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Journal articles on the topic 'Manufacturing processes Energy consumption Data processing'

Author: Grafiati

Published: 10 December 2022

Last updated: 19 July 2025

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1

Zhang, Chaoyang, Juchen Zhang, Weixi Ji, and Wei Peng. "Data Acquisition Network Configuration and Real-Time Energy Consumption Characteristic Analysis in Intelligent Workshops for Social Manufacturing." Machines 10, no. 10 (2022): 923. http://dx.doi.org/10.3390/machines10100923.

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To achieve energy-saving production, one critical step is to calculate and analyze the energy consumption and energy efficiency of machining processes. However, considering the complexity and uncertainty of discrete manufacturing job shops, it is a significant challenge to conduct data acquisition and energy consumption data processing of manufacturing systems. Meanwhile, under the growing trend of personalization, social manufacturing is an emerging technical practice that allows prosumers to build individualized services with their partners, which produces new requirements for energy data pr

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Jones, Lewis C. R., Nicholas Goffin, Jinglei Ouyang, et al. "Laser specific energy consumption: How do laser systems compare to other manufacturing processes?" Journal of Laser Applications 34, no. 4 (2022): 042029. http://dx.doi.org/10.2351/7.0000790.

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Laser material interactions are routinely praised for their selective processing and high processing rates. However, this does not guarantee that the total manufacturing system has a low energy intensity compared to conventional manufacturing processes. This paper presents the results of a collaborative UK and China research project to improve the comprehension of the total energy consumption and carbon emissions for laser-based manufacturing. A range of individual laser cutting, welding, and cleaning processes were studied to assess their energy efficiency, including the laser and its ancilla

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VYAKINA, Irina V., and Anton V. SKRYNNIK. "Developing the fuel and energy complex and energy security of the Russian Federation in the context of reindustrialization." Economic Analysis: Theory and Practice 22, no. 10 (2023): 1805–30. http://dx.doi.org/10.24891/ea.22.10.1805.

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Subject. The article considers the impact of fuel and energy complex on economic development and energy security of the Russian Federation. Objectives. The aim is to identify trends and specific features of Russia’s fuel and energy complex development in conditions of reindustrialization, and to work out practical recommendations for improving its energy security, focusing on elimination of imbalances in the development of extractive and manufacturing industries. Methods. We employed methods of systems analysis and analysis of statistical data. The general scientific method of induction was ap

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Adeniyi Kehinde Adeleke. "INTELLIGENT MONITORING SYSTEM FOR REAL-TIME OPTIMIZATION OF ULTRA-PRECISION MANUFACTURING PROCESSES." Engineering Science & Technology Journal 5, no. 3 (2024): 803–10. http://dx.doi.org/10.51594/estj.v5i3.904.

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In the realm of ultra-precision manufacturing, the minutiae of process control and material handling are paramount to achieving the highest levels of product quality and manufacturing efficiency. The industry faces a significant challenge: maintaining and enhancing the precision of manufacturing processes in real-time to ensure optimal output quality while minimizing waste and energy consumption. This challenge is compounded by the increasing complexity of products and the materials used, requiring ever more precise and adaptive manufacturing techniques. The importance of addressing this chall

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Iten, Muriel, Miguel Oliveira, Diogo Costa, and Jochen Michels. "Water and Energy Efficiency Improvement of Steel Wire Manufacturing by Circuit Modelling and Optimisation." Energies 12, no. 2 (2019): 223. http://dx.doi.org/10.3390/en12020223.

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Industrial water circuits (IWC) are frequently neglected as they are auxiliary circuits of industrial processes, leading to a missing awareness of their energy- and water-saving potential. Industrial sectors such as steel, chemicals, paper and food processing are notable in their water-related energy requirements. Improvement of energy efficiency in industrial processes saves resources and reduces manufacturing costs. The paper presents a cooling IWC of a steel wire processing plant in which steel billets are transformed into wire. The circuit was built in object-oriented language in OpenModel

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Taphasanoğlu, Saime, Muhammet Raşit Cesur, and Elif Cesur. "A Precise Energy Consumption Model for Computer Numerical Control Machines: A Hybrid Approach." Sustainability 16, no. 23 (2024): 10659. https://doi.org/10.3390/su162310659.

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In today’s world, energy efficiency is becoming increasingly crucial, due to its impact on sustainability in production. Designing systems that consume less energy and manage resources efficiently is essential. Variations in operating speed can affect processing time, energy consumption, idle times of subsequent machines, work delays, and missed deadlines. While most studies focus on prediction parameters like cut depth and cut area to estimate the energy consumption or processing time, our approach emphasizes variations in G-code motion parameters. To enhance both precision and the adaptabili

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Ingarao, Giuseppe, Paolo C. Priarone, Francesco Gagliardi, Rosa di Lorenzo, and Luca Settineri. "Environmental Comparison between a Hot Extrusion Process and Conventional Machining Processes through a Life Cycle Assessment Approach." Key Engineering Materials 622-623 (September 2014): 103–10. http://dx.doi.org/10.4028/www.scientific.net/kem.622-623.103.

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Nowadays manufacturing technologies have to be evaluated not only for the technical features they can provide to products, but also considering the environmental perspective as well. As long as the technological feasibility of a given process is guaranteed, processes minimizing resources and energy consumption have to be selected for manufacturing. With respect to this topic, the research studies in the domain of metal processing technologies predominantly focus on conventional material removal processes as milling and turning. Despite some exceptions, many other non-machining technologies, su

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Willenbacher, Martina, Jonas Scholten, and Volker Wohlgemuth. "Machine Learning for Optimization of Energy and Plastic Consumption in the Production of Thermoplastic Parts in SME." Sustainability 13, no. 12 (2021): 6800. http://dx.doi.org/10.3390/su13126800.

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In manufacturing companies, especially in SMEs, the optimization of processes in terms of resource consumption, waste minimization, and pollutant emissions is becoming increasingly important. Another important driver is digitalization and the associated increase in the volume of data. These data, from a multitude of devices and systems, offer enormous potential, which increases the need for intelligent, dynamic analysis models even in smaller companies. This article presents the results of an investigation into whether and to what extent machine learning processes can contribute to optimizing

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Indzere, Zane, Kevin D. Manzano Martinez, Tereza Bezrucko, Zauresh Khabdullina, Ivars Veidenbergs, and Dagnija Blumberga. "Energy Efficiency Improvement in Thawing." Environmental and Climate Technologies 24, no. 2 (2020): 221–30. http://dx.doi.org/10.2478/rtuect-2020-0068.

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AbstractThe thawing process within fish processing is one of the most essential steps in manufacturing. Various processes of thawing can be used where efficiency varies between companies depending on such characteristics as energy consumption, the price of resources, etc. The main aim of the research is to increase the efficiency of thawing processes. Firstly, to analyse various thawing methods and to find the most efficient one by using multi-criteria decision making analysis method. Secondly, analysing data of thawing of existing company to find opportunities for improvements, including the

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Moon, Yeeun, Younjeong Lee, Yejin Hwang, and Jongpil Jeong. "Long Short-Term Memory Autoencoder and Extreme Gradient Boosting-Based Factory Energy Management Framework for Power Consumption Forecasting." Energies 17, no. 15 (2024): 3666. http://dx.doi.org/10.3390/en17153666.

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Electricity consumption prediction is crucial for the operation, strategic planning, and maintenance of power grid infrastructure. The effective management of power systems depends on accurately predicting electricity usage patterns and intensity. This study aims to enhance the operational efficiency of power systems and minimize environmental impact by predicting mid to long-term electricity consumption in industrial facilities, particularly in forging processes, and detecting anomalies in energy consumption. We propose an ensemble model combining Extreme Gradient Boosting (XGBoost) and a Lon

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Zurnacı, Erman, Sabri Uzuner, and Engin Nas. "Comparison of Automation-Supported and Conventional Methods for Measuring Energy Consumption in Computer Numerical Control Machining." Machines 13, no. 2 (2025): 148. https://doi.org/10.3390/machines13020148.

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Optimizing energy consumption in machining processes is critical for achieving sustainable manufacturing. This study introduces an Automation-Supported measurement approach that integrates a custom power analyzer with real-time data logging and visualization capabilities to accurately measure energy usage during CNC (computer numerical control) operations. Statistical comparisons were conducted using the independent samples t-test and Taguchi analysis to evaluate the effectiveness of the proposed method against traditional measurement techniques. The results revealed that there is a statistica

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Yu, Hui Jun, Zhi Wei Zhou, Cai Biao Chen, and Ju Hui Gu. "Design of Locomotive Intelligent Watt Hour Meter Based on STM32." Applied Mechanics and Materials 672-674 (October 2014): 1205–9. http://dx.doi.org/10.4028/www.scientific.net/amm.672-674.1205.

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The paper focuses on the locomotive intelligent watt hour meter based on STM32. By designing Intelligent watt hour meter main function, hardware architecture, and software processes to achieve energy data display, storage, and duplex communication. The hardware structure consists of main control module, electric energy metering module, communication module and other components, electric energy metering module is responsible for data acquisition, the main control module is responsible for data processing, communications module is responsible for two-way communication. Using MATLAB software to s

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Brooks, Christopher, Mark Swainson, Ian Beauchamp, Isabel Campelos, Ruzaina Ishak, and Wayne Martindale. "Transformational Steam Infusion Processing for Resilient and Sustainable Food Manufacturing Businesses." Foods 10, no. 8 (2021): 1763. http://dx.doi.org/10.3390/foods10081763.

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Here we show how food and beverage manufacturers report more incisive sustainability and product fulfilment outcomes for their business enterprises when innovative processing technologies are used. The reported steam infusion technology heats food materials within a Vaction Pump device so that steam is directed into the food material within a much reduced volume, reducing the use of steam and processing time. This study reports how such technological interventions will enable supply chain stakeholders to demonstrate responsible consumption by connecting assessments for the reduction of greenho

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Shen, Zhaoxin, and Xiuxu Zhao. "Evaluation of Resource Utilization Efficiency in the Machining Process Based on the SBM-DEA Model with Non-Expected Output." Processes 11, no. 3 (2023): 916. http://dx.doi.org/10.3390/pr11030916.

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As one of the basic industries in the manufacturing industry, the modeling and evaluation of resource utilization efficiency in the machining process is the premise of energy conservation and consumption reduction in the manufacturing industry. Mechanical processing is the process of using resources to change the shape and performance of the blank to form the workpiece and generate emissions. However, the current research on the utilization of machining process resources, whether focusing on energy efficiency or emissions, cannot provide a comprehensive solution to this problem. Therefore, thi

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Wróbel-Jędrzejewska, Magdalena, and Ewelina Włodarczyk. "Comparison of Carbon Footprint Analysis Methods in Grain Processing—Studies Using Flour Production as an Example." Agriculture 14, no. 1 (2023): 14. http://dx.doi.org/10.3390/agriculture14010014.

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Rational energy management in food production is one of the key actions in the context of reducing greenhouse gas emissions. Ongoing rapid climate change and global warming are making energy consumption an increasingly critical point in food production, throughout the “farm-to-table” manufacturing chain. The carbon footprint (CF) can be used to assess the amount of greenhouse gas (GHG) emissions in the area of food cultivation, production and distribution. The work purpose was to characterize the CF methodology on the basis of literature data, to analyze manufacturing processes in production p

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Bolanowski, Marek, Andrzej Paszkiewicz, Tomasz Żabiński, Grzegorz Piecuch, Mateusz Salach, and Krzysztof Tomecki. "System Architecture for Diagnostics and Supervision of Industrial Equipment and Processes in an IoE Device Environment." Electronics 12, no. 24 (2023): 4935. http://dx.doi.org/10.3390/electronics12244935.

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IoE components are becoming an integral part of our lives and support the operation of systems such as smart homes, smart cities, or Industry 4.0. The large number and variety of IoE components force the creation of flexible systems for data acquisition, processing, and analysis. The work presents a proposal for a new flexible architecture model and technology stack designed for the diagnostics and monitoring of industrial components and processes in an IoE device environment. The proposed solutions allow creating custom flexible systems for managing a distributed IoT environment, including th

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Girdu, Constantin Cristinel, and Catalin Gheorghe. "Energy Efficiency in CO2 Laser Processing of Hardox 400 Material." Materials 15, no. 13 (2022): 4505. http://dx.doi.org/10.3390/ma15134505.

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The use of laser technology for materials processing has a wide applicability in various industrial fields, due to its proven advantages, such as processing time, economic efficiency and reduced impact on the natural environment. The expansion of laser technology has been possible due to the dynamics of research in the field. One of the directions of research is to establish the appropriate cutting parameters. The evolution of research in this direction can be deepened by determining the efficiency of laser cutting. Starting from such a hypothesis, the study contains an analysis of laser cutti

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18

Soulis, Spyridon, George Konstantopoulos, Elias P. Koumoulos, and Costas A. Charitidis. "Impact of Alternative Stabilization Strategies for the Production of PAN-Based Carbon Fibers with High Performance." Fibers 8, no. 6 (2020): 33. http://dx.doi.org/10.3390/fib8060033.

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The aim of this work is to review a possible correlation of composition, thermal processing, and recent alternative stabilization technologies to the mechanical properties. The chemical microstructure of polyacrylonitrile (PAN) is discussed in detail to understand the influence in thermomechanical properties during stabilization by observing transformation from thermoplastic to ladder polymer. In addition, relevant literature data are used to understand the comonomer composition effect on mechanical properties. Technologies of direct fiber heating by irradiation have been recently involved and

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19

Wati, Devisa Restiana, and Ikhlasul Amallynda. "A No-Idle Flow Shop Scheduling using Fire Hawk Optimizer to Minimize Energy Consumption." Jurnal Teknik Industri 24, no. 1 (2023): 65–80. http://dx.doi.org/10.22219/jtiumm.vol24.no1.65-80.

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The current energy crisis is a pressing global challenge, with the industrial sector accounting for half of global energy consumption. Scheduling is considered one of the potential methods to reduce energy consumption. This article introduces the Fire Hawk Optimizer (FHO) algorithm to solve the no-idle flow shop scheduling problem to minimize overall energy consumption. FHO organizes the job sequence in no-idle flow shop scheduling for reduce energy consumption. This research investigates the use of different machine speed levels, namely slow, fast, and normal, based on case data of manufactur

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20

Yakunin, A. G. "Research and development of data compression methods for technical monitoring systems." Herald of Dagestan State Technical University. Technical Sciences 50, no. 3 (2023): 156–66. http://dx.doi.org/10.21822/2073-6185-2023-50-3-156-166.

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Objective. The aim of the study is to develop methods for data compression in relation to monitoring systems.Method. The studies were carried out mainly experimentally, by processing data generated by the information-measuring system of the Altai State Technical University in the process of meteorological observations, temperature control and control of the consumption of such energy resources as hot and cold water, heat supply. However, when it was proposed to change their structure and presentation form to compact the stored data, the degree of compression was found theoretically.Result. The

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21

Yarlagadda, Sri Charan. "Role of Artificial Intelligence, Automation, and Machine Learning in Sustainable Plastics Packaging markets: Progress, Trends, and Directions." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 9s (2023): 818–28. http://dx.doi.org/10.17762/ijritcc.v11i9s.9489.

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The optimisation of manufacturing processes in terms of resource consumption, waste minimization, and pollutant emissions is gaining prominence, especially in small and medium-sized enterprises (SMEs). The advent of digital technology and the subsequent explosion in data volume is another key factor. There is great potential in the data collected from a wide variety of devices and systems, which is why even smaller businesses require access to clever, dynamic analytic models. Sustainable packaging solutions are gaining significance as the world struggles to address global environmental issues.

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Chi, Xiongfei. "Control Algorithm of Precision Machining." E3S Web of Conferences 260 (2021): 03020. http://dx.doi.org/10.1051/e3sconf/202126003020.

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Due to more and more private customized non-standard design and precision manufacturing, as well as strict requirements for green environmental protection and sustainable economic development mode, it is challenging to realize the synchronous meeting of energy-saving optimization requirements in the processing process of high-precision workpiece. A new semi-automatic machining optimization system is proposed in this paper. The system is based on the high-precision 3D computer files of the workpiece to be processed and the laser thermophysical system. At the same time, the processing parameters

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Butyrin, Andrey Y., Ammar Hameed Shnain, G. Keerthi Reddy, et al. "Assessing the Environmental Impact of Plastic Waste using Life Cycle Assessment." E3S Web of Conferences 581 (2024): 01010. http://dx.doi.org/10.1051/e3sconf/202458101010.

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This research use a life cycle assessment (LCA) paradigm to investigate the environmental effects of plastic waste management practices. The environmental impacts of these processes are measured using experimental data. The acquisition of raw materials, particularly in plastic manufacturing, results in considerable environmental consequences, including an energy expenditure of 1200 MJ and the release of 300 kg of CO2. Likewise, waste processing activities, such as plastic shredding and molding, need 1500 MJ of energy and produce 400 kg of CO2 emissions. The operational lifespan of the product

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Kanoun, Olfa, Sabrine Khriji, Slim Naifar, et al. "Prospects of Wireless Energy-Aware Sensors for Smart Factories in the Industry 4.0 Era." Electronics 10, no. 23 (2021): 2929. http://dx.doi.org/10.3390/electronics10232929.

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Advanced sensors are becoming essential for modern factories, as they contribute by gathering comprehensive data about machines, processes, and human-machine interaction. They play an important role in improving manufacturing performance, in-factory logistics, predictive maintenance, supply chains, and digitalization in general. Wireless sensors and wireless sensor networks (WSNs) provide, in this context, significant advantages as they are flexible and easily deployable. They have reduced installation and maintenance costs and contributed by reducing cables and preinstalled infrastructure, le

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Andrew Nii Anang, Peter Ofuje Obidi, Adeleye Oriola Mesogboriwon, James Opani Obidi, Maurice kuubata, and Dabira Ogunbiyi. "THE role of Artificial Intelligence in industry 5.0: Enhancing human-machine collaboration." World Journal of Advanced Research and Reviews 24, no. 2 (2024): 380–400. http://dx.doi.org/10.30574/wjarr.2024.24.2.3369.

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The emergence of Industry 5.0 marks a transformative shift in the manufacturing landscape, emphasizing a synergistic relationship between humans and machines. This paper explores the pivotal role of Artificial Intelligence (AI) in enhancing human-machine collaboration within this paradigm. By leveraging AI technologies, industries can foster a more personalized, efficient, and innovative work environment. AI systems facilitate seamless communication and decision-making processes, thereby augmenting human capabilities rather than replacing them. This collaboration allows for the optimization of

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Andrew, Nii Anang, Ofuje Obidi Peter, Oriola Mesogboriwon Adeleye, Opani Obidi James, kuubata Maurice, and Ogunbiyi Dabira. "THE role of Artificial Intelligence in industry 5.0: Enhancing human-machine collaboration." World Journal of Advanced Research and Reviews 24, no. 2 (2024): 380–400. https://doi.org/10.5281/zenodo.15076074.

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The emergence of Industry 5.0 marks a transformative shift in the manufacturing landscape, emphasizing a synergistic relationship between humans and machines. This paper explores the pivotal role of Artificial Intelligence (AI) in enhancing human-machine collaboration within this paradigm. By leveraging AI technologies, industries can foster a more personalized, efficient, and innovative work environment. AI systems facilitate seamless communication and decision-making processes, thereby augmenting human capabilities rather than replacing them. This collaboration allows for the optimization of

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Singha Roy, Pritha, Gaurab Joarder, Saibal Debnath, and Avisek Pahari. "A REVIEW OF THE INNOVATIVE DRYING TECHNOLOGIES FOR BIOPHARMACEUTICALS." International Journal of Advanced Research 10, no. 05 (2022): 1100–1111. http://dx.doi.org/10.21474/ijar01/14820.

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Reviewing data from the previous twenty to twenty-five years reveals that bio-pharmaceuticals are a sudden, dramatic, and incredibly significant finding in progressively enhancing the quality of life for patients with different kinds of malignancies, auto-immune illnesses, genetic disorders, etc. Drying technologies are a required manufacturing step in the pharmaceutical industry/production unit, and an understanding of drying technologies and how to use them is now an absolute must. With the increased demand for biopharmaceuticals, it is essential to reduce production costs without sacrificin

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Enow, Ojong Felix, Andrew Tochukwu Ofoedu, Ebimor Yinka Gbabo, and Possible Emeka Chima. "The Role of Embedded Systems in Industrial Automation: A Review of Global Developments." International Journal of Multidisciplinary Research and Growth Evaluation 4, no. 2 (2023): 836–43. https://doi.org/10.54660/.ijmrge.2023.4.2.836-843.

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The integration of embedded systems in industrial automation has witnessed significant advancements globally, revolutionizing manufacturing processes and enhancing overall efficiency. This Review provides a comprehensive review of the role played by embedded systems in industrial automation, highlighting key developments on a global scale. Embedded systems, characterized by their dedicated functionality within larger systems, have become indispensable in the realm of industrial automation. This paper explores the evolution and impact of embedded systems in automating various aspects of industr

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Zhulai, Yu O., and D. D. Zahovailova. "Energy efficient technologies for the mining industry." Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu, no. 6 (December 25, 2022): 11–17. http://dx.doi.org/10.33271/nvngu/2022-6/011.

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The cavitation generator of fluid pressure oscillations is a promising device for productivity and efficiency improvement in the mining industry (hereinafter referred to as the generator). Due to the periodic growth, separation and collapse of cavitation cavities into generator volume, shock pressure oscillations are realized with a frequency range from 1 to 20 kHz. Oscillatory pressure peak values are up by 4 times higher than the steady-state pressure at the generator inlet. The destroyed rock takes on a fatigue character under repeated alternating effects of force impulses. Due to the devel

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Liu, Wei, and Qingcheng Huang. "Research on Carbon Footprint Accounting in the Materialization Stage of Prefabricated Housing Based on DEMATEL-ISM-MICMAC." Applied Sciences 13, no. 24 (2023): 13148. http://dx.doi.org/10.3390/app132413148.

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This work employs the carbon emission factor method to offer real-world instances for carbon footprint accounting, allowing for a thorough analysis of the carbon footprint and important influencing elements throughout the materialization stage of prefabricated housing. To identify the 18 important influencing factors that need to be examined from the five stages of building material production, conveyance of building materials, component manufacturing, component transportation, and building, this paper applies the DEMATEL-ISM-MICMAC (Decision-Making Trial and Evaluation Laboratory–Interpretive

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Zhang, Huiling, Ruping Liu, Huiqing Zhao, et al. "Research Progress of Biomimetic Memristor Flexible Synapse." Coatings 12, no. 1 (2021): 21. http://dx.doi.org/10.3390/coatings12010021.

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With the development of the Internet of things, artificial intelligence, and wearable devices, massive amounts of data are generated and need to be processed. High standards are required to store and analyze this information. In the face of the explosive growth of information, the memory used in data storage and processing faces great challenges. Among many types of memories, memristors have received extensive attentions due to their low energy consumption, strong tolerance, simple structure, and strong miniaturization. However, they still face many problems, especially in the application of a

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Mwampulo, Andrew, Arthur Omari, and Duncan Mwakipesile. "Experimental Assessment of Energy Potentials from Tea Wastes as a Source of Energy: A Case of Itona Tea Factory in Tanzania." International Journal of Energy and Power Engineering 13, no. 4 (2024): 63–66. http://dx.doi.org/10.11648/j.ijepe.20241304.11.

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Tea processing is an energy-intensive process. However, high agricultural productivity and subsequently the growth of the green revolution have been made possible only by a large amount of energy inputs, especially those from fossil fuels, wood fuels, and electricity. With recent price rise and scarcity of these fuels there has been a trend towards use of alternative energy sources such as waste (agricultural waste) to energy that could solve both energy and environment issues. Moreover, these energy resources have not been able to provide an economically viable solution for agricultural appli

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ROUSSIS, Ioannis, Ioanna KAKABOUKI, Panteleimon STAVROPOULOS, et al. "Carbon Footprint Analysis of Processing Tomato Cultivation in Greece." Bulletin of University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca. Horticulture 80, no. 2 (2023): 76–79. http://dx.doi.org/10.15835/buasvmcn-hort:2023.0021.

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Agriculture contributes to global warming through the emissions of greenhouse gasses (GHGs). As one of the most important horticultural crops, tomato (Lycopersicon esculentum Mill.) is of great economic importance. Approximately 80% of the tomatoes grown around the world are processed into sauces, juices, ketchup, canned tomatoes, and soups. The goal of the present study was to assess the carbon footprint of commercially grown processing tomatoes in Greece. The emissions were calculated by using the Cool Farm Tool software. For data collection, a questionnaire was distributed to processing tom

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Markatos, Nikolaos Grigorios, Alireza Mousavi, Giulia Pippione, and Roberto Paoletti. "Industry 4.0-Based Framework for Real-Time Prediction of Output Power of Multi-Emitter Laser Modules during the Assembly Process." Electronics 12, no. 3 (2023): 766. http://dx.doi.org/10.3390/electronics12030766.

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The challenges of defects in manufacturing and assembly processes in optoelectronic industry continue to persist. Defective products cause increased time to completion (cycle time), energy consumption, cost, and loss of precious material. A complex laser assembly process is studied with the aim of minimising the generation of defective laser modules. Subsequently, relevant data were gathered to investigate machine learning and artificial intelligence methods to predict the output beam power of the module during the assembly process. The assembly process was divided into a number of chain steps

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Leite, Sueli Souza, Gessica Mina Kim Jesus, Manoel Cléber de Sampaio Alves, et al. "Analysis of the parameters affecting the surface sanding of Pinus elliottii and Corymbia citriodora wood species." BioResources 14, no. 2 (2019): 2773–83. http://dx.doi.org/10.15376/biores.14.2.2773-2783.

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Wood is a versatile and renewable material. It features characteristic mechanical resistance, thermal and electrical insulation, easy workability, and low energy consumption during processing. These properties make it attractive compared with other materials, mainly in the manufacturing and civil construction industries. One of the most important processes in the logging industry is sanding, though it is treated empirically by companies without a systematic study of the influence of its parameters, and it incurs high costs in this sector. Therefore, this work analyzed the effects of the sandpa

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Aragonés, Raúl, Roger Malet, Joan Oliver та ін. "Milliwatt μ-TEG-Powered Vibration Monitoring System for Industrial Predictive Maintenance Applications". Information 15, № 9 (2024): 545. http://dx.doi.org/10.3390/info15090545.

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This paper presents a novel waste-heat-powered, wireless, and battery-less Industrial Internet of Things (IIoT) device designed for predictive maintenance in Industry 4.0 environments. With a focus on real-time quality data, this device addresses the limitations of current battery-operated IIoT devices, such as energy consumption, transmission range, data rate, and constant quality of service. It is specifically developed for heat-intensive industries (e.g., iron and steel, cement, petrochemical, etc.), where self-heating nodes, low-power processing platforms, and industrial sensors align with

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Aragonés, Raúl, Roger Malet, Joan Oliver та ін. "Milliwatt μ-TEG-Powered Vibration Monitoring System for Industrial Predictive Maintenance Applications". Information 15, № 9 (2024): 545. https://doi.org/10.3390/info15090545.

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This paper presents a novel waste-heat-powered, wireless, and battery-less Industrial Internet of Things (IIoT) device designed for predictive maintenance in Industry 4.0 environments. With a focus on real-time quality data, this device addresses the limitations of current battery-operated IIoT devices, such as energy consumption, transmission range, data rate, and constant quality of service. It is specifically developed for heat-intensive industries (e.g., iron and steel, cement, petrochemical, etc.), where self-heating nodes, low-power processing platforms, and industrial sensors align with

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Pavel Yurievich, Ilyushin, Vyatkin Kirill Andreevich, and Kozlov Anton Vadimovich. "Development of a Digital Well Management System." Applied System Innovation 6, no. 1 (2023): 31. http://dx.doi.org/10.3390/asi6010031.

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The modern oil industry is characterized by a strong trend towards the digitalization of all technological processes. At the same time, during the transition of oil fields to the later stages of development, the issues of optimizing the consumed electricity become relevant. The purpose of this work is to develop a digital automated system for distributed control of production wells using elements of machine learning. The structure of information exchange within the framework of the automated system being created, consisting of three levels of automation, is proposed. Management of the extracti

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Alam, Md Shafayet, Imran Hossain, Gaurab Dutta, and Erica Murray. "Effects of Different Scan Speeds on Microstructural and Corrosion Properties of Additively Manufactured HSLA Steels in 3.5% NaCl Solution." ECS Meeting Abstracts MA2022-02, no. 10 (2022): 696. http://dx.doi.org/10.1149/ma2022-0210696mtgabs.

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In automotive applications, high-strength low alloy (HSLA) steels are providing enhanced material properties, due to the high yield strength, less fragility, and lower weight, which also promotes lower fuel consumption. HSLA steels contain a small amount of carbon (under 0.2%) and also contain small amounts of alloying elements such as copper, nickel, niobium, vanadium, chromium, molybdenum and zirconium. This eliminates the toughness reducing effect of a pearlitic volume fraction, yet maintains and increases the material's strength by refining the grain size. Therefore, HSLA steels are used f

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Aichberger, Christian, and Gerfried Jungmeier. "Environmental Life Cycle Impacts of Automotive Batteries Based on a Literature Review." Energies 13, no. 23 (2020): 6345. http://dx.doi.org/10.3390/en13236345.

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We compiled 50 publications from the years 2005–2020 about life cycle assessment (LCA) of Li-ion batteries to assess the environmental effects of production, use, and end of life for application in electric vehicles. Investigated LCAs showed for the production of a battery pack per kWh battery capacity a median of 280 kWh/kWh_bc (25%-quantile–75%-quantile: 200–500 kWh/kWh_bc) for the primary energy consumption and a median of 120 kg CO2-eq/kWh_bc (25%-quantile–75%-quantile: 70–175 kg CO2-eq/kWh_bc) for greenhouse gas emissions. We expect results for current batteries to be in the lower range.

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Spencer, D. B., J. W. Temple, D. M. Forsythe, and B. E. Bond. "Large-Scale Rotary Shear Shredder Performance Testing." Journal of Energy Resources Technology 107, no. 2 (1985): 289–96. http://dx.doi.org/10.1115/1.3231192.

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Slow-speed rotary shear shredders have recently received considerable attention for processing of municipal solid waste. Potential benefits from shear shredding could include reduced explosion potential, lower power consumption, lower operating and maintenance costs and less overgrinding of glass. Although there has been much interest in rotary shear shredders, little actual operating data exists showing the capacity and performance of these units on municipal solid waste at full scale. A large-scale, 50 tph (45.3 tonnes/hr) Iowa Manufacturing Company (Cedarapids) Model 5096 (127 cm × 244 cm)

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Ifeoluwa Sarah Fesojaye, Favour Dada, and Florence Acha. "Innovative applications of nanomaterials in semiconductor manufacturing: Advancing efficiency and performance for next-generation technologies." World Journal of Advanced Research and Reviews 20, no. 3 (2023): 2048–70. https://doi.org/10.30574/wjarr.2023.20.3.2446.

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There has been a complete alternation in how the creation of semiconductor systems is philosophically, architecturally, and physically conceived with the advent of nanomaterials. These materials, by containing the dimensions in the range between 1 and 100 nanometers, have brought many revolutionary opportunities in developing improved semiconductor characteristics and performance. Micro and nano electronics have played a pivotal role in introducing new methodologies in transistor technology, chip layout and manufacturing methods, enlargement in speed, consuming power, and miniaturization of el

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Devoino, O. G., V. Gorbunov, D. A. Shpackevitch, et al. "On Energy Efficiency Characteristics of Laser Erosion on Oxidic Surfaces of Carbon Steels, Cast Iron and Low-alloy Non-ferrous Alloys During Deoxidizing Cleaning. Part 1." Science & Technique 24, no. 1 (2025): 12–23. https://doi.org/10.21122/2227-1031-2025-24-1-12-23.

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A comparison of operating characteristics has been carried out for laser erosion cleaning (LC) processes studied in recent years and prospective for metalworking manufacturing of products/pieces from a number of carbon steels, cast iron and low-alloy non-ferrous metal alloys from oxidized layers formed as products of gas or other corrosion, often having inhomogeneous structure and porosity. To analyze the efficiency of various (in terms of layer composition) laser processes, it is advisable to use a group of parameters that affect the energy efficiency of LC-processing during the deoxidizing o

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Rajvin Mehta and Kavish Devnani. "Integrating IoT with machine learning: A path towards ubiquitous smart applications." International Journal of Science and Research Archive 4, no. 1 (2021): 217–21. http://dx.doi.org/10.30574/ijsra.2021.4.1.0142.

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The integration of the Internet of Things (IoT) with Machine Learning (ML) is a transformative advancement that is revolutionizing the way data-driven decision-making occurs across various industries. IoT systems comprise interconnected devices that collect and transmit vast amounts of real-time data from sensors, machines, and appliances. However, merely collecting data is not sufficient; the real value lies in the analysis and interpretation of this data to generate actionable insights. This is where ML comes into play. ML techniques allow systems to learn from the data generated by IoT devi

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Bunke, Samantha, Xi Chen, Michael Machala, Ines Azevedo, Sally Benson, and William Abraham Tarpeh. "Life Cycle Comparison of Battery Recycling and Conventional Material Refining." ECS Meeting Abstracts MA2022-01, no. 5 (2022): 586. http://dx.doi.org/10.1149/ma2022-015586mtgabs.

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Background: The rise of renewable energy generation and vehicle electrification has created exponential growth in lithium-ion battery (LIB) production, particularly for electric vehicles.1 However, the limited supply of raw materials needed for prominent battery chemistries has exacerbated concerns linked to economic, environmental, national security, and human rights dimensions.2 For example, raw materials necessary for LIB production are not equally distributed, and current supply chains are insufficient for projected demand. For countries with natural reserves of critical LIB elements, the

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Parsoya, Shubham, and Chhagan Lal Parsoya. "Biofuel Production from the Wastes of Fisheries: An Alternative to Petroleum." Just Agriculture, An Open Access Peer Reviewed e-Newsletter (e-ISSN: 2582-8223) 2 (JAN 2022), no. 5 (2022): 1–14. https://doi.org/10.5281/zenodo.5910844.

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<strong>Biofuel Production from the Wastes of Fisheries: An Alternative to Petroleum</strong> <em><strong>Authors: </strong></em> <em>Shubham Parsoya and Chhagan Lal Parsoya</em>   <em><strong>Abstract: </strong></em> The importance of biofuels from an energy point of view as well as a reliable substitute to petroleum is significantly growing all over the world. The encouragement in the utilization of green energy and clean energy directs the world toward biofuel as an energy source. India had already announced its National Biofuel Policy for encouraging biof

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Tubiello, Francesco N., Kevin Karl, Alessandro Flammini, et al. "Pre- and post-production processes increasingly dominate greenhouse gas emissions from agri-food systems." Earth System Science Data 14, no. 4 (2022): 1795–809. http://dx.doi.org/10.5194/essd-14-1795-2022.

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Abstract. We present results from the FAOSTAT emissions shares database, covering emissions from agri-food systems and their shares to total anthropogenic emissions for 196 countries and 40 territories for the period 1990–2019. We find that in 2019, global agri-food system emissions were 16.5 (95 %; CI range: 11–22) billion metric tonnes (Gt CO2 eq. yr−1), corresponding to 31 % (range: 19 %–43 %) of total anthropogenic emissions. Of the agri-food system total, global emissions within the farm gate – from crop and livestock production processes including on-farm energy use – were 7.2 Gt CO2 eq.

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admin, admin, Anwar Ja’afar M. .., Mohammed A. Jalil, Noor Sami, and Zaid Saad Madhi. "Multi-Level Fusion Optimization in Cyber-Physical Systems Using Computer Vision-Based Fault Detection." Fusion: Practice and Applications 11, no. 2 (2023): 62–75. http://dx.doi.org/10.54216/fpa.110205.

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The healthcare sector's use of cyber-physical systems to provide high-quality patient treatment highlights the need for sophisticated security solutions due to the wide range of attack surfaces from medical and mobile devices, as well as body sensor nodes. Cyber-physical systems have various processing technologies to choose from, but these technical methods are as varied. Existing technologies are not well-suited for managing complex information about problem identification and diagnosis, which is distinct from technology. To address this issue, intelligent techniques for fusion processing, s

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Xiao, Yongmao, Qingshan Gong, and Xiaowu Chen. "Energy Saving and Low-Cost-Oriented Design Processes of Blank’s Dimensions Based on Multi-Objective Optimization Model." Processes 7, no. 11 (2019): 811. http://dx.doi.org/10.3390/pr7110811.

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The blank’s dimensions are an important focus of blank design as they largely determine the energy consumption and cost of manufacturing and further processing the blank. To achieve energy saving and low cost during the optimization of blank dimensions design, we established energy consumption and cost objectives in the manufacturing and further processing of blanks by optimizing the parameters. As objectives, we selected the blank’s production and further processing parameters as optimization variables to minimize energy consumption and cost, then set up a multi-objective optimization model.

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Li, Bing Bing, Hong Chao Zhang, Qing Di Ke, Li Ding, and Lei Zhang. "Overview of Energy Consumption Model for Manufacturing Processes." Applied Mechanics and Materials 130-134 (October 2011): 2288–93. http://dx.doi.org/10.4028/www.scientific.net/amm.130-134.2288.

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The energy consumption for manufacturing processes is the largest impact contributor in various characterization categories, based on the assessment of environmental effects during the whole life cycle. It is necessary to investigate the manufacturing processes in depth to find out mechanism that can improve energy efficiency. This paper presents a comprehensive overview on two important aspects of energy consumption models for manufacturing processes: 1) two data collection methods: top-down and bottom-up; 2) two process-based analytical methods: thermodynamic model (including energy flow ana

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