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Interdisciplinary Production Risk exploration: A Grounded Approach to Integrate data- and Knowledge-Driven Analytics 56

Interdisciplinary Production Risk Exploration: A Grounded Ap...

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56th CIRP International conference on Manufacturing Systems, CIRP CMS 2023

作者： Hoffmann, David Nowacki, Natalie Biffl, Stefan Kiesling, Elmar Meixner, Kristof Lüder, Arndt Otto-von-Guericke University Magdeburg Universitätsplatz 2 Magdeburg39106 Germany Christian Doppler Laboratory SQI TU Wien Information Systems Engineering Favoritenstraße 9-11/194-1 Vienna1040 Austria Comet Center for Digital Production Seestadtstr. 2 Vienna1220 Austria WU Wien Welthandelsplatz 1 Vienna1020 Austria Volkswagen AG Volkswagenwerk Wolfsburg38440 Germany

In the age of disruption, rapidly evolving conditions in manufacturing necessitate effective capabilities to identify and manage production risks. Some of the most challenging risks in this context emerge from interdisciplinary issues that cannot easily be addressed by methods and tools within a single discipline, such as mechanical, electrical, or automation engineering. To enable comprehensive analysis of such interdisciplinary production risks, we propose Interdisciplinary Production Risk exploration (IPRE) as a structured, data-driven methodology. IPRE integrates data with fragmented knowledge of production engineers, process experts, and data analysts across domains to identify and characterize production risks to guide data-analytic processes. We evaluate the approach in a case study on a hairpin production process at volkswagen AG. The study results show that validated hypotheses can effectively focus data analysis on the most critical quality factors and thereby significantly reduce the number of quality criteria that need to be analyzed. Furthermore, the study shows how IPRE can be effectively integrated into the production process. © 2023 The Authors. Published by Elsevier B.v. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the 56th CIRP International conference on Manufacturing Systems 2023.

关键词： data mining Knowledge graph Product-Process-Resource (PPR) Risk analysis

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Fog Computing in IoT: Architecture and Applications 9

Fog Computing in IoT: Architecture and Applications

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9th International conference on Science, Technology, Engineering and Mathematics, ICONSTEM 2024

作者： Agrawal, Anurag vijay Shashi Gowridurga, A. Suresh Balakrishnan, T. Shaikh, Anwar Ahamed Kalaipriya, v. J. P. Institute of Engineering And Technology Department of Electronics And Communication Engineering Uttar Pradesh Meerut250001 India Ccs University Department of Computer Application Meerut250004 India Velammal Institute of Technology Department of Computer Science And Engineering Tamil Nadu 601204 India Saveetha School of Engineering Saveetha Institute of Medical And Technical Sciences Department of Computer Science And Engineering Tamil Nadu Thandalam602105 India KoneruLakshmaiah Education Foundation Department of Computer Science And Engineering Andhra Pradesh Vaddeswaram522502 India Rmk College of Engineering And Technology Department of Computer Science And Engineering Tamil Nadu Puduvoyal601206 India

ISBN: (纸本)9798350365092

This exploration paper explores the paradigm of Fog Computing as a transformative armature in the Internet of effects(IoT) geography. Fog Computing represents a decentralized approach, positioning computing coffers closer to the edge of the network, thereby addressing quiescence, bandwidth, and data sequestration challenges current in traditional polycentric IoT infrastructures. The paper provides an in-depth analysis of Fog Computing's armature, expounding its crucial factors similar to fog bumps, middleware, and edge bias. likewise, it investigates the different operations of Fog Computing in IoT, ranging from realtime data analytics, effective resource operation, to enhanced security and sequestration measures. By bridging the gap between edge bias and centralised pall waiters, Fog Computing emerges as a vital result, fostering the elaboration of scalable, effective, and responsive IoT ecosystems. This exploration contributes precious perceptivity to the architectural nuances and practical operations, paving the way for the integration of Fog Computing as a foundation in the ever-expanding realm of IoT technologies. © 2024 IEEE.

关键词： Fog computing

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3rd International conference of International Society for Intelligent Construction, ISIC 2022

3rd International Conference of International Society for In...

引用

3rd International conference of International Society for Intelligent Construction, ISIC 2022

ISBN: (纸本)9783031202407

The proceedings contain 38 papers. The special focus in this conference is on International Society for Intelligent Construction. The topics include: Additive Manufactured (3D-Printed) Connections for Thermoplastic Facades;auto(mated)nomous Assembly;BIM-to-FEM: Development of a Software Tool to Increase the Operational Efficiency of Dam Construction Projects;converting Algorithms into Tangible Solutions: A Workflow for Materializing Algorithmic Facade Designs;Development of a BIM Model for Facility Management with virtual/Augmented Reality Interaction;improv-Structure: Exploring Improvisation in Collective Human-Robot Construction;An exploration of Graph-Based FEM Optimization for Construction Industry;assessing Hazardous Spills Impact on Road Surface Performances by 3D High Resolution Surveying Techniques;integrating Smart and Sustainable Construction: A Review of Present Status, and Possible Opportunities;digital Construction Strategy for Project Management Optimization in a Building Renovation Site: Machine Learning and Big data analysis;integration of Spot Tests and vibratory Roller data in Rural Road Pavement Layers Made with Recycled Aggregates;multiphysical Coupling analysis of the Transition Zone Behaviour in Corroded Reinforced Concrete Structures;the Influence of the visual Factor on the Efficiency of visualization Method in the Production Environment;waste Elimination and value Management Framework Based on Lean Design Methods;Aggregating High-Precision GNSS Intelligent Construction data for Quality Asphalt Pavements;construction Sector Transformation: Developing a New Learning Paradigm;digitalization of the Asphalt Paving Workflow and Process – Its Challenges and Opportunities;discrete Aggregate Mass Calculation Method for visual Detection of Aggregate Gradation and Elongated and Flat Aggregate Contents;a New Sustainable System for Piped Water Cooling of Mass Concrete Structures.

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Towards Johan Sverdrup Field Development Optimization and Concept Robustness Using AI Assistance

Towards Johan Sverdrup Field Development Optimization and Co...

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2025 SPE/IADC International Drilling conference and Exhibition, DC 2025

作者： Les, B. Tjøstheim, B.P. Sørbel, J. Ulvedal, L. Dolle, N. Equinor ASA Norway WhiteSpace Solutions B.V. Netherlands

ISBN: (纸本)9781959025641

This paper introduces an artificial intelligence (AI)-assisted methodology for rapidly screening multitude field development concepts across cost and risk domains. The methodology, matured over the last years, has been applied to the early-phase Johan Sverdrup Phase 3 Field Development Project (FDP), the company's digital frontrunner, with aim to improve the project's economy while ensuring robust infrastructure placement and expedited CAPEX screening. The methodology integrates evolutionary algorithms to generate sets of possible and feasible well trajectories for considered development targets. Feasibility is ensured adopting the field-specific well concept and associated drilling rules, whereas all possible solutions are evaluated through greedy exploration of a large option space. This is combined with a second solver that optimizes well-to-template allocation and subsea template placement, ensuring that subsurface hazards are avoided and either the total project cost or drilling risk is minimized. Simulated results are presented in an online user interface and analyzed through a digital data report, facilitating evaluation of multiple concepts and the associated cost-risk trade-offs. The study demonstrates a novel fast-track methodology for screening tens of thousands of drilling and surface combinations, significantly accelerating concept comparison and identifying new, relevant FDP solutions. data generated by this methodology was used for internal validation of project assumptions and refinement of concept selection as the project matures towards the final investment decision. Results of study highlighted data-driven concept improvements, sensitivity analysis of reference concept sensitivities, and benefits of human-centered evaluation of solution space. Extracted learning resulted in more efficient use of engineering resources and time, channeling them towards the subset of most promising FDP solutions. This case study represents the first application of an

关键词： Decision making

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An Interactive visual System for data Analytics of Social Media 21st

An Interactive Visual System for Data Analytics of Social Me...

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21st International conference on Algorithms and Architectures for Parallel Processing (ICA3PP)

作者： Zhang, Yi Li, Zhaohui Xi, Dewei Tianjin Univ Coll Intelligence & Comp Tianjin Peoples R China Tianjin Univ Sch New Media & Commun Tianjin Peoples R China

ISBN: (纸本)9783030953911;9783030953904

With the development of the Internet, Big data analysis of social media has become a hot research topic in recent years. However, a challenging problem in social media analysis is how to intelligently detect event information from massive media data and how to help users quickly understand event content. Therefore, we propose a method to extract important time periods of events from media data to analyze the media event information, and develop an interactive visual system based on the "5W" principle. The system provides an interactive analysis platform for exploring media Big data (e.g., Twitter data). The system uses a dynamic topic model to extract topics, a Naive Bayesian classifier to distinguish emotions, and explores events based on the evolution of time, topics, and emotions. In terms of visualization, the system allows users to add some annotations based on segmentation of complex information and highlight important events by adding different story cards to the timeline so that users can get a quick overview of events. Users can also interactively modify the story cards during the exploration process. Finally, several case studies show that our system can effectively reduce the time required to understand social media data and allow users to quickly explore the full picture of an event through an interactive approach.

关键词： Social media analysis Big data analysis Important time period extraction Interactive visualization Social media event

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COLING 2025 - 31st International conference on Computational Linguistics, Proceedings of the Main conference

COLING 2025 - 31st International Conference on Computational...

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31st International conference on Computational Linguistics, COLING 2025

ISBN: (纸本)9798891761964

The proceedings contain 848 papers. The topics discussed include: how well can a long sequence model model long sequences? comparing architectural inductive biases on long-context abilities;sequential fusion of text-close and text-far representations for multimodal sentiment analysis;PoemBERT: a dynamic masking content and ratio based semantic language model for chinese poem generation;STAND-Guard: a small task-adaptive content moderation model;query-LIFE: query-aware language image fusion embedding for e-commerce relevance;improving tool retrieval by leveraging large language models for query generation;RED-CT: a systems design methodology for using LLM-labeled data to train and deploy edge linguistic classifiers;beyond visual understanding introducing PARROT-360v for vision language model benchmarking;and AI-Press: a multi-agent news generating and feedback simulation system powered by large language models.

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1D displacement coding for the displaced subdivision surface

1D displacement coding for the displaced subdivision surface

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2023 IEEE International conference on visual Communications and Image Processing, vCIP 2023

作者： Kishimoto, Koki Kawamura, Kei Kato, Haruhisa KDDI Research Inc. Saitama Japan

ISBN: (纸本)9798350359855

Compression of a dynamic mesh, which represents the dynamic volumetric data for immersive applications, is an emerging technique. One advanced compression technique is video-based dynamic mesh coding (v-DMC). Therein, an original mesh is decomposed into a decimated base mesh including displacement vectors in the v-DMC framework. Because the mesh represents an object in 3D space, these displacements, which express the detailed information of the mesh, are also represented as 3D vectors over the subdivision surface. However, such representation of a 3D vector is redundant because the displacement direction is almost equal to a normal direction of the subdivision surface. Hence, we present a 1D displacement coding that operates with an existing video codec. This method improves both the encoding/decoding procedure complexity and the coding performance on dynamic mesh coding when compared to competing approaches. © 2023 IEEE.

关键词： volumetric analysis

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Surface Integrity Evaluation Based on Barkhausen Noise analysis: A Conceptual Approach 7

Surface Integrity Evaluation Based on Barkhausen Noise Analy...

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7th CIRP conference on Surface Integrity, CSI 2024

作者： Lötfering, Jakob Schrank, Maximilian Rüppel, Adrian Karl Meurer, Markus Bergs, Thomas RWTH Aachen University Campus-Boulevard 30 Aachen52074 Germany Fraunhofer Institute for Production Technology IPT Steinbachstr. 17 Aachen52074 Germany

Destructive testing methods, such as vickers hardness test or hole drilling methods for residual stress evaluation have long been conventional approaches in manufacturing to investigate surface integrity and are widely being used in industry to date. However, their limitations in terms of material damage and high costs have spurred the exploration of non-destructive testing alternatives like Barkhausen noise analysis. So far almost exclusively data-driven and empirical models have been used to employ Barkhausen noise analysis as a non-destructive testing method in manufacturing. These models provide valid predictions for the manufacturing process and the specific material studied. However, they lack the capability to be generalized to other process conditions and materials. Physics-based models on the other hand provide the generalizability needed for widespread industrial applications. This strength turns out to be a weakness when trying to extract residual stress or microstructural properties from these models. The goal of this paper is, to provide an overview of published data-driven models in literature with thematic relevance to manufacturing processes and to propose a new, generalizable model. © 2024 The Authors. Published by Elsevier B.v.

关键词： Nondestructive examination

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An inverse modelling framework for SAR imagery analysis built on SARCASTIC v2.0

An inverse modelling framework for SAR imagery analysis buil...

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IEEE Radar conference (RadarConf)

作者： Woollard, Michael Griffiths, Hugh Ritchie, Matthew UCL Elect & Elect Engn Dept London WC1E 7JE England

ISBN: (纸本)9798350329216;9798350329209

The analysis and interpretation of SAR imagery is widely recognised to be a challenging problem. The number and nature of non-intuitive effects often complicate human visual analysis, whilst the wide variation of target scattering behaviour over extended operating conditions is well-known to hinder automated processing. In this paper, we demonstrate how the SARCASTIC simulation engine is being extended to support answering analytical questions which would typically require significant input from expert analysts through inverse modelling approaches. This is a critical step towards enabling the exploitation of SAR collections at scale, which will become increasingly important as New Space continues to increase the number of taskable sensors on orbit. A case study examining an unusual urban target is presented, utilising real SAR collection data from an Umbra SAR satellite and matching simulations produced using the SARCASTIC toolset. An example analytical approach is demonstrated, and several opportunities for model-aided exploitation are identified. Preliminary results demonstrate promising correlation between the real and synthetic datasets.

关键词： Inverse problems

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visualization Research of Big data in Higher Education Based on the Web of Science 3

Visualization Research of Big Data in Higher Education Based...

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3rd International conference on Electronics, Communications and Information Technology, CECIT 2022

作者： She, Linwei Lai, Liqi Jinan University International Business School Zhuhai519070 China Jinan University GBA and B&R International Joint Research Center for Smart Logistics Zhuhai519070 China Modern Education Technology Center Jinan University Zhuhai519070 China

ISBN: (纸本)9798350331974

With the rapid development of information technology such as artificial intelligence and cloud computing, big data of higher education has received a lot of attention. This article uses the visual software Citespace from 2013 to 2022 to research higher education in big data in the Web of Science database. Through visual analysis, and uses of the keyword co-occurrence function and cluster analysis function, this article clarifies the main research directions, key documents, hotspots, and limitations in the field of big data in higher education, education big data technology, learning behavior analysis, learning style exploration, education resource management, and personalized teaching reform are the development direction and research hotspots. This article can provide readers and other researchers with some references and help. © 2022 IEEE.

关键词： Big data

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