie R. Ewien

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Palm oil production in Delta State, Nigeria, is a significant economic activity. However, ensuring its sustainability is crucial to mitigate environmental impacts, promote social equity, and maintain long-term economic viability. This abstract provides an overview of palm oil production sustainability in Delta State, focusing on environmental, social, and economic aspects. In terms of environmental sustainability, the impact of palm oil plantations on deforestation and biodiversity loss is explored. The adoption of sustainable land use practices and measures to reduce greenhouse gas emissions, such as conserving high conservation value areas and utilizing methane capture systems, are highlighted. Social sustainability considerations encompass the inclusion and empowerment of smallholders, ensuring fair labor practices and community engagement. Supporting small-scale farmers, promoting fair working conditions, and investing in local infrastructure and services are identified as key strategies. Economic sustainability is emphasized through yield improvement, efficiency, and value addition. Enhancing productivity and profitability for farmers, promoting downstream processing and market diversification, and building economic resilience is crucial for long-term sustainability. Government policies, including regulatory frameworks and public-private collaborations, play a pivotal role in promoting sustainable palm oil production. Enabling policies and partnerships with industry stakeholders and NGOs facilitates the adoption of sustainable practices. Challenges such as illegal activities, the need to balance economic development with environmental conservation, and leveraging technology for sustainability are discussed. The abstract concludes by emphasizing the importance of stakeholders' commitment to prioritize sustainable palm oil production in Delta State, Nigeria, for a sustainable future.

Keywords: palm oil production, environmental sustainability, community development, yield improvement, future outlook

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Authors: Jotham Mazhura

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Floriculture production is an ideal project for sustainable horticultural production in Masvingo city.Gender links in collaboration with the embasy of Sweedenare supporting the floriculture project with the aim of improving residents livelihoods in the city.World trade in floriculture such as cut flowers,live ornamental plants and foliage continue to increase and there are recognised markets opportunities across the globe.Some specific opportunitiesin an interview discussion by the consultant appointed by gender links and embasy of Sweeden highlightedsome constraints and opportunities in the project of floriculture in Masvingo city.Based on the outcome of the scoping studies this research project developed and evaluated strategies for enhancing floriculture production in Masvingo city. A survey was therefore carried out by the researcher among the existing florists farmers in the city to determine strategies to be employed to improve floriculture production.The survey was conducted to twenty florists in the city.The sample was taken by using purposive sampling which is a sampling technique based on the certain considerations, hence there were some basic creteria in selecting samples. A questionnaire in this aspect was administered to the 20 florists to determine the essential strategies to be employed to enhance floriculture production.Each respondent was given data for the business strategies and asked to rank those strategies from the most to the least important.From the research findings the following were revealed out by the respondents that is capturing marketshare,establishment of of ownership of the project,the project manager to be innovative,the business should gain competitive strategic through generic strategies market development strategy and product development strategy. Based on the observation and structured interview with respondents the average of floriculture owners had similar strategies implemented on their business.The research proved that floriculture farmers use various strategies to keep their businesses running and succeding in achieving set goals.Therefore the ressearche who happens to be the project focal person became certain that it is edeal to emply a variety of of strategies to improve floriculture oproduction

Keywords: florist, floriculture, strategy, livelihoods

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Authors: Julius Denafas, Irina Kliopova, Gintaras Denafas

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Three opportunities for implementation of industrial ecology principles in the real industrial production of c-Si solar cells and modules are presented in this study. It includes: material flow dematerialisation, product modification and industrial symbiosis. Firstly, it is shown how the collaboration between R&D institutes and industry helps to achieve significant reduction of material consumption by a) refuse from phosphor silicate glass cleaning process and b) shortening of SiNx coating production step. This work was performed in the frame of Eco-Solar project, where Soli Tek R&D is collaborating together with the partners from ISC-Konstanz institute. Secondly, it was shown how the modification of solar module design can reduce the CO2 footprint for this product and enhance waste prevention. It was achieved by implementing a frameless glass/glass solar module design instead of glass/backsheet with aluminium frame. Such a design change is possible without purchasing new equipment and without loss of main product properties like efficiency, rigidity and longevity. Thirdly, industrial symbiosis in the solar cell production is possible in such case when manufacturing waste (silicon wafer and solar cell breakage) are collected, sorted and supplied as raw-materials to other companies involved in the production chain of c-Si solar cells. The obtained results showed that solar cells produced from recycled silicon can have a comparable electrical parameters like produced from standard, commercial silicon wafers. The above mentioned work was performed at solar cell producer Soli Tek R&D in the frame of H2020 projects CABRISS and Eco-Solar.

Keywords: solar cells and solar modules, manufacturing, waste prevention, recycling

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Authors: Bahaa Eltahawy, Mikko Ylihärsilä, Reino Virrankoski, Esko Petäjä

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Sheet metal processing is automated, but the step from product models to the production machine control still requires human intervention. This may cause time consuming bottlenecks in the production process and increase the risk of human errors. In this paper we present a system, which automatically recognizes features from the CAD-model of the sheet metal product. By using these features, the system produces a complete model of the particular sheet metal product. Then the model is used as an input for the sheet metal processing machine. Currently the system is implemented, capable to recognize more than 11 of the most common sheet metal structural features, and the procedure is fully automated. This provides remarkable savings in the production time, and protects against the human errors. This paper presents the developed system architecture, applied algorithms and system software implementation and testing.

Keywords: feature recognition, automation, sheet metal manufacturing, CAD, CAM

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Authors: R. Sanchez-Salcedo, N. H. Voelcker

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Currently, low breast milk production in women is one of the leading health complications in infants. Recently, It has been demonstrated that exclusive breastfeeding, especially up to a minimum of 6 months, significantly reduces respiratory and gastrointestinal infections, which are the main causes of death in infants. However, the current data shows that a high percentage of women stop breastfeeding their children because they perceive an inadequate supply of milk, and only 45% of children are breastfeeding under 6 months. It is, therefore, clear the necessity to design and develop a biosensor that is sensitive and selective enough to identify and validate a panel of milk biomarkers that allow the early diagnosis of this condition. In this context, electrochemical biosensors could be a powerful tool for assessing all the requirements in terms of reliability, selectivity, sensitivity, cost efficiency and potential for multiplex detection. Moreover, they are suitable for the development of POC devices and wearable sensors. In this work, we report the development of two types of sensing platforms towards several biomarkers, including miRNAs and hormones present in breast milk and dysregulated in this pathological condition. The first type of sensing platform consists of an enzymatic sensor for the detection of lactose, one of the main components in milk. In this design, we used gold surface as an electrochemical transducer due to the several advantages, such as the variety of strategies available for its rapid and efficient functionalization with bioreceptors or capture molecules. For the second type of sensing platform, nanoporous silicon film (pSi) was chosen as the electrode material for the design of DNA sensors and aptasensors targeting miRNAs and hormones, respectively. pSi matrix offers a large superficial area with an abundance of active sites for the immobilization of bioreceptors and tunable characteristics, which increase the selectivity and specificity, making it an ideal alternative material. The analytical performance of the designed biosensors was not only characterized in buffer but also validated in minimally treated breastmilk samples. We have demonstrated the potential of an electrochemical transducer on pSi and gold surface for monitoring clinically relevant biomarkers associated with the heightened risk of low milk production in women. This approach, in which the nanofabrication techniques and the functionalization methods were optimized to increase the efficacy of the biosensor highly provided a foundation for further research and development of targeted diagnosis strategies.

Keywords: biosensors, electrochemistry, early diagnosis, clinical markers, miRNAs

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Authors: Ida Bruheim Jensen, Hulda Mjöll Gunnarsdottir, Ingunn T. Ellingsen

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Digital government is often seen as an enabler or even driver of transformation of public administration, with the objective of creating public value. The increasing use of digital solutions in public services comes with great expectations of new and/or more efficient service provision. Digitalizing public sector services involve multi-level implementation. It involves national policy negotiations and decisions of digital government solutions. It involves co-creation/-production of ideas where planning, design, and implementation involves several groups of actors targeting end-users. Norway is among the most digitalised countries in the world, and Government spendings on digital technologies in public services are high compared to other OECD countries. This contribution studies an ongoing digital transformation in the Norwegian child welfare services. DigiBarnevern (Digi child welfare) is a nationwide project promising better and more efficient child welfare services through various digital technologies. The digitalization process, which is managed by the state and municipalities, is still in its early stages, and as of 2022, only a few services are operative. Digital technologies such as DigiBarnevern are implemented with promises of qualitatively improving child protection work, making the services more effective, foster user participation, and increase availability. There is limited research on the implications of using digital technologies in child protection work. We aim to present findings from an ongoing research project (2022-2024). Drawing on data from focus group interviews with social workers in 5 municipal child welfare services in Norway, we explore social workers’ experiences and expectations towards using digital technologies in child welfare services. Technological solutions may change the services and child protection work in numerous ways. Potential points of departure for discussion are how technologies may change the relationships between social workers, children, youth, and their families, how technologies can alter and obscure responsibilities, and how technologies may demand digital competence among social workers and service recipients.

Keywords: child welfare, social work, technology, digitalisation

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Authors: Elisaveta Doncheva, Jelena Djokikj, Ognen Tuteski, Bojana Hadjieva

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In the past decade, additive manufacturing technology or 3D printing has been promoted as an efficient method for fabricating hybrid composite materials and structures with superior mechanical properties and complex shape and geometry. Fused deposition modeling (FDM) process is commonly used additive manufacturing technique for production of polymer products. Therefore, many studies and experiments are focused on investigating the possibilities for improving the obtained results on product properties as a key factor for expanding the spectrum of their application. This article provides an extensive review on recent research advances in FDM and reports on studies that cover the effects of process parameters, material, and design of the product properties. The paper conclusions provide a clear up-to date information for optimum efficiency and enhancement of the mechanical properties of 3D printed samples and recommends further research work and investigations.

Keywords: additive manufacturing, critical parameters, filament, print orientation, 3D printing

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Authors: Farzaneh Tahmoorian, Bijan Samali, John Yeaman

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Road networks are expanding all over the world during the past few decades to meet the increasing freight volumes created by the population growth and industrial development. At the same time, the rate of generation of solid wastes in the society is increasing with the population growth, technological development, and changes in the lifestyle of people. Thus, the management of solid wastes has become an acute problem. Accordingly, there is a need for greater efficiency in the construction and maintenance of road networks, in reducing the overall cost, especially the utilization of natural materials such as aggregates. An efficient means to reduce construction and maintenance costs of road networks is to replace natural (virgin) materials by secondary, recycled materials. Recycling will also help to reduce pressure on landfills and demand for extraction of natural virgin materials thus ensuring sustainability. Application of solid wastes in asphalt layer reduces not only environmental issues associated with waste disposal but also the demand for virgin materials which will subsequently result in sustainability. Therefore, this research aims to investigate the feasibility of the application of some of the waste materials such as glass, construction and demolition wastes, etc. as alternative materials in pavement construction, particularly flexible pavements. To this end, various combination of different waste materials in certain percentages is considered in designing the asphalt mixture. One of the goals of this research is to determine the optimum percentage of all these materials in the mixture. This is done through a series of tests to evaluate the volumetric properties and resilient modulus of the mixture. The information and data collected from these tests are used to select the adequate samples for further assessment through advanced tests such as triaxial dynamic test and fatigue test, in order to investigate the asphalt mixture resistance to permanent deformation and also cracking. This paper presents the results of these investigations on the application of waste materials in asphalt mixture for production of a sustainable asphalt mix.

Keywords: asphalt, glass, pavement, recycled aggregate, sustainability

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Authors: Kai Warsoenke, Maik Mackiewicz

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To achieve a high quality of assembled car body structures, tolerancing is used to ensure a geometric accuracy of the single car body parts. There are two main techniques to determine the required tolerances. The first is tolerance analysis which describes the influence of individually tolerated input values on a required target value. Second is tolerance synthesis to determine the location of individual tolerances to achieve a target value. Both techniques are based on classical statistical methods, which assume certain probability distributions. To ensure competitiveness in both saturated and dynamic markets, production processes in vehicle manufacturing must be flexible and efficient. The dimensional specifications selected for the individual body components and the resulting assemblies have a major influence of the quality of the process. For example, in the manufacturing of forming tools as operating equipment or in the higher level of car body assembly. As part of the metrological process monitoring, manufactured individual parts and assemblies are recorded and the measurement results are stored in databases. They serve as information for the temporary adjustment of the production processes and are interpreted by experts in order to derive suitable adjustments measures. In the production of forming tools, this means that time-consuming and costly changes of the tool surface have to be made, while in the body shop, uncertainties that are difficult to control result in cost-intensive rework. The stored measurement results are not used to intelligently design tolerances in future processes or to support temporary decisions based on real-world geometric data. They offer potential to extend the tolerancing methods through data analysis and machine learning models. The purpose of this paper is to examine real-world measurement data from individual car body components, as well as assemblies, in order to develop an approach for using the data in short-term actions and future projects. For this reason, the measurement data will be analyzed descriptively in the first step in order to characterize their behavior and to determine possible correlations. In the following, a database is created that is suitable for developing machine learning models. The objective is to create an intelligent way to determine the position and number of measurement points as well as the local tolerance range. For this a number of different model types are compared and evaluated. The models with the best result are used to optimize equally distributed measuring points on unknown car body part geometries and to assign tolerance ranges to them. The current results of this investigation are still in progress. However, there are areas of the car body parts which behave more sensitively compared to the overall part and indicate that intelligent tolerancing is useful here in order to design and control preceding and succeeding processes more efficiently.

Keywords: automotive production, machine learning, process optimization, smart tolerancing

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Authors: Huan Ting Liao

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In a typical manufacturing environment, computer numerical control (CNC) machining is essential for automating production through precise computer-controlled tool operations, significantly enhancing efficiency and ensuring consistent product quality. However, traditional CNC production lines often rely on manual loading and unloading, limiting operational efficiency and scalability. Although automated loading systems have been developed, they frequently lack sufficient intelligence and configuration efficiency, requiring extensive setup adjustments for different products and impacting overall productivity. This research addresses the job shop scheduling problem (JSSP) in CNC machining environments, aiming to minimize total completion time (makespan) and maximize CNC machine utilization. We propose a novel approach using reinforcement learning (RL), specifically the Q-learning algorithm, to optimize scheduling decisions. The study simulates the JSSP, incorporating robotic arm operations, machine processing times, and work order demand allocation to determine optimal processing sequences. The Q-learning algorithm enhances machine utilization by dynamically balancing workloads across CNC machines, adapting to varying job demands and machine states. This approach offers robust solutions for complex manufacturing environments by automating decision-making processes for job assignments. Additionally, we evaluate various layout configurations to identify the most efficient setup. By integrating RL-based scheduling optimization with layout analysis, this research aims to provide a comprehensive solution for improving manufacturing efficiency and productivity in CNC-based job shops. The proposed method's adaptability and automation potential promise significant advancements in tackling dynamic manufacturing challenges.

Keywords: job shop scheduling problem, reinforcement learning, operations sequence, layout optimization, q-learning

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Authors: M. Nikafrooz, J. Darsareh

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Due to the COVID-19 pandemic, its impacts on education all over the world and the problems arising from the use of traditional methods in education, it was necessary to apply alternative solutions to achieve educational goals. In this regard, electronic content production through screen recording and giving educational services in virtual classes became popular among many teachers. But the production of screen recorded videos involves special technical and educational considerations so that educators could be able to produce valuable and well-made videos by taking those considerations into account. The purpose of this study was to extract and find the technical and educational considerations of producing screen recorded videos to provide a useful and comprehensive guideline for e-content producers to enable them to produce high-quality educational videos. This study is fundamental research and data collection has been done using the Delphi method. In this research, an attempt has been made to provide the necessary criteria and considerations regarding the design and production of screen recorded videos by studying the literatures, identifying and analyzing learners' and teachers' needs and expectations, reviewing the previously produced videos. The results of these studies led to the finding and extracting 129 indicators in the form of 6 criteria. Such considerations are expected to reduce production and editing time, increase the technical and educational quality, and finally facilitating and enhancing the processes of teaching and learning.

Keywords: e-content, screen recorded videos, screen recording software, technical and pedagogical considerations

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Authors: Laura Piedra-Munoz, Angeles Godoy-Duran, Emilio Galdeano-Gomez, Juan C. Perez-Mesa

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Spain is very sensitive to water management issues due to its climatic characteristics and the deficit of this resource in many areas of its territory. This study examines the characteristics of the family farms that are more efficient in the use of water, focusing on a semi-arid area located in Almeria, southeast of Spain. In the case of irrigated agriculture, water usage efficiency usually indicates water productivity in terms of yield (kg/m³), or in economic terms (euros/m³). These two water usage indicators were considered to analyse water usage efficiency according to other studies on water efficiency in the horticultural area under analysis. This work also takes into account other water usage characteristics such as water supplied, innovative irrigation practices, water-efficient technology, and water-saving practices. The results show that the most water efficient farms have technical advisors and use irrigation on demand, that measures the water needs of the crops and are considered the most technological irrigation system. These farms are more technological and less labor intensive. They are also aware of water scarcity and the need to conserve the environment. This approach allow managers to identify the principal factors and best practices related to water efficiency in order to promote and implement them in inefficient farms and promote sustainability.

Keywords: cluster analysis, family farms, Spain, sustainability, water-use efficiency

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Authors: Hamida Qumber Ali, Waseem Muhammad Arain, Shama Siddiqui, Sayeed Ghani

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We present an implementing of RMAC in TinyOS 1.x. RMAC is a cross layer and Duty-cycle MAC protocols that was proposed to provide energy efficient transmission services for wireless sensor networks. The protocol has a unique and efficient packet transmission scheduling mechanism that enables it to overcome delivery latency and overcome traffic congestion. Design details and implementation challenges are divulged. Experiments are conducted to show the correctness of our implementation with numerous assumptions. Simulations are performed to compare the performance of RMAC and SMAC. Our results show that RMAC outperforms SMAC in energy efficiency and delay.

Keywords: MAC protocol, performance, RMAC, wireless sensor networks

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Authors: Lars Rödel, Jonas Krebs, Gregor Müller

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The growing price pressure due to the increasing number of global suppliers, the growing individualization of products and ever-shorter delivery times are upcoming challenges in the industry. In this context, Mass Personalization stands for the individualized production of customer products in batch size 1 at the price of standardized products. The possibilities of digitalization and automation of technical order processing open up the opportunity for companies to significantly reduce their cost of complexity and lead times and thus enhance their competitiveness. Many companies already use a range of CAx tools and configuration solutions today. Often, the expert knowledge of employees is hidden in "knowledge silos" and is rarely networked across processes. DesignChain describes the automated digital process from the recording of individual customer requirements, through design and technical preparation, to production. Configurators offer the possibility of mapping variant-rich products within the Design Chain. This transformation of customer requirements into product features makes it possible to generate even complex CAD models, such as those for large-scale plants, on a rule-based basis. With the aid of an automated CAx chain, production-relevant documents are thus transferred digitally to production. This process, which can be fully automated, allows variants to always be generated on the basis of current version statuses.

Keywords: automation, design, CAD, CAx

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Authors: Francisco Vidal Vázquez, Pekka Simell, Christian Frilund, Matti Reinikainen, Ilkka Hiltunen, Tim Böltken, Benjamin Andris, Paolo Piermartini

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Carbon capture and utilization (CCU) are one of the key topics in mitigation of CO2 emissions. There are many different technologies that are applied for the production of diverse chemicals from CO2 such as synthetic natural gas, Fischer-Tropsch products, methanol and polymers. Power-to-Gas and Power-to-Liquids concepts arise as a synergetic solution for storing energy and producing value added products from the intermittent renewable energy sources and CCU. VTT is a research and technology development company having energy in transition as one of the key focus areas. VTT has extensive experience in piloting and upscaling of new energy and chemical processes. Recently, VTT has developed and commissioned a Mobile Synthesis Unit (MOBSU) in close collaboration with INERATEC, a spin-off company of Karlsruhe Institute of Technology (KIT, Germany). The MOBSU is a multipurpose synthesis unit for CO2 upgrading to energy carriers and chemicals, which can be transported on-site where CO2 emission and renewable energy are available. The MOBSU is initially used for production of fuel compounds and chemical intermediates by combination of two consecutive processes: reverse Water-Gas Shift (rWGS) and Fischer-Tropsch synthesis (FT). First, CO2 is converted to CO by high-pressure rWGS and then, the CO and H2 rich effluent is used as feed for FT using an intensified reactor technology developed and designed by INERATEC. Chemical equilibrium of rWGS reaction is not affected by pressure. Nevertheless, compression would be required in between rWGS and FT in the case when rWGS is operated at atmospheric pressure. This would also require cooling of rWGS effluent, water removal and reheating. For that reason, rWGS is operated using precious metal catalyst in the MOBSU at similar pressure as FT to simplify the process. However, operating rWGS at high pressures has also some disadvantages such as methane and carbon formation, and more demanding specifications for materials. The main parts of FT module are an intensified reactor, a hot trap to condense the FT wax products, and a cold trap to condense the FT liquid products. The FT synthesis is performed using cobalt catalyst in a novel compact reactor technology with integrated highly-efficient water evaporation cooling cycle. The MOBSU started operation in November 2016. First, the FT module is tested using as feedstock H2 and CO. Subsequently, rWGS and FT modules are operated together using CO2 and H2 as feedstock of ca. 5 Nm3/hr total flowrate. On spring 2017, The MOBSU unit will be integrated together with a direct air capture (DAC) of CO2 unit, and a PEM electrolyser unit at Lappeenranta University of Technology (LUT) premises for demonstration of the SoletAir concept. This would be the first time when synthetic fuels are produced by combination of DAC unit and electrolyser unit which uses solar power for H2 production.

Keywords: CO2 utilization, demonstration, Fischer-Tropsch synthesis, intensified reactors, reverse water-gas shift

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Authors: Bayan Alqasem, Israa Othman, Mohammad Abu Haija, Fawzi Banat

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The large-scale production of wastewater containing highly toxic pollutants made it necessary to find efficient water treatment technologies. Phenolic compounds, which are known to be persistent and hazardous, are highly presented in wastewater. In this study, different ferrite catalysts CrFe₂O₄, CuFe₂O₄, MgFe₂O₄, MnFe₂O₄, NiFe₂O₄, and ZnFe₂O₄ were employed to study the catalytic degradation of phenol aqueous solutions. The catalysts were prepared via sol-gel and co-precipitation methods. All of the prepared catalysts were characterized using infrared spectroscopy (IR), X-ray diffraction (XRD), and scanning electron microscopy (SEM). The ferrites catalytic activities were tested towards phenol degradation using high-performance liquid chromatography (HPLC). The photocatalytic properties of the ferrites were also investigated. The experimental results suggested that CuFe₂O₄ is an effective catalyst for the removal of phenol from wastewater. Additionally, different CuFe₂O₄composites were also prepared either by varying the metal ratios or incorporating chemically reduced graphene oxide in the ferrite cluster.

Keywords: phenol degradation, ferrite catalysts, ferrite composites, photocatalysis

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Authors: Ruedee Niyomrath, Somboon Sarasit, Chaisri Tharaswatpipat

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This research aims to study the potential of local waste material in quantity and quality. The potential for such local forms of waste material used as renewable energy for the production of processed agricultural products. The results of this study are useful to producers of agricultural products to use fuel that in local, reduce production costs, and conservation. The results showed that Samut Songkhram is a small province located in the central Thailand, sea area, and subdivided into 3 districts. This province has a population of 80 percent of farmers and agriculture with 50 percent of the area planted to coconut growing. Productivity of coconut help create value for the primacy of the province. Waste materials from coconut have quantity and quality potentials for processing biomass into charcoal as the renewable energy for the production of processed agricultural products.

Keywords: waste, renewable energy, producing of product, processed agricultural products

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Authors: Hwang Ho Kim, Do Gyun Kim, Jin Young Choi, Sang Chul Park

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Since tire production process is very complicated, company-wide management of it is very difficult, necessitating considerable amounts of capital and labors. Thus, productivity should be enhanced and maintained competitive by developing and applying effective production plans. Among major processes for tire manufacturing, consisting of mixing component preparation, building and curing, the mixing process is an essential and important step because the main component of tire, called compound, is formed at this step. Compound as a rubber synthesis with various characteristics plays its own role required for a tire as a finished product. Meanwhile, scheduling tire mixing process is similar to flexible job shop scheduling problem (FJSSP) because various kinds of compounds have their unique orders of operations, and a set of alternative machines can be used to process each operation. In addition, setup time required for different operations may differ due to alteration of additives. In other words, each operation of mixing processes requires different setup time depending on the previous one, and this kind of feature, called sequence dependent setup time (SDST), is a very important issue in traditional scheduling problems such as flexible job shop scheduling problems. However, despite of its importance, there exist few research works dealing with the tire mixing process. Thus, in this paper, we consider the scheduling problem for tire mixing process and suggest an efficient particle swarm optimization (PSO) algorithm to minimize the makespan for completing all the required jobs belonging to the process. Specifically, we design a particle encoding scheme for the considered scheduling problem, including a processing sequence for compounds and machine allocation information for each job operation, and a method for generating a tire mixing schedule from a given particle. At each iteration, the coordination and velocity of particles are updated, and the current solution is compared with new solution. This procedure is repeated until a stopping condition is satisfied. The performance of the proposed algorithm is validated through a numerical experiment by using some small-sized problem instances expressing the tire mixing process. Furthermore, we compare the solution of the proposed algorithm with it obtained by solving a mixed integer linear programming (MILP) model developed in previous research work. As for performance measure, we define an error rate which can evaluate the difference between two solutions. As a result, we show that PSO algorithm proposed in this paper outperforms MILP model with respect to the effectiveness and efficiency. As the direction for future work, we plan to consider scheduling problems in other processes such as building, curing. We can also extend our current work by considering other performance measures such as weighted makespan or processing times affected by aging or learning effects.

Keywords: compound, error rate, flexible job shop scheduling problem, makespan, particle encoding scheme, particle swarm optimization, sequence dependent setup time, tire mixing process

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Authors: Sifat Rahman Ahona, Rifat Tasnim, Naima Hassan

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Data aggregation is a helpful technique for reducing the data communication overhead in wireless sensor network. One of the important tasks of data aggregation is positioning of the aggregator points. There are a lot of works done on data aggregation. But, efficient positioning of the aggregators points is not focused so much. In this paper, authors are focusing on the positioning or the placement of the aggregation points in wireless sensor network. Authors proposed an algorithm to select the aggregators positions for a scenario where aggregator nodes are more powerful than sensor nodes.

Keywords: aggregation point, data communication, data aggregation, wireless sensor network

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Authors: Turan Çalban, Fatih Sevim, Oral Laçin

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In this study, the precipitation conditions of Chevreul’s salt were evaluated. The structure of Chevreul’s salt was examined by considering the previous studies. Thermodynamically, the most important precipitation parameters were pH, temperature, and sulphite-copper(II) ratio. The amount of Chevreul’s salt increased with increasing the temperature and sulphite-copper(II) ratio at the certain range, while it increased with decreasing the pH value at the chosen range. The best solution medium for recovery of Chevreul’s salt is sulphur dioxide gas-water system. Moreover, the soluble sulphite salts are used as efficient precipitating reagents. Chevreul’s salt is generally used to produce the highly pure copper powders from synthetic copper sulphate solutions and impure leach solutions. When the pH of the initial ammoniacal solution is greater than 8.5, ammonia in the medium is not free, and Chevreul’s salt from solution does not precipitate. In contrast, copper ammonium sulphide is precipitated. The pH of the initial solution containing ammonia for precipitating of Chevreul’s salt must be less than 8.5.

Keywords: Chevreul's salt, production, copper sulfites, copper compound

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Authors: Vojtech Stejskal, Hana Skalova, Petr Kvapil, George Hutchinson

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Algae growth has been an important issue in water management of water plants, ponds and lakes, swimming pools, aquaculture & fish farms, gardens or golf courses for last decades. There are solutions based on chemical or biological principles. Apart of these traditional principles for inhibition of algae growth and biofilm production there are also physical methods which are very competitive compared to the traditional ones. Ultrasonic technology is one of these alternatives. Ultrasonic emitter is able to eliminate the biofilm which behaves as a host and attachment point for algae and is original reason for the algae growth. The ultrasound waves prevent majority of the bacteria in planktonic form becoming strongly attached sessile bacteria that creates welcoming layer for the biofilm production. Biofilm creation is very fast – in the serene water it takes between 30 minutes to 4 hours, depending on temperature and other parameters. Ultrasound device is not killing bacteria. Ultrasound waves are passing through bacteria, which retract as if they were in very turbulent water even though the water is visually completely serene. In these conditions, bacteria does not excrete the polysaccharide glue they use to attach to the surface of the pool or pond, where ultrasonic technology is used. Ultrasonic waves decrease the production of biofilm on the surfaces in the selected area. In case there are already at the start of the application of ultrasonic technology in a pond or basin clean inner surfaces, the biofilm production is almost absolutely inhibited. This paper talks about two different pilot applications – one in Czech Republic and second in United States of America, where the used ultrasonic technology (AlgaeControl) is coming from. On both sites, there was used Mezzo Ultrasonic Algae Control System with very positive results not only on biofilm production, but also algae growth in the surrounding area. Technology has been successfully tested in two different environments. The poster describes the differences and their influence on the efficiency of ultrasonic technology application. Conclusions and lessons learned can be possibly applied also on other sites within Europe or even further.

Keywords: algae growth, biofilm production, ultrasonic solution, ultrasound

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Authors: Evgeny E. Tereshatov

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Astatine-211 is considered one of the most promising radionuclides for Targeted Alpha Therapy. In order to develop reliable procedures to label biomolecules and utilize efficient delivery vehicle principles, one should understand the main chemical characteristics of astatine. The short half-life of 211At (~7.2 h) and absence of any stable isotopes of this element are limiting factors towards studying the behavior of astatine. Our team has developed a procedure for rapid and efficient isolation of astatine from irradiated bismuth material in nitric acid media based on 3-octanone and 1-octanol extraction chromatography resins. This process has been automated and it takes 20 min from the beginning of the target dissolution to the At-211 fraction elution. Our next step is to consider commercially available chromatography resins and their applicability in astatine purification in the same media. Results obtained along with the corresponding sorption mechanisms will be discussed.

Keywords: astatine-211, chromatography, automation, mechanism, radiopharmaceuticals

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Authors: Wieland Hoppe, Nadine Wachter, Stefan Bringezu

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Carbon dioxide (CO2) utilization might be a promising way to substitute fossil raw materials like coal, oil or natural gas as carbon source of chemical production. While first life cycle assessments indicate a positive environmental performance of CO2-based process routes, a commercialization of CO2 is limited by several economic obstacles up to now. We, therefore, analyzed the economic performance of the three CO2-based chemicals methane and methanol as basic chemicals and polyoxymethylene as polymer on a cradle-to-gate basis. Our approach is oriented towards life cycle costing. The focus lies on the cost drivers of CO2-based technologies and options to stimulate a CO2-based economy by changing regulative factors. In this way, we analyze various modes of operation and give an outlook for the potentially cost-effective development in the next decades. Biogas, waste gases of a cement plant, and flue gases of a waste incineration plant are considered as CO2-sources. The energy needed to convert CO2 into hydrocarbons via electrolysis is assumed to be supplied by wind power, which is increasingly available in Germany. Economic data originates from both industrial processes and process simulations. The results indicate that CO2-based production technologies are not competitive with conventional production methods under present conditions. This is mainly due to high electricity generation costs and regulative factors like the German Renewable Energy Act (EEG). While the decrease in production costs of CO2-based chemicals might be limited in the next decades, a modification of relevant regulative factors could potentially promote an earlier commercialization.

Keywords: carbon capture and utilization (CCU), economic assessment, life cycle costing (LCC), power-to-X

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Authors: S. Jaikeaw, S. Chavadej

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The objective of this study was to determine the effects of COD loading rate on hydrogen and methane production and micronutrient transportation using a two-stage upflow anaerobic sludge blanket (UASB) system under mesophilic temperature (37°C) with a constant recycle ratio of 1:1 (final effluent flow rate: feed flow rate). The first (hydrogen) UASB unit having 4 L liquid holding volume was controlled at pH 5.5 but the second (methane) UASB unit having 24 L liquid holding volume had no pH control. The two-stage UASB system operated at different COD loading rates from 8 to 20 kg/m³d based on total UASB working volume. The results showed that, at the optimum COD loading rate of 13 kg/m³d, the produced gas from the hydrogen UASB unit contained 1.5% H₂, 16.5% CH₄, and 82% CO₂ with H₂S of 252 ppm and also provided a hydrogen yield of 1.66 mL/g COD removed (or 0.56 mL/g COD applied) and a specific hydrogen production rate of 156.85 ml H₂/LRd (or 5.12 ml H₂/g MLVSS d). Under the optimum COD loading rate, the produced gas from the methane UASB unit mainly contained methane and carbon dioxide without hydrogen of 74 and 26%, respectively with hydrogen sulfide of 287 ppm and the system also provided a maximum methane yield of 407.00 mL/g COD removed (or 263.23 mL/g COD applied) and a specific methane production rate of 2081.44 ml CH₄/LRd (or 99.75 ml CH₄/g MLVSS d). Under the optimum COD loading rate, all micronutrients markedly dropped by the sulfide precipitation reactions. The reduction of micronutrients mostly appeared in the methane UASB unit. Under the studied conditions, both Co and Ni were found to be greatly precipitated out, causing the deficiency to microbial activity. It is hypothesized that an addition of both Co and Ni can improve the methanogenic activity.

Keywords: hydrogen and methane production, ethanol wastewater, a two-stage upflow anaerobic blanket (UASB) system, mesophillic temperature, microbial concentration (MLVSS), micronutrients

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Authors: Ifeanyichukwu Edeh, Tim Overton, Steve Bowra

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Currently biodiesel is produced from plant oils or animal’s fats by a liquid-phase catalysed transesterification process at low temperature. Although biodiesel is renewable and to a large extent sustainable, inherent properties such as poor cold flow, low oxidation stability, low cetane value restrict application to blends with fossil fuels. An alternative to biodiesel is renewable diesel produced by catalytic hydrotreating of oils and fats and is considered a drop in fuel because its properties are similar to petroleum diesel. In addition to developing alternative productions routes there is continued interest in reducing the cost of the feed stock, waste cooking oils and fats are increasingly used as the feedstocks due to low cost. However, use of oils and fat are highly adulterated resulting in high free fatty acid content which turn impacts on the efficiency of FAME production. Therefore, in light of the need to develop, alternative lipid feed stocks and related efficient catalysis the present study investigates the potential of producing renewable diesel from the lipids-extracted from activated sludge, a waste water treatment by-product, through catalytic hydrothermal decarboxylation. The microbial lipids were first extracted from the activated sludge using the Folch et al method before hydrothermal decarboxylation reactions were carried out using palladium (Pd/C) and platinum (Pt/C) on activated carbon as the catalysts in a batch reactor. The impact of three temperatures 290, 300, 330 °C and residence time between 30 min and 4hrs was assessed. At the end of the reaction, the products were recovered using organic solvents and characterized using gas chromatography (GC). The principle products of the reaction were pentadecane and heptadecane. The highest yields of pentadecane and heptadecane from lipid-extract were 23.23% and 15.21%, respectively. These yields were obtained at 290 °C and residence time 1h using Pt/C. To the best of our knowledge, the current work is the first investigation on the hydrothermal decarboxylation of lipid-extract from activated sludge.

Keywords: activated sludge, lipid, hydrothermal decarboxylation, renewable diesel

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Authors: Malte Brettel, Niklas Friederichsen, Michael Keller, Marius Rosenberg

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The German manufacturing industry has to withstand an increasing global competition on product quality and production costs. As labor costs are high, several industries have suffered severely under the relocation of production facilities towards aspiring countries, which have managed to close the productivity and quality gap substantially. Established manufacturing companies have recognized that customers are not willing to pay large price premiums for incremental quality improvements. As a consequence, many companies from the German manufacturing industry adjust their production focusing on customized products and fast time to market. Leveraging the advantages of novel production strategies such as Agile Manufacturing and Mass Customization, manufacturing companies transform into integrated networks, in which companies unite their core competencies. Hereby, virtualization of the process- and supply-chain ensures smooth inter-company operations providing real-time access to relevant product and production information for all participating entities. Boundaries of companies deteriorate, as autonomous systems exchange data, gained by embedded systems throughout the entire value chain. By including Cyber-Physical-Systems, advanced communication between machines is tantamount to their dialogue with humans. The increasing utilization of information and communication technology allows digital engineering of products and production processes alike. Modular simulation and modeling techniques allow decentralized units to flexibly alter products and thereby enable rapid product innovation. The present article describes the developments of Industry 4.0 within the literature and reviews the associated research streams. Hereby, we analyze eight scientific journals with regards to the following research fields: Individualized production, end-to-end engineering in a virtual process chain and production networks. We employ cluster analysis to assign sub-topics into the respective research field. To assess the practical implications, we conducted face-to-face interviews with managers from the industry as well as from the consulting business using a structured interview guideline. The results reveal reasons for the adaption and refusal of Industry 4.0 practices from a managerial point of view. Our findings contribute to the upcoming research stream of Industry 4.0 and support decision-makers to assess their need for transformation towards Industry 4.0 practices.

Keywords: Industry 4.0., mass customization, production networks, virtual process-chain

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Authors: Adriano Araujo Carvalho, Arturo Alatrista Corrales

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This paper intends to show how electrical energy consumption and production data analysis were used to find opportunities to save energy at Taboada wastewater treatment plant in Callao, Peru. In order to access the data, it was used independent data networks for both electrical and process instruments, which were taken to analyze under an ISO 50001 energy audit, which considered, thus, Energy Performance Indexes for each process and a step-by-step guide presented in this text. Due to the use of aforementioned methodology and data mining techniques applied on information gathered through electronic multimeters (conveniently placed on substation switchboards connected to a cloud network), it was possible to identify thoroughly the performance of each process and thus, evidence saving opportunities which were previously hidden before. The data analysis brought both costs and energy reduction, allowing the plant to save significant resources and to be certified under ISO 50001.

Keywords: energy and production data analysis, energy management, ISO 50001, wastewater treatment plant energy analysis

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Authors: Sajjad Ur Rahman, Muhammad Tahir, Mukarram Bashir, Jawad, Aoun Muhammad, Muhammad Zohaib, Hannan Khan, Seemal Javaid, Mariam Azam

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The efficiency of natural metabolites obtained from partially fermented soya hulls and wheat bran using Saccharomyces cerevisiae (DL-22 S/N) ensures a potential impact on the total milk yield and quality of milk production. On attaining a moderate number of Saccharomyces cerevisiae cells around 1×10⁹ CFU/ml, the concentrate was further elevated under in-vivo conditions to study the quality of milk production in lactating buffalo. Ten lactating buffalos of the Nili Ravi breed having the same physical factors were given 12 gm of microbial metabolites daily, along with the palleted feed having 22 % proteins. Another group of 10 lactating animals with the same characteristics was maintained without metabolites. The body score, overall health, incidence of mastitis, milk fat, milk proteins, ash and solid not fat (SNF) were elevated on a weekly basis up to thirty days of trial. It was recorded that the average total increase in quality milk production was 0.9 liter/h/d, whereas SNF in the milk was enhanced to 0.71, and fats were decreased to 0.09 %. Moreover, during all periods of the trial, the overall non-specific immunity of buffalo was increased, as indicated by less than 0.2 % of mastitis incidence compared to 1.8% in the untreated buffalos.

Keywords: natural metabolites, quality milk, milk yield, microorganisms, fermentation, nonspecific immunity, better performing animals

Procedia PDF Downloads 88