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

共 37040 条记录，以下是171-180 订阅

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Intelligent manufacturing system based on AI parameter modification 3

Intelligent manufacturing system based on AI parameter modif...

引用

3rd international conference on Mechatronics and Mechanical engineering, ICMME 2024

作者： Qiu, Xiongwei Shi, Lianzhi Ren, Jiale R&D Department Zhejiang Yixiong Intelligent Technology Co. Ltd. Hangzhou China R&D Department Hangzhou Ptop Information Technology Co. Ltd. Hangzhou China

ISBN: (纸本)9781510681651

The traditional manufacturing system cannot effectively coordinate and balance control over multiple functional segments in the design process. This not only results in certain errors in the connection between functional segments, but also leads to lower precision in welding and assembly of mechanical components, thereby affecting the production yield of specific manufactured objects. Based on the above problems, an intelligent manufacturing system based on AI parameter correction is proposed. By establishing a hardware configuration for AI data collection and redesigning the hardware framework, real-time data collection for different functional segments can be achieved. The key point is to implement parameter correction during the handover process between functional segments through AI analysis and calculation of the data, ensuring the manufacturing system's yield rate. This method is applied to shipbuilding, and the effectiveness and superiority of the proposed design system are demonstrated through a comparison of yield rates with traditional manufacturing systems. © 2024 SPIE.

关键词： Smart manufacturing

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data analysis of three-point bending deformation based on finite element method 3

Data analysis of three-point bending deformation based on fi...

引用

3rd international conference on Advanced manufacturing Technology and manufacturing systems, ICAMTMS 2024

作者： Liang, Meiqin Mao, Xing Liu, Shuai Peng, Fei College of Automation Engineering Beijing Polytechnic Beijing100176 China Institute of Engineering Technology University of Science and Technology Beijing Beijing China

ISBN: (纸本)9781510681804

The three-point bending experiment is widely used to evaluate the mechanical properties of materials under bending loads. However, traditional testing methods have limitations in terms of data acquisition. To overcome these challenges, this study aims to develop an accurate finite element model of the three-point bending test using Abaqus software. The model is utilized to data analyze bending specimens made of aluminum alloy and carbon steel. The simulations provide stress/strain distributions that are not easily obtained through experiments, and the displacements of nodes at different locations are statistically calculated to accurately capture bending deformations. The flexibility of the model allows for adjustments in specimen parameters to explore the bending resistance of different materials, as well as modifications in specimen dimensions to provide a comprehensive evaluation of mechanical properties for various cross-sections under bending loading. © 2024 SPIE.

关键词： Aluminum alloys

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A vibration based self-learning approach for machine condition monitoring 31

A vibration based self-learning approach for machine conditi...

引用

31st international conference on Noise and Vibration engineering, ISMA 2024 and 10th international conference on Uncertainty in Structural Dynamics, USD 2024

作者： De Fabritiis, F. Gryllias, K. KU Leuven Department of Mechanical Engineering Celestijnenlaan 300 HeverleeB-3001 Belgium Flanders Make@KU Leuven Celestijnenlaan 300 HeverleeB-3001 Belgium Leuven.AI - KU Leuven Institute for AI LeuvenB-3000 Belgium

ISBN: (纸本)9789082893175

Labeling data in the industry is frequently a resource-intensive and time-consuming process and extracting relevant features from real-world data becomes non-trivial when dealing with complex systems that may operate in diverse contexts. data-driven approaches that can learn from unlabeled data are essential to enhance the robustness and trustworthiness of such systems in practical applications. With this intent, self-supervised learning, leveraging on domain-knowledge to learn relevant features from the data, is proposed to overcome the limit of classical supervised approaches. In this paper a methodology based on a self-learning approach is presented for possible application in condition monitoring. The methodology is tested on the IMS dataset provided by the Intelligent Maintenance systems, University of Cincinnati, for early fault detection in bearings. The results suggest the possibility of future developments for real-world applications. © 2024 Proceedings of ISMA 2024 - international conference on Noise and Vibration engineering and USD 2024 - international conference on Uncertainty in Structural Dynamics. All rights reserved.

关键词： Self-supervised learning

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Research on OTA-based automotive bootloader remote data update technology 3

Research on OTA-based automotive bootloader remote data upda...

引用

3rd international conference on Advanced manufacturing Technology and manufacturing systems, ICAMTMS 2024

作者： Niu, Jigao Wu, Aiguo Liu, Mengmeng Xu, Chunhua Zhongyuan University of Technology School of Mechanical and Electrical Engineering Xinzheng Zhengzhou China Zhengzhou Vocational College of Science and Technology School of Mechanical and Electrical Engineering Xinzheng Zhengzhou China

ISBN: (纸本)9781510681804

To enhance the convenience and efficiency of automotive software upgrades, a method utilizing Over-the-Air (OTA) technology is proposed. In this approach, the Bootloader system establishes a wireless connection to Alibaba Cloud, transmitting firmware packages earmarked for upgrade to the cloud. The cloud then facilitates the download to the gateway board, which, through its Lora module, transmits the firmware to multiple sub-devices, enabling a bulk remote upgrade process. Taking the BCM automotive controller core board as an example, the relay transmission feature of Lora is utilized to extend the transmission range, while the built-in AES encryption algorithm ensures the security of the transmitted firmware packages. Experimental results demonstrate that this remote data update technology significantly accelerates the rate of automotive software updates, reducing the workload and staff requirements in the process. Moreover, this remote data update technology is equally applicable to address status detection issues in body control modules. © 2024 SPIE.

关键词： Firmware

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FAIRlead: A Conceptual Framework for a Model Driven Software Development Approach in the Field of FAIR data Management 16

FAIRlead: A Conceptual Framework for a Model Driven Software...

引用

16th international conference on knowledge Management and Information systems, KMIS 2024 as part of 16th international Joint conference on knowledge Discovery, knowledge engineering and knowledge Management, IC3K 2024

作者： Schmidt, Andreas Koubaa, Mohamed Anis Liu, Nan Schmurr, Philipp Stucky, Karl-Uwe Süß, Wolfgang Karlsruhe Germany Department of Computer Science and Business Information Systems Karlsruhe University of Applied Sciences Karlsruhe Germany

ISBN: (纸本)9789897587160

The publication of scientific results together with the underlying experiments is an important source of further research. In 2016, the "FAIR Guiding Principles for scientific data management and stewardship" were published, in which the authors postulate a series of guidelines for improving the (F)indability, (A)ccessibility, (I)nteroperability and (R)eusability of digital information (FAIR). The point (I)nteroperability deals with the prerequisites for the reusability of digital objects. The central point here is the need to have a common understanding of the meaning of digital objects. This understanding is provided by formal languages of knowledge representation (ontologies), which describe the actual data. These descriptions of data are also known as metadata. As part of our current work at the Institute for Automation and Applied Computer Science (IAI) at KIT, we are implementing novel concepts and technologies for the sustainable handling of research data using high-quality metadata. As part of this work, we plan to develop a software tool that can be used to enrich data with suitable metadata and thus automate the process of making research results available. A key requirement is that the tool must be independent of the underlying domain. In order to be able to deal with data from any domain, we have opted for a model-driven approach in which an ontology, and possibly other platform-specific information, are input for a software generator, which then generates an (interactive) tool for specifying the metadata and linking it to the data itself. The generated tool includes the complete software stack, starting with a user interface, programmatic APIs for connecting additional application logic, and a persistence component. How these individual layers are realized is not specified, but defined by the mapping rules of the software generator, which also opens up the possibility of generating and evaluating different variants of the software. © 2024 by SCITEPRESS

关键词： Ontology

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Web Scraping Using Beautiful Soup

Web Scraping Using Beautiful Soup

引用

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

作者： Pant, Sakshi Yadav, Narinder Milan Sharma, Monnie Bedi, Yash Raturi, Anshuman Chandigarh University Mohali India

ISBN: (纸本)9798350359688

This paper explores the power of Beautiful Soup, a Python library, for web scraping. We delve into the advantages of web scraping for data acquisition, highlighting its limitations and ethical considerations. Subsequently, we dissect the core functionalities of Beautiful Soup, showcasing its effectiveness in parsing HTML content, identifying elements, and extracting desired information. Through practical case studies involving news data mining, product information extraction, and academic research data collection, we demonstrate the versatility and efficiency of Beautiful Soup. We compare it to other scraping tools and evaluate its strengths and weaknesses. Finally, we conclude by summarizing our findings, discussing the future of web scraping, and suggesting potential improvements for Beautiful Soup. © 2024 IEEE.

关键词： data collection

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data-model driven nonlinear dynamic modeling method for rolling linear guideway 3

Data-model driven nonlinear dynamic modeling method for roll...

引用

3rd international conference on Advanced manufacturing Technology and manufacturing systems, ICAMTMS 2024

作者： Guo, Song School of Computer Science and Engineering Shenyang Jianzhu University Shenyang China

ISBN: (纸本)9781510681804

The rolling linear guideway is a key component of the reciprocating linear motion system. Modeling the dynamic behavior of rolling linear guide is of great significance for analyzing the motion accuracy. The physical method was presented by Li et al. However, there is a obvious error between the theoretical solution and the experimental results. To reduce the error, the data-model driven modeling method is proposed for describing the nonlinear dynamic behavior of the rolling linear guideway in this work. The parameters in the physical model are identified by the intelligent optimization algorithm (in this work, Particle Swarm Optimization are employed) and experimental data. The objective function is to minimize the absolute error between the theoretical acceleration and the corresponding experimental one. The constraint condition is to meet the assembly requirements of the rolling linear guide. The experimental results shown that the solution accuracy of the proposed method is almost 100% higher than that of the theoretical solution method. © 2024 SPIE.

关键词： Runge Kutta methods

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Optimizing data Center Load Balancing in Cloud Computing with SDN Controller

Optimizing Data Center Load Balancing in Cloud Computing wit...

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

作者： Girish, B.G. Subramanaya, Bala Rohan, S. Nandu Priya, V. Sjcit Dept of Cse Chikkaballapur India

ISBN: (纸本)9798350359688

In the era of modern cloud computing, data centers play a pivotal role in supporting the ever-increasing demand for computational resources. To ensure optimal resource utilization and seamless service delivery, effective network load balancing within these data centers is imperative. In this we introduces a novel approach to network load balancing by leveraging Software-Defined Networking (SDN) controllers, tailored specifically for cloud computing data centers. This Project takes the cloud data center as the research object, provides the overall framework of network load balancing based on SDN controller. By analyzing the traffic characteristics of the data center network, we implement elephant flows in combination with SDN and link load evaluation algorithm to reserve bandwidth for other flows. © 2024 IEEE.

关键词： Cloud platforms

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The Research and Application of Platform on Mining Equipment Supply Chain Service 14

The Research and Application of Platform on Mining Equipment...

引用

14th international conference on Logistics and systems engineering

作者： Zhu, Qin CCTEG Shanghai Co. Ltd Shanghai200030 China

ISBN: (纸本)9798331314347

Addressing the issues of slow information technology development, low data integration, and delayed supply chain feedback in the design selection, processing and manufacturing, safety production, and monitoring and traceability aspects of the mining equipment manufacturing industry, we have proposed a platform on mining equipment supply chain service. This platform encapsulates and stores relevant software and hardware resources from the design to the application stages of distributed mining equipment, utilizing resource virtualization and dynamic construction technologies to agilely respond to user needs. It also employs structured documents to address the standardization of message transmission processes. After being built and tested in a real-world environment, the results indicate that the platform can effectively improve the resource utilization rate of mining equipment, enable information sharing and functional reorganization within the connected domain, promptly feedback issues encountered in practical applications for improving defects in product design, testing, and manufacturing processes, further strengthen the safety supervision of mining equipment, and lay the foundation for intelligent manufacturing and stable supply of mining equipment. © (2025) by Aussino Academic Publishing House All rights reserved.

关键词： Smart manufacturing

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EXTRACTING DESIGN knowledge FROM OPTIMIZATION data: APPLICATION TO MULTI-SPLIT THERMAL MANAGEMENT SYSTEM CONFIGURATION

EXTRACTING DESIGN KNOWLEDGE FROM OPTIMIZATION DATA: APPLICAT...

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ASME 2024 international Design engineering Technical conferences and Computers and Information in engineering conference, IDETC-CIE 2024

作者： Bayat, Saeid Shahmansouri, Nastaran Peddada, Satya R.T. Tessier, Alex Butscher, Adrian Allison, James T. Department of Industrial and Enterprise Systems Engineering University of Illinois at Urbana-Champaign UrbanaIL United States Autodesk Research 661 University Ave Toronto Canada

ISBN: (纸本)9780791888377

As engineering systems become more complex, the traditional sources of design knowledge face limits in the rate and complexity of design knowledge generation. Additional sources of knowledge are needed to guide future design efforts, especially for unprecedented engineering systems that have no design heritage. One promising avenue lies in the analysis of design optimization data, which has the potential to offer valuable insights into unprecedented system design, and to break free from incremental improvements over heritage designs. This paper presents a step toward extracting knowledge from design optimization data. The resulting design knowledge can be used as a basis for successfully synthesizing engineering system configurations that are more complex than those the knowledge was derived from. These methods are studied here using the combined system topology and optimal control design of multi-split fluid-based thermal management systems. This knowledge generation approach offers several advantages over traditional strategies, including applicability in cases where there is no design heritage and the ability to provide normative guidance as opposed to descriptive (i.e., how should systems be designed vs. how have they been designed). Four significant case studies with varying levels of complexity are presented that demonstrate the effectiveness of using knowledge extracted from design optimization data in enhancing the design of complex thermal management systems. Our results show that the knowledge extracted in this way provides a good basis for more general design of complex thermal management systems. It is shown that the objective function value of the estimated optimal configuration closely approximates the true optimal configuration with less than 1 percent error, achieved using basic features based on the system heat loads without involving the corresponding optimal open loop control (OLOC) features. This eliminates the need to solve the OLOC problem, lea

关键词： Open loop control

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