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Optimal coordination of Production, Logistics, and Maintenance 4.0: A framework for Multi-Site Stamping Plants 6

Optimal coordination of Production, Logistics, and Maintenan...

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6th international conference on Industry 4.0 and Smart Manufacturing, ISM 2024

作者： Zerrad, Raoua Diaz, Kamar Mechkouri, Meriem Hayani Sefiani, Naoufal Department of Mechanical Engineering Research Laboratory in Engineering Innovation and Management of Industrial Systems Faculty of Sciences and Techniques Abdelmalek Essaadi University Tangier Morocco Department of Industrial Engineering and Maintenance Computer Engineering Production and Maintenance Laboratory University of Lorraine Metz France

this paper presents a comprehensive framework for optimal coordination of production, logistics, and maintenance in multi-site stamping plants within the context of Industry 4.0. By integrating key technologies such as the Internet of things, cloud computing and big data analytics, we developed a system that would enable real-time data sharing, predictive analytics, and intelligent decision-making. this framework aims to enhance operational efficiency, reduce downtime, and improve service rate. Additionally, our approach aims to optimize spare parts inventory management across different sites, minimizing inventory costs and lead times by ensuring timely availability and efficient sourcing of spare parts. © 2024 the Authors. Published by Elsevier B.V.

关键词： Inventory control

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Investigating Research Trends in Computer Vision for Food Quality control: A Bibliometric Approach 6

Investigating Research Trends in Computer Vision for Food Qu...

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6th international conference on Industry 4.0 and Smart Manufacturing, ISM 2024

作者： Lysova, Natalya Solari, Federico Montanari, Roberto Department of Engineering for Industrial Systems and Technologies University of Parma Parco Area delle Scienze 181/A Parma43124 Italy

the production throughputs of the food industry grow continuously due to the ever-increasing customer demand. At the same time, food safety measures become increasingly strict. To this end, efficient quality control is essential to ensure quality and safety for consumers, and to guarantee efficient and valuable production for industrial stakeholders. Computer vision is often applied to this end, usually integrated with other Industry 4.0 technologies and process automation. Computer vision applications in quality control, indeed, can greatly enhance supply chain management in the food industry by maintaining consistent product quality and minimizing waste. In this paper, a keyword-based analysis is carried out to assess the main research trends and topics in the field of computer vision for quality control in the food industry. the bibliometric analysis aims to assess the main applications of the technology in terms of processes and products and the main issues targeted by the analyses. Finally, the results of the bibliometric investigation allow to identify and highlight topics that present potential for future investigations in the field. © 2024 the Authors. Published by Elsevier B.V.

关键词： Food industry

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Evaluating Llama-3.1 for Adverse Drug Event Entity and Relationship Extraction Across Prompting Techniques 3rd

Evaluating Llama-3.1 for Adverse Drug Event Entity and Rel...

引用

3rd international conference on Advances in computing Research, ACR 2025

作者： Prioleau, Howard Aryal, Saurav K. Burge, Legand Electrical Engineering and Computer Science Howard University 2400 6th St NW WashingtonDC20059 United States

ISBN: (纸本)9783031876462

Post-market adverse drug effects (ADEs) are often found in the clinical notes of Electronic Health Records. We evaluate open-weight large language model, Llama-3.1, for detection of ADEs, Named Entity Recognition, and Entity Linkage tasks across varying prompting techniques suited for text decomposition including, but not limited to zero-shot, few-shot and tree of thought. Finally, we propose a novel improvement to the tree of thought prompting technique which combines consistency and thought merging. Our proposed approach is then evaluated and compared with the other approaches on these tasks using standard metrics for each task (f1, precision and recall). © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Adverse Drug Events Artificial intelligence Clinical Notes Large language models Llama n2c2

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Study on the Correlation between the Black Sludge and Chemical Oxygen Demand in Wastewater from Cold Rolling Pickling Lines 6

Study on the Correlation between the Black Sludge and Chemic...

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2024 6th international conference on Advanced Materials and Ecological Environment, AMEE 2024

作者： Xu, Xianglai Li, Donghui Yan, Cui Tian, Peng Liu, Yongyue Ren, Xueping Gao, Jiangtao Jia, Qingwei Wang, Baolei School of Electrical Automation and Information Engineering Tianjin University Tianjin300072 China Intelligent Technology Co. Ltd. Zhejiang Ningbo315500 China Marine College Tangshan Normal University Hebei Tangshan063000 China School of Materials Science and Engineering University of Science and Technology Beijing100083 China Tangshan Donghua Iron and Steel Enterprise Group Co. Ltd. Hebei Tangshan063016 China

Black sludge is commonly found in the acid tanks of cold rolling pickling lines and in the pipelines of acid regeneration units, impacting system efficiency and causing negative effects on equipment and the environment. To address this issue, a method combining black sludge composition analysis and Chemical Oxygen Demand (COD) measurement of rinse water was proposed to study its origin and formation mechanisms. the results showed that the black sludge mainly contains carbon, chlorine, oxygen, and small amounts of iron, with significant organic matter loss between 300-400°C, indicating a high content of alkanes and cycloalkanes. the COD value of rinse water is higher when fresh acid is used, and alkanes and cycloalkanes are the main contributors to the formation of black sludge and the increase in COD values. Strengthening the management of fresh acid can help reduce sludge formation. © Published under licence by IOP Publishing Ltd.

关键词： Chemical oxygen demand

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Safe Reinforcement Learning for Social Motor Coordination in Two Dimensional Space 26

Safe Reinforcement Learning for Social Motor Coordination in...

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26th international conference on Industrial Technology, ICIT 2025

作者： Yang, Fan Huang, Yuening Zhai, Chao Zhang, Hehong China University of Geosciences School of Automation Wuhan Campus China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Rice University George R. Brown School of Engineering and Computing HoustonTX United States Fuzhou University School of Computer and Data Science Fuzhou China

ISBN: (纸本)9798331521950

this paper presents an interactive motion control method based on reinforcement learning, designed to assist children with autism who have social motor impairments through a mirror game intervention. the virtual teacher uses the Deep Deterministic Policy Gradient (DDPG) algorithm to optimize its actions, guiding the participant to follow a Lissajous trajectory. To ensure safety, a motion-correction mechanism was developed, which automatically adjusts actions when the predicted trajectory surpasses predefined safety boundaries. the reward function considers both the distance between the virtual teacher and the target trajectory, as well as the distance between the virtual teacher and the participant, with dynamic adjustments applied by the motion-correction mechanism. Experimental results demonstrate that the virtual teacher effectively guides the participant towards the target trajectory while adhering to safety constraints. © 2025 IEEE.

关键词： Reinforcement learning

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Application of Recurrent Neural Networks for Predictive Modeling of electrical Submersible Pumps in Oil Extraction 11

Application of Recurrent Neural Networks for Predictive Mode...

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11th Vienna international conference on Mathematical Modelling, MAthMOD 2025

作者： Rebello, Carine Menezes Costa, Erbet Almeida Luiz De Abreu, Odilon Santana Reges, Galdir Viena, Vinicius Guimares Mendes, Tefilo Paiva Fontana, Marcio Ribeiro Bacellar, Francisco Raphael Ribeiro, Marcos Pellegrini Foresti, Bernardo Pereira Schnitman, Leizer Nogueira, Idelfonso B.R. Department of Chemical Engineering Norwegian University of Science and Technology Norway Department of Chemical Engineering Federal University of Bahia Bahia Brazil Department of Electrical and Computer Engineering Federal University of Bahia Bahia Brazil CENPES Petrobras R&D Center Ilha do Fundo Rio de Janeiro Brazil

this study presents a mathematical modeling framework that leverages recurrent neural networks (RNNs), specifically echo state networks (ESNs) and long short-Term memory (LSTM) architectures, for the predictive modeling of electrical submersible pumps (ESPs) in offshore oil extraction operations. Utilizing real operational data from an offshore oil field, the research addresses the inherent complexity and nonlinear dynamics of ESP systems by employing these recurrent structures to capture and represent the temporal dependencies within the data. Key challenges, such as data noise, variability, and limited diversity, are systematically tackled to ensure robust dynamic modeling. A comparative analysis evaluates the performance of ESN and LSTM models under these constrained data conditions, aiming to identify the superior model in terms of predictive accuracy and resilience. the modeling approach emphasizes the formulation, parameterization, and validation processes essential for effective ESP optimization and control in real-world industrial settings. Findings reveal the distinct strengths and limitations of each RNN variant when applied to offshore operational data. Copyright © 2025 the Authors.

关键词： Offshore oil well production

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A Learning Factory Implementation with Industry, Teaching and Research Perspectives 6

A Learning Factory Implementation with Industry, Teaching an...

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6th international conference on Industry 4.0 and Smart Manufacturing, ISM 2024

作者： Quinn, William Ahearn, Aaron Buckley, Killian Casotti, Alberto Ozturk, Cemalettin School of Mechanical Electrical and Process Engineering Munster Technological University Cork Ireland

In the last decade, Industry 4.0 has resulted in widespread change in how manufacturing operates and, as a consequence, the skills set that a graduating engineer is required to display. this rapid change has resulted in challenges for educational institutions at third level as mechanical and manufacturing engineering has now become a interdisciplinary profession requiring not only traditional skills but also skills in information technology, computer science, among others. the challenge in an educational setting is to develop a space where various disciplines can work together, both educators and students in an industrially relevant space. For this reason, a learning factory has been developed in the Munster Technological University with that purpose in mind. Following up on previous work, this paper presents achievements in educational, industrial interaction and research projects. the learning factory has permitted the development of masters level modules, provide training for local industry and also research in the area of machine learning, digital twin, and autonomous flexible manufacturing systems, projects which are summarised in this paper. the paper ends with a discussion of the future direction of the learning factory with the objective of sustainable growth. © 2025 the Authors.

关键词： Networked control systems

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Design and Simulation of SCADA System to Improve Reliability of a Distribution Feeder: A Case Study on Bahir Dar, Feeder R6-G2 11th

Design and Simulation of SCADA System to Improve Reliability...

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11th EAI international conference on Advancement of science and Technology, ICAST 2023

作者： Fenitaw, Melaku Asrat Beza, Teketay Mulu Faculty of Electrical and Computer Engineering Bahir Dar Institute of Technology – Bahir Dar University Bahir Dar Ethiopia

ISBN: (纸本)9783031641503

this paper presents a design and simulation of a supervisory control and data acquisition (SCADA) system to improve the reliability of a distribution feeder in Bahir Dar, Ethiopia. the SCADA system was modeled using MATLAB Simulink and Java programming language, and it includes sensors, circuit breakers, and a human-machine interface (HMI) for remote monitoring and control of the distribution feeder. the results of the simulation show that the proposed SCADA system has significantly improved the reliability of the distribution feeder, with a 60% reduction in the system average interruption duration index (SAIDI), a 61% reduction in the customer average interruption duration index (CAIDI), and a 1.11% improvement in the average service availability index (ASAI). © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Java programming language

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Highly Reliable Information Interaction and Sharing Based on Distributed Collaboration Communication 26

Highly Reliable Information Interaction and Sharing Based on...

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26th international conference on Industrial Technology, ICIT 2025

作者： Xu, Mingxuan Song, Haifeng Wu, Shourong Zhou, Min Dong, Hairong School of Automation and Intelligence Beijing Jiaotong University Beijing100044 China School of Electronic and Information Engineering Beihang University Beijing100191 China Institute of Computing Technology China Academy of Railway Sciences Corporation Limited Beijing10081 China Design Institute of Signal & Communication Beijing National Railway Research Beijing100070 China School of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao266590 China

ISBN: (纸本)9798331521950

To improve the operational efficiency and reliability of high-speed trains (HSTs), the Automatic Train control System has received considerable attention. Train-to-Train (T2T) communication is one of the critical technologies for autonomous train operation. However, the development of T2T communication technology still faces many challenges, particularly regarding communication distance limitations and reliability issues. To address these challenges, this paper introduces an innovative T2T collaborative communication model for HSTs, focusing on highly reliable information interaction and sharing in distributed collaboration environments. the model employs dynamic and static nodes to enable direct T2T information exchange. Using formal verification and state space analysis to ensure the system's reliability and performance. A Build-in-Test (BIT) mechanism is implemented for fault detection and isolation, enhancing the reliability of the system. By analyzing the performance indicators of the system in different scenarios, the reliability of the system was verified. © 2025 IEEE.

关键词： Signaling

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Modeling, simulation and control of the nutritional solution in the hydroponic cultivation of blueberries 6

Modeling, simulation and control of the nutritional solution...

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6th international conference on Industry 4.0 and Smart Manufacturing, ISM 2024

作者： Pacco, Honorato Ccalli Franco Medina, Jorge Lázaro Universidad Nacional de Moquegua Ancash s/n Moquegua18001 Peru

Much importance is being given worldwide to the cultivation of blueberries (Vaccinium corymbosum) for its nutritional qualities, probiotic properties, antioxidant and many others, so productivity and quality in its production is sought using new technologies for its cultivation, and that are efficient and profitable to obtain the good productivity and corresponding quality. Reasons why the fuzzy logic of the LabVIEW software has been used for the control of important parameters in the nutrient solution for the crop, and that allows us a non-linear graphical programming and very easy to use without the need of a programming specialist. the electrical conductivity (EC) in dS/m units and the concentration of hydrogen ions in the nutrient solution (pH) were used as measurement parameters, for this it was instrumented virtually and the fuzzy logic of the Mamdani method was programmed in the LabVIEW block panel. With which the expected results could be obtained in the control of the process since by varying the input variables to the need for nutrients in the nutrient solution system, productivity is achieved in said hydroponic cultivation of blueberries. © 2024 the Authors. Published by Elsevier B.V.

关键词： Fruits

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