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检索条件"任意字段=International Conference on Data and Knowledge Systems for Manufacturing and Engineering"

共 37467 条记录，以下是661-670 订阅

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Towards Test-Driven Performance Validation of a Flexible Cyber-Physical Production System 28

Towards Test-Driven Performance Validation of a Flexible Cyb...

引用

28th IEEE international conference on Emerging Technologies and Factory Automation, ETFA 2023

作者： Biffl, Stefan Meixner, Kristof Hoffmann, David Winkler, Dietmar Lüder, Arndt TU Wien Christian Doppler Laboratory SQI Austria TU Wien Inst. of Information Systems Engineering Austria CDP Austria Otto-von-Guericke U. Institute of Ergonomics Manufacturing Systems and Automation Germany SBA Austria

ISBN: (纸本)9798350339918

Fast changes in production require flexibility regarding products, production processes, and production resources (PPR), moving towards a flexible production system that consists of independent systems. However, production systems engineering traditionally considers mainly static systems and requires advanced capabilities to effectively and efficiently validate performance indicators specified in test scenarios for a flexible production system. For validating production process and system variants, this vision paper explores the Test-Driven Performance Validation (TPV) approach for knowledge representation of (1) a family of production variants (2) with test scenarios on production effects and conditions, and (3) a Production Asset Network that defines PPR configuration dependencies and production data sources as a foundation for calculating a production variant's performance. We conclude with a research agenda towards coordinating performance validation of flexible production with human and machine agents. © 2023 IEEE.

关键词： knowledge representation

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knowledge-Enhanced Recommendation with User-Centric Subgraph Network 40

Knowledge-Enhanced Recommendation with User-Centric Subgraph...

引用

40th IEEE international conference on data engineering, ICDE 2024

作者： Liu, Guangyi Yao, Quanming Zhang, Yongqi Chen, Lei Tsinghua University Department of Electronic Engineering Beijing China Paradigm Inc. Beijing China Guangzhou China

ISBN: (纸本)9798350317152

Recommendation systems, as widely implemented nowadays on various platforms, recommend relevant items to users based on their preferences. The classical methods which rely on user-item interaction matrices has limitations, especially in scenarios where there is a lack of interaction data for new items. knowledge graph (KG)-based recommendation systems have emerged as a promising solution. However, most KG-based methods adopt node embeddings, which do not provide personal-ized recommendations for different users and cannot generalize well to the new items. To address these limitations, we propose knowledge-enhanced User-Centric subgraph Network (KUCNet), a subgraph learning approach with graph neural network (GNN) for effective recommendation. KUCN et constructs a U-I subgraph for each user-item pair that captures both the historical information of user-item interactions and the side information provided in KG. An attention-based GNN is designed to encode the U-I subgraphs for recommendation. Considering efficiency, the pruned user-centric computation graph is further introduced such that multiple U-I subgraphs can be simultaneously computed and that the size can be pruned by Personalized PageRank. Our proposed method achieves accurate, efficient, and interpretable recommendations especially for new items. Experimental results demonstrate the superiority of KUCNet over state-of-the-art KG-based and collaborative filtering (CF)-based methods. Our code and data is available in https://***/leolouis14/KUCNet. © 2024 IEEE.

关键词： Graph neural networks

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international conference on Production and Industrial engineering, CPIE 2023

International Conference on Production and Industrial Engine...

引用

international conference on Production and Industrial engineering, CPIE 2023

ISBN: (纸本)9789819983421

The proceedings contain 72 papers. The special focus in this conference is on Production and Industrial engineering. The topics include: A Comprehensive Overview on Additive manufacturing Processes: Materials, Applications, and Challenges;an Overview of the Untapped Potential of Soft Robotic Arms with Integration of Machining Tools;life Cycle Assessment of Abrasive Flow Machining of 3D Printed Parts: A Comparative Analysis;Modelling and Simulation of Wire DED Additive manufacturing Process;an Overview of the Recent Advances in Additive manufacturing, and Its Scope for the Benefit of Research and Development in Commercial Vehicle Industries;design and Development of Customized Helmet for Military Personnel;additive manufacturing and Sustainability: The Mediating Role of Supply Chain;leverage of Metal 3D Printing Technology in the Automotive Industry;digital Twins of Hybrid Additive and Subtractive manufacturing systems–A Review;exploring Sustainable manufacturing: A Comprehensive Review of Literature and Practices;performance Analysis of 3D Printed Impellers for Portable Vacuum Cleaner;3D Printed Electronics: Role of Materials and Processes;electrochemical Micromachining: A Review on Principles, Processes, and Applications;friction and Wear Characteristics of Engine Oil Through Four-Ball Tester;recent Trends in 4th Industrial Revolution for A Sustainable Future–A Review;AI Control of EMG Sensor data for 3D Printed Prosthesis Hand.

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international conference on Production and Industrial engineering, CPIE 2023

International Conference on Production and Industrial Engine...

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international conference on Production and Industrial engineering, CPIE 2023

ISBN: (纸本)9789819960934

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Development of stationary expert systems for improving energy efficiency in manufacturing 17

Development of stationary expert systems for improving energ...

引用

17th CIRP conference on Intelligent Computation in manufacturing engineering, CIRP ICME 2023

作者： Ioshchikhes, Borys Weigold, Matthias Technical University of Darmstadt Institute for Production Management Otto-Berndt-Str. 2 Darmstadt64287 Germany

Increasing energy prices as well as the transition towards the goal of climate neutrality are major challenges for manufacturing companies. Expert systems offer the possibility to address these challenges by aggregating expert knowledge, processing energy data and thus identifying energy efficiency potentials to deduce energy efficiency measures. In this paper, approaches for mobile preliminary and stationary detailed energy analysis are compared. Additionally, a systematic development method for stationary expert systems is presented. The proposed method is demonstrated through the implementation for a chamber cleaning machine to quantify energy efficiency potentials. © 2024 Elsevier B.V.. All rights reserved.

关键词： Smart manufacturing

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Distributed Cloud Simulation Architecture Combining Virtual and Real Environment

Distributed Cloud Simulation Architecture Combining Virtual ...

引用

2024 international conference on Interactive Intelligent systems and Techniques, IIST 2024

作者： Hu, Jiangang Mao, Yukun Li, Junjie Ye, Mengya Chen, Li Wan, Zhangbo Peng, Yuhuai Zhiyuan Research Institute Strategic Research Department Hangzhou China Northeastern University School of Computer Science and Engineering Shenyang China

ISBN: (纸本)9798350374421

With the deep integration of advanced manufacturing technology and the new generation of information technology, human-machine collaborative intelligent manufacturing has emerged as the core technology driving the development of the industrial sector. However, the human-machine collaborative intelligent manufacturing equipment exhibits high complexity and uncertainty in faults. The data silos that exist between equipment, personnel, systems, and platforms contribute to decreased productivity. Furthermore, the prolonged and costly technician training cycles add further obstacles. Therefore, a virtual-real integrated cloud simulation architecture is constructed using LVC (Live, Virtual, Constructive) simulation technology combined with a distributed computing framework. This architecture aims to achieve intelligent human-machine collaboration and real-time virtual-real interaction in industrial production. Real time monitoring of equipment and the entire production process through cloud simulation technology to optimize production processes and efficiency. The architecture supports simulation services such as intelligent task scheduling, human-machine collaborative manufacturing, adaptive flexible manufacturing, and production equipment precision and performance evaluation. The current architecture has just been proposed as a theoretical innovation for intelligent manufacturing cloud simulation solutions, but it has yet to be put into practice. © 2024 IEEE.

关键词： Smart manufacturing

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international conference on Production and Industrial engineering, CPIE 2023

International Conference on Production and Industrial Engine...

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international conference on Production and Industrial engineering, CPIE 2023

ISBN: (纸本)9789819966004

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The Implementation of Preventive Maintenance in a Product-Service System (PSS) Business Model 32nd

The Implementation of Preventive Maintenance in a Product-Se...

引用

32nd international conference on Flexible Automation and Intelligent manufacturing

作者： Kuroki, Alisson Cardoso, Valdir H. Oliveira Neto, Geraldo C. Amorim, Marlene FEI Univ BR-01525000 Sao Paulo SP Brazil Aveiro Univ P-3810193 Aveiro Portugal

ISBN: (纸本)9783031381645;9783031381652

The commoditization initiatives triggered inmanufacturing companies the concern with the rigidity of their offers, and the appeal of their offers to their customers, leading to servitization strategies. This research highlights the importance of preventive maintenance, and builds on the extraction and processing of data for a PSS business model. data from https://*** was used to analyze the performance of a production process with three products with differentiated levels of quality. data analysis was of exploratory nature using descriptive statistics and Pearson's correlation through, using Python via Google Collaboratory. The main failures were exposed allowing the elaboration of a preventive maintenance plan. Through multivariate statistical analyses, we demonstrate that in a PSS business model, having machine suppliers at your disposal that combine the sale of the item with the provision of predictive maintenance services is a differential that will help to make assertive a preventive d skillful decision, avoiding maintenance unnecessary and waste of time.

关键词： Business Intelligence Big data Analytics Servitization Fault Identification

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From Pixels to Payouts -A Satellite Based Solution

From Pixels to Payouts -A Satellite Based Solution

引用

2024 international conference on knowledge engineering and Communication systems, ICKECS 2024

作者： Deepthi, R.S.S.V. Priya, A Leela Revanth, D. Ajay, K. Madhavi, M. Velagapudi Ramakrishna Siddhartha Engineering College Depratment of Artificial Intelligence and Data Science Vijayawada India Velagapudi Ramakrishna Siddhartha Engineering College Depratment of Computer Science and Engineering Vijayawada India

ISBN: (纸本)9798350359688

The Pradhan Mantri Fasal Bima Yojana (PMFBY) stands as a crucial initiative for farmers' protection, yet grapples with challenges like delayed claims, inaccurate loss assessments, and uneven aid distribution [1]. This project proposes an innovative solution that addresses these issues by introducing a precision agriculture and risk management framework. The current crop insurance policies rely on an area-based approach and limited weather indices, resulting in an inadequate assessment of individual crop health and losses [2]. This shortfall leads to unjust aid distribution, leaving deserving farmers underserved [3]. The proposed solution advocates for a paradigm shift, incorporating a personalized and technology-driven approach. By integrating remote sensing technology, machine learning algorithms, and comprehensive data analysis, the system optimizes insurance resource allocation, assessing crop and regional risk profiles with precision. Furthermore, the project implements advanced image processing, segmentation, and machine learning models, such as SVM and CNN, for crop detection and yield estimation. The Google Maps API enhances decision support through geo-mapping, providing a transparent and data-driven basis for aid distribution. This innovative approach fosters equity, transparency, and active farmer participation, overcoming the limitations of existing methodologies. With a focus on precision, transparency, and equity, the proposed solution aims to revolutionize the effectiveness of PMFBY, ensuring accurate assessment and targeted aid distribution for farmers facing crop stress and losses. © 2024 IEEE.

关键词： Risk management

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Research on the Construction of knowledge QA System Driven by Large Language Model: One Case Study of Power Transformer Domain 7

Research on the Construction of Knowledge QA System Driven b...

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7th international conference on data Science and Information Technology, DSIT 2024

作者： Xu, Hao Kang, Zhenyuan Zhang, Yan Jin, Zhenqiang Wang, Mulan Ge, Linlin Lu, Haihua Management Nanjing University School of Management Engineering Nanjing Institute of Technology School of Information Nanjing China Nanjing Institute of Technology School of Electrical Power Engineering Shen Guorong College Nanjing China Nanjing Institute of Technology School of Management Engineering Nanjing China Jiangsu Power Transmission & Transformation Co. Ltd Nanjing China Nanjing Institute of Technology School of Industrial Center Nanjing China

ISBN: (纸本)9798350384093

The QA system can provide various professionals with fast and accurate knowledge support, significantly improving work efficiency. The introduction of LLMs has further enhanced the accuracy and efficiency of QA systems. A QA system based on LLMs for power transformers can effectively improve the efficiency of fault diagnosis and the resolution of technical issues in the power transformer domain. This study first proposes an automatic dataset construction method for QA based on LLMs, through which a QA dataset of basic knowledge about power transformers is obtained. This dataset then performs low-rank adaptive fine-tuning on the LLM. Subsequently, an external knowledge base covering fundamental knowledge and fault cases of power transformers is built. Finally, with the aid of prompt texts, knowledge responses were generated by RAG in combination with the fine-tuned LLM. Experimental results show that compared with the QA systems driven by general LLMs, the method proposed in this paper generates more concise and professional responses, thus promoting, to some extent, the application of LLMs in the power domain. © 2024 IEEE.

关键词： Distribution transformers

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