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

共 36972 条记录，以下是181-190 订阅

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Development of a Digital Thread for Orchestrating data Along the Product Lifecycle for Large-Part and High-Precision manufacturing 32nd

Development of a Digital Thread for Orchestrating Data Along...

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32nd international conference on Flexible Automation and Intelligent manufacturing

作者： Vidal, Felix Alonso, Lucia de Luca, Patrick Duplessis-Kergomard, Yann Castillo, Roberto AIMEN Technol Ctr O Porrino 36400 Spain ESI Grp 25 Rue Marcel Issartier F-33700 Merignac France ATOS Spain SA Madrid Spain

ISBN: (纸本)9783031382406;9783031382413

manufacturing of large components is a complex and challenging process characterized by high customization requirements, involving a large variety of subassemblies that must be manufactured and assembled involving multistage manufacturing processes. Moreover, product quality and production efficiency are key elements to ensure. Therefore, an integrated framework capable of ensuring an efficient manufacturing from the initial design phase is needed. The goal is to obtain the continuous evolution of the large component being manufactured by linking Product, Process and Resources data. In this regard, this paper presents a methodology for implementing a data-driven digital infrastructure supporting data exchange in a heterogeneous engineering landscape between engineering, production, quality and management. As a result, a digital platform integrating data models, digital twins and data-driven algorithms have been implemented enabling the application of feedforward control strategies as well as optimization loops to enable a more precise, efficient and sustainable manufacturing.

关键词： Digital Pipeline Control Orchestration Technologies Hierarchical and modular digital thread

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engineering Design and Prototyping Methodology in Complex Environments: The In-Bore Welding Tool 4th

Engineering Design and Prototyping Methodology in Complex En...

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4th international conference of the Italian Association of Design Methods and Tools for Industrial engineering

作者： Claps, Vincenzo Di Giacomo, Antonio Salvato, Rocco Sorgente, Donato Mozzillo, Rocco Basilicata Univ CREATE Engn Sch Campus Macchia Romana Potenza Italy Politecn Bari Dept Mech Math & Management Via Orabona 4 I-70125 Bari Italy

ISBN: (纸本)9783031765964;9783031765971

The engineering process is a critical area in the design and development of devices for scientific, industrial and technological applications. This process involves the conceptualization, design, prototyping and production of equipment suitable for specific operations or functions. The main objectives of equipment engineering are to optimize the performance, efficiency of functionality, safety and reliability of devices, as well as to reduce costs and production time. The application of advanced engineering methodologies, such as Computer-Aided Design (CAD), systems analysis and advanced manufacturing techniques such as Additive manufacturing (AM), allows the creation of high specialized and high performance equipment to satisfy the specific needs of modern industries. In the framework of advanced technologies such as nuclear fusion, equipment engineering plays a key role in solving complex challenges and developing innovative solutions involving various aspects of engineering knowledge. This paper presents the design and prototyping process of a tool for in-bore welding of pipes used in fusion nuclear power plants, called In-Bore Welding Tool (IBWT).

关键词： Design Methods Additive manufacturing engineering Design CAD Prototyping

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To Solve the "Last Kilometer" Problem in Aerospace Unit knowledge engineering Based on Intelligent Search Engine 2

To Solve the "Last Kilometer" Problem in Aerospace Unit Know...

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2nd international conference on Intelligent Communication and Networking, ICN 2024

作者： Ji, Long Ji, Wei Zhou, Anji Yao, Meng Xing, Chao Fei, Di Beijing Institute of Spacecraft System Engineering Beijing China

ISBN: (纸本)9798331519162

In order to solve the problem that all kinds of knowledge data of the aerospace unit are scattered in different business systems, improve the accuracy and intelligence of information retrieval as well as reduce the cost of repeated construction of search module in different systems, the paper puts forward a knowledge acquisition method based on intelligent search engine. In terms of the intelligent search engine, it realizes the multi-source management of the common knowledge through integrating with a plurality of business systems, which helps to provide a unified retrieval channel for users;Convenient acquisition and use of knowledge in various scenarios is achieved, such as writing documents and consulting documents, by building web search service and developing functions of input client including instant input search and word-drag search;by introducing a semantic understanding model, designing an intelligent user query sentence understanding/recall/sorting algorithm, supporting search strategy adjustment and optimization based on user feedback and improving the recall rate and the precision of the search task on the domain data, the problem of "last kilometer" knowledge acquisition and utilization can be solved. © 2024 IEEE.

关键词： Search engines

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Performance of MIMO-GFDM scheme for Future Wireless Communications

Performance of MIMO-GFDM scheme for Future Wireless Communic...

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

作者： Kumar, R. Anil Kumar, R. Prakash Patchala, Sarala Sreenivasulu, U. Aditya College of Engineering and Technology Electronics and Communication Engineering Surampalem India Cvr College of Engineering Electronics and Communication Engineering Hyderabad India Srkr Engineering College Electronics and Communication Engineering Bhimavaram India Kkr & Ksr Institute of Technology and Sciences Electronics and Communication Engineering Guntur India

ISBN: (纸本)9798350359688

Wireless Technology became more popular from couple of decades. Modern Technologies such as Mobile Broad Band Communications, Ultra Low Latency Communications and Internet of Things purely depends on Wireless technologies. The use of set of antennas at User Equipment and/or Base Station improves the User Capacity, Bit Error Rate, Spectral Efficiency and data Rates. Current research on Generalized Frequency Division Multiplexing Technique combined with Multi-Input Multi-Output (MIMO systems) gives good resource allocation and better signal strengths over the existing Orthogonal Frequency Division Multiplexing (OFDM). This paper explains the performance of MIMO-GFDM in an ultradense multipath environment with affordable complexity by considering Uplink scenario at User Equipment (UE). The simulation results such as Spectral Efficiency, User Capacity, Bit Error Rate and data rates are calculated for different set of antenna systems. © 2024 IEEE.

关键词： Orthogonal frequency division multiplexing

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Semantic knowledge Representation in Asset Administration Shells: Empowering manufacturing Utilization 33rd

Semantic Knowledge Representation in Asset Administration Sh...

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33rd international conference on Flexible Automation and Intelligent manufacturing

作者： Elshafei, Basem Martinez-Arellano, Giovanna Chaplin, Jack C. Sanderson, David Ratchev, Svetan Univ Nottingham Inst Adv Mfg Nottingham NG7 2RD England

ISBN: (纸本)9783031744815;9783031744822

Within the context of Industry 4.0 and the Reference Architecture Model Industrie 4.0, the Asset Administration Shell (AAS) framework has emerged as a critical component for implementing Digital Twins that facilitate a seamless data exchange within a manufacturing ecosystem. The concept enables asset communication across various application domains, organizing the design and interaction amongst manufacturing components while capturing key information relating to assets such as operational parameters, intrinsic properties, and technical functionalities. Each category of information is stored within the AAS in a structure called a sub-model, while specific properties are stored as sub-model elements. Moreover, the literature presents a gap in post-processing the information contained within the sub-models to generate data-driven decisions and the bidirectional data exchange with the AAS. Additionally, the developing concept behind AAS requires demonstration with manufacturing cases of what can be done with the information in the submodels of the AAS. This research explores the practical implementation of AAS in a manufacturing context and the tools used in their development. An approach is developed to map a semantic ontology representation from the AAS structure. The semantic structure of the information enables querying and reasoning about the data, which contributes to better understanding among diverse manufacturing components, enabling enhanced monitoring and decision-making. The use case utilizes parameter data from the AAS to estimate a key performance Indicator, Overall Equipment Effectiveness (OEE), and stores the value back in the AAS. Utilizing this approach contributes to optimizing manufacturing efficiency and productivity within manufacturing production.

关键词： Asset Administration Shell Semantic Ontology Digital Twin Key Performance Indicator

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Key Technologies and Methods of Intelligent Quality Management in Electronic Product manufacturing Process 18

Key Technologies and Methods of Intelligent Quality Manageme...

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18th international conference on Intelligent systems and knowledge engineering, ISKE 2023

作者： Su, Enkai Song, Yuhong Getech Co. Ltd Guangdong Shenzhen China School of Smart Manufacturing Shunde Polytechnic Guangdong Foshan China

ISBN: (纸本)9798350318401

Electronic products are essential core cells or components in multiple industries such as automobiles. With industry transformation or upgrading, as well as high-quality market demand, higher requirements have been put forward for the manufacturing process of electronic products. Conduct research on the implementation of intelligent quality management in the electronic product manufacturing process, and explore the joint application of 5G (the fifth generation communication technology), industrial IOT (internet of things), QMS(quality management system), AI (artificial intelligence) and other technologies to transform and upgrade the quality management system of the electronic product manufacturing process. The research results would be used for intelligent quality management in the manufacturing process of automotive electronic products. © 2023 IEEE.

关键词： Internet of things

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Artificial Intelligence Models for Overall Equipment Effectiveness Prediction: A Case Study in an Assembly manufacturing Company 7

Artificial Intelligence Models for Overall Equipment Effecti...

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7th international conference on Green Technology and Sustainable Development, GTSD 2024

作者： Nguyen, Van Trieu Vy Quynh Le, Song Thanh Nguyen, Duc Duy Department of Industrial Systems Engineering 268 Ly Thuong Kiet Street District 10 Ho Chi Minh City Viet Nam Vietnam National University Ho Chi Minh City Linh Trung Ward Ho Chi Minh City Thu Duc City Viet Nam Department of Textile and Garment Engineering 268 Ly Thuong Kiet Street District 10 Ho Chi Minh City Viet Nam

ISBN: (纸本)9798350386073

Overall Equipment Effectiveness (OEE) stands as a key performance metric widely adopted in the manufacturing industry, aiding in enhancing productivity. This metric offers a comprehensive overview to higher management, enabling them to identify equipment-related losses. With the advancements in Industry 4.0 technologies, the manufacturing Execution System facilitates real-time data collection, enhancing production efficiency and reducing manufacturing costs. However, the real-time depiction of OEE often fails to provide decision-makers with timely insights to conduct their tasks effectively. This study formulated machine learning models to tackle this challenge by forecasting the OEE for the upcoming working shift. Firstly, the historical dataset encompasses 31 features collected and processed to estimate the OEE value. Then, prominent machine learning models were utilized as prediction models: Linear Regression, Support Vector Regression, Random Forest, Extreme Gradient Boosting, and Artificial Neural Networks. The results show that the Extreme Gradient Boosting performs well for the OEE prediction with accuracy in training higher than 99% and testing nearly 90%. Our study illustrates an actionable knowledge-discovery process using a real-world data mining approach for the manufacturing industry, potentially applicable to other sectors. © 2024 IEEE.

关键词： Smart manufacturing

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Multi-Privacy Level Encryption Technique for Secure Cloud-Based data Repositories

Multi-Privacy Level Encryption Technique for Secure Cloud-Ba...

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

作者： Sunil Kumar Aithal, S. Rajashree Nmam Institute of Technology Department of Computer Science and Engineering Nitte India

ISBN: (纸本)9798350359688

Cloud security encompasses the deployment of advanced technologies, methodologies, and programming to safeguard cloud-based applications, ensuring their protection against potential threats and vulnerabilities. Cloud computing is an environment for providing services namely platform, software, hardware and infrastructure on user demand posing a serious challenge for enabling high secure digital data cloud repository. To keep sensitive information safe in cloud computing, we must use strong techniques to protect it from external attackers. In today's world, creating a security system that will last a lifetime is extremely difficult, as attackers gain more ways to access data as time progresses. Hence, we create a web based application that uses several encryption levels, including the DNA algorithm, Vigenere Cipher, and Advanced Encryption Standard (AES) algorithm to achieve greater confidentiality before loading a digital data onto cloud storage. © 2024 IEEE.

关键词： Cloud security

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Lean manufacturing vs Coaching Alliance in Engagement Promotion: An Employee Suggestion System Prototype 32nd

Lean Manufacturing vs Coaching Alliance in Engagement Promot...

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32nd international conference on Flexible Automation and Intelligent manufacturing

作者： Salvadorinho, Juliana Bastos, Tiago Pintor, Paulo Teixeira, Leonor Univ Aveiro Dept Econ Management Ind Engn & Tourism DEGEIT Aveiro Portugal Univ Aveiro Dept Elect Telecommun & Informat DETI Aveiro Portugal Univ Aveiro Inst Elect & Informat Engn Aveiro IEETA Intelligent Syst Associate Lab LASI Aveiro Portugal

ISBN: (纸本)9783031381645;9783031381652

Industry 4.0 is being pushed by Industry 5.0 to put the human factor at the centre of technological innovation by fostering engagement practices, namely through participatory design and communication and knowledge sharing. Kaizen Teian, or suggestion systems, are tools that empower employees with voice behaviour, giving them the possibility to foster innovation in the organisation by fostering in them this feeling of involvement and/or belonging. This paper brings a prototype of a suggestion system, co-created with employees from three multi-sector companies that integrates the PDCA cycle with the Disney strategy, a Neuro-linguistic Programming technique used in Coaching. The Disney strategy aims at supporting innovation through a process for the realisation of ideas, giving them a mature character. This system fosters two of the predictors of work engagement, which are participative design and knowledge sharing, and brings transparency to suggestions, enabling the employee to monitor them. The promotion of sustainable innovation through the Disney strategy, the improvement of labour engagement and the sharing of knowledge, are all enhancing factors of organisational competitive advantage, not only by retaining the workforce, but also by preserving organisational knowledge. This is a digital tool adapted to the current challenging technological context, where Lean must be preserved and coaching tools applied.

关键词： Workforce Engagement Industry 4.0 Lean manufacturing

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

16th International Conference on Knowledge Management and In...

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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

ISBN: (纸本)9789897587160

The proceedings contain 123 papers. The topics discussed include: supervised machine learning models and schema matching techniques for ontology alignment;framework for a knowledge-based course recommender system focused on IT career needs;optimization of methods for querying formal ontologies in natural language using a neural network;personalized asthma recommendation system: leveraging predictive analysis and semantic ontology-based knowledge graph;elementary multiperspective material ontology: leveraging perspectives via a showcase of EMMO-based domain and application ontologies;positive-unlabeled learning using pairwise similarity a parametric minimum cuts;efficient visualization of association rule mining using the rules;predicting post myocardial infarction complication: a study dual-modality and imbalanced flow cytometry data;a model for designing personalized and context-aware nudges;automatic transcription systems: a game changer for court hearings;scientific claim verification with fine-tuned NLI models;and assessing the use of online platforms in sharing tacit knowledge in innovation networks.

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