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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271-280 订阅

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engineering Challenges in Industrial AI 24

Engineering Challenges in Industrial AI

引用

IEEE/ACM 3rd international conference on AI engineering - Software engineering for AI (CAIN)

作者： Hollender, Martin Xu, Chaojun Tan, Ruomu ABB Corp Res Ladenburg Germany ABB PAEN Mannheim Germany

ISBN: (纸本)9798400705915

This talk summarizes important experiences we cultivated in several projects where we developed AI methods for industrial customers like chemical production plants or gas fired power plants. One might think that applying leading edge AI methods to large quantities of industrial data will automatically yield valuable results. In our experience there are many "traditional" obstacles that need to be removed, before the magic can happen [2]. For many use cases, data from various sources need to be integrated. For example, time series data stored in industrial data Historians need to be labeled according to quality data stored in Laboratory Information Management systems (LIMS). The process data like setpoints and raw material characteristics need to be contextualized using the production data, e.g. production orders, raw material lots, from ERP systems. Although many companies are currently building up enterprise data lakes, the reality in many plants still is that data is locked in separate silos and a real-time data integration requires significant efforts. Building, automating and operating a large industrial plant requires major (traditional) engineering efforts and expertise. data scientists usually have different backgrounds and often lack knowledge, for example in control systems engineering and process engineering. In addition, many important engineering artifacts like Piping and Instrumentation Diagrams (P&ID) and process design document are either not up to date or even unavailable at all. However, in order to define relevant use cases and design powerful AI solutions, quite a high level of both traditional engineering and data science know-how is required. This means that traditional plant experts need to closely cooperate with data science experts. In the long run, software tools like ABB Ability (TM) BatchInsight will be able to offer easy to use solutions for a broad class of use-cases, so that plant experts can use AI solutions without the need for additi

关键词： Time Series Quality Prediction Golden Batch Analytics

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Research on modeling and adaptation algorithms for reconfigurable production line systems in discrete workshops 3

Research on modeling and adaptation algorithms for reconfigu...

引用

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

作者： Zhou, Jian He, Hai Hu, Wenqiang Wang, Yuhui HuaZhong University of Science and Technology Hubei Province Wuhan China

ISBN: (纸本)9781510681804

With the development of intelligent manufacturing, reconfigurable manufacturing has become one of the current application characteristics, but the actual landing of reconfigurable system in manufacturing workshop still has big problems. In order to solve this problem, this thesis addresses the application of reconfigurable systems and carries out the research and development of intelligent reconfigurable systems. It focuses on the reconfigurable software part, including static model creation, dynamic production process model creation, model adaptation algorithm design, simulation module development and other work. The reconfiguration scheme can be directly simulated, and the reconfigurable scheme and its evaluation indexes are finally obtained and stored in XLS file format, which is convenient for direct access to other process software systems. After comparing the simulation results with the practical results, the practical data proves the reasonableness of the reconfigurable model, the correctness of the reconfigurable algorithm and the effectiveness of the system, which provides theoretical basis for the practical application of the reconfigurable production line at a later stage. © 2024 SPIE.

关键词： Smart manufacturing

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An Empirical Study of Image based Steganography and Watermarking

An Empirical Study of Image based Steganography and Watermar...

引用

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

作者： Padma, R. Yendapalli, Vamsidhar Jyothi, A.P. Gitam University Computer Science and Engineering Gitam School of Technology Bengaluru India Ramaiah University of Applied Sciences Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350359688

In the current technological landscape, the transmis-sion of data through communication channels has experienced significant advancements. The rapid growth in communication technology has brought about improved outcomes. However, challenges arise in ensuring the security and integrity of the transmitted data. It becomes crucial to safeguard from unauthorized access or users without proper authorization, it is important to implement various security parameters and best practices. This need has led to the development of various data hiding techniques. The objective of this paper is to conduct a comprehensive study on the taxonomy of Steganography and Watermarking types, as well as the taxonomy of techniques employed in Steganography and Watermarking. The paper aims to provide an overview and classification of different types of Steganography and Watermarking techniques. It also focuseson analyzing the advantages and disadvantages associated with these *** examining the taxonomy and assessing the pros and cons of Steganography and Watermarking techniques, this paper aims to contribute to a better understanding of their applications and implications in data security. The findings of this study can serve as a valuable resource for researchers and practitioners working in the field of data hiding and information security. © 2024 IEEE.

关键词： Discrete Fourier transforms

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Shower vs. Bath: A Comparative Study of Water Usage and Environmental Impact

Shower vs. Bath: A Comparative Study of Water Usage and Envi...

引用

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

作者： George, Angelina Ashik, F. Jose, Alphonsa Kumar, T.M. Mohan Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science & Engineering Bengaluru India Amrita Vishwa Vidyapeetham Amrita School of Engineering Department of Chemistry Bengaluru India

ISBN: (纸本)9798350359688

This study investigates the usage of water in urban areas, with particular attention to location, age, water quality, and bathing habits. We examined the data using machine learning, more especially a RandomForestClassifier. After accounting for several variables, the study's accuracy rate in predicting the types of baths was 83.63% without SMOTE and reached 90.51% after SMOTE analysis. Our knowledge of urban water consumption is improved by this research, which also shows how flexible machine learning is in identifying intricate links within datasets. The results of this study can help with resource management, urban planning, and environmental initiatives. © 2024 IEEE.

关键词： Bath Type Preferences dataset Analysis Machine Learning Urban Water Consumption

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Transformer Digital Twin Development Framework and Functionality Demonstration

Transformer Digital Twin Development Framework and Functiona...

引用

IEEE international conference on High Voltage engineering and Applications (ICHVE)

作者： Wang, Tingxuan Liu, Ziyuan Wang, Zhaozheng Liu, Jing Matharage, Shanika Yasantha Wang, Zhongdong Univ Manchester Manchester M13 9PL Lancs England

ISBN: (纸本)9798350374995;9798350374988

Industries are embracing the implementation of digital twin to improve reliability and efficiency of their systems. Even though the concept of digital twin is simple, its implementation is challenging due to various issues including the detailed framework which can vary depending on the type of industry. Power transformers are one of the greatest engineering inventions in the 19(th) century that helped achieve today's highly efficient electricity transport process. They are indispensable for the reliable operation of the power network, and managing these assets to their optimal lifetime without unexpected in-service failures is vital. While various modelling approaches have been utilized in design, operation and condition monitoring of power transformers, it is expected that implementation of digital twin will incorporate various physics/knowledge based, data driven models into a single platform where data are of high fidelity, live and interchanged among models and support the best utilization of transformers with high reliability. This paper provides a demonstration of implementing a digital twin platform for power transformers through MATLAB software.

关键词： digital twin power transformer physics-based model data-driven model experience-based model

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Application of Artificial Intelligence to Reduce Production Shortcomings, Reworks and Returns, Logistics Errors 18

Application of Artificial Intelligence to Reduce Production ...

引用

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

作者： Tshihwela, Mulisa Mulongo, Ndala Yves University of Johannesburg Faculty of Engineering and the Built Enviroment South Africa

ISBN: (纸本)9798350318401

The advent of artificial intelligence within the manufacturing industry has been a major swift and is the philosophy of machines to reason, conduct, and achieve either the same output as or comparable to mankind. Numerous flaws and faults that impair product quality and, as a result, lower sales occur during manufacturing and long-product production. Reworking is the wasteful attempt involved in redoing a procedure or action that was done wrong the first time. This study adopts the PRISMA approach to critically review artificial intelligence as a tool to detect products defects, and to help on the returns and reworks, and eliminating errors in the logistics sector. The result from the database focuses more on the current application of artificial intelligence in the manufacturing industries of metal and are mostly based on eliminating products defects, products returns and reworks and eliminating logistic errors also enhancing relationships between the suppliers and the customers. © 2023 IEEE.

关键词： Errors

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A Survey on Improved Feature engineering Assisted Multi-Constraints Outlier Analysis Model for Heuristic Driven K-Means Clustering

A Survey on Improved Feature Engineering Assisted Multi-Cons...

引用

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

作者： Palaparthi, Durga Prasad Sampath, S. Dept. of Information Science & Engineering Adichunchanagiri Institute of Technology Chikkamagaluru India Vtu Belagavi India

ISBN: (纸本)9798350359688

Outliers are the data points that vary significantly from the primary distribution of data. In data mining, determining outliers is an essential task for establishing the data quality, decision-making, and models' performance. Outliers generally cause errors during data collection, sensor malfunction, or data entry. By addressing and detecting outliers, the overall reliability and quality of the data can be increased. The clustering approach is utilized in data mining, image identification, and pattern recognition. In this study, the hard and soft efficient outlier detection clustering models that are implemented for data mining are considered. These are namely K-Means, K++, modified K-Means, K-Medoids, Fuzzy C-means (FCM), Adaptive Switching Randomly Perturbed Particle Swarm Optimization (ASRPPSO) based FCM, and Teaching and Learning-based optimization (TLBO). Accuracy, False Positive Rate (FPR), precision, f-measure, f-score, True Positive Rate (TPR), Completeness Score (CS), Purity measure, Silhouette (SC), Entropy measure, Partition entropy, Partition coefficient Rand Index (RI), Adjusted Rand Index (ARI), Weighted Kappa (WK) coefficient, and convergence time are utilized as the parameters in this study respectively. © 2024 IEEE.

关键词： K-means clustering

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Movement Tracking-Based In-Situ Monitoring System for Additive manufacturing 32nd

Movement Tracking-Based In-Situ Monitoring System for Additi...

引用

32nd international conference on Flexible Automation and Intelligent manufacturing

作者： Vasantha, Gokula Aslan, Ayse Lapok, Paul Lawson, Alistair Thomas, Stuart Edinburgh Napier Univ Edinburgh EH10 5DT Midlothian Scotland

ISBN: (纸本)9783031382406;9783031382413

Monitoring and identification of defects during additive manufacturing is mostly done by bespoke optical or acoustic measurement systems. These in-situ monitoring technologies are either intrusive or sensitive to noisy manufacturing environments. We propose a movement tracking-based in-situ monitoring system for additive manufacturing, which is non-intrusive, less sensitive to environmental factors, and easier to operate and maintain. It evaluates the hypothesis that extruder nozzle temperature can be predicted from printer head movement, since temperature and acceleration are correlated due to the printers control unit. Subsequently, this provides an indication of print quality as the extruder temperature plays a vital role. We collected data from experiments using the MakerBot Replicator to examine the hypothesis. Results show that a Random Forest algorithm is more accurate in predicting the temperature variation using head acceleration and time lag temperature data as input parameters, and outperforms a k-Nearest Neighbors and a Vector Autoregression algorithm.

关键词： In-process monitoring 3D Printer Prediction Modelling Machine Learning Fault Detection

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Human-Centric Design of Automated Production Lines Using Virtual Reality Tools and Human data Analysis 32nd

Human-Centric Design of Automated Production Lines Using Vir...

引用

32nd international conference on Flexible Automation and Intelligent manufacturing

作者： Grandi, Fabio Khamaisi, Riccardo Karim Morganti, Alessio Peruzzini, Margherita Pellicciari, Marcello Univ Modena & Reggio Emilia Dept Engn Enzo Ferrari Modena Italy Univ Modena & Reggio Emilia Dept Sci & Methods Engn Reggio Emilia Italy

ISBN: (纸本)9783031381645;9783031381652

The 4.0 revolution is leading to increasingly automated, flexible, and intelligent manufacturing systems that require greater complexity to manage during maintenance and process control. In this context the optimization of the human machine interaction plays a crucial important role in the design of modern industrial systems. Virtual Reality (VR) offers realistic simulation environments where users can be involved to replicate specific human tasks, detecting and solving problems before they occur. The paper proposes a human-centric digital design methodology that integrates VR technologies with human data analysis tools to support the design or redesign of complex industrial systems. Different wearable devices have been used to collect data about physical and mental user conditions to provide an early assessment of the operators' workload, while comparing different design solutions into the virtual space. An industrial use case related to the redesign of packaging automated machines was used to validate the proposed method and tools: a preliminary correlation between physiological parameters and machines interactions was found.

关键词： Human-centred design Virtual Reality Human data analysis ergonomics and human factors digital simulation

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Research on Intelligent manufacturing Production Lines for Automobile Wheel Hubs by Digital Twin Models 3

Research on Intelligent Manufacturing Production Lines for A...

引用

3rd international conference on data Analytics, Computing and Artificial Intelligence, ICDACAI 2024

作者： Zhuming, Cao Huanbo, Dong Jide, Jia Shouhua, Yi Xiamen China Metalworking Practice Center School of Advanced Engineering University of Science and Technology Beijing Beijing China Center of Modern Engineering Training Hunan University Changsha China

ISBN: (纸本)9798331519032

Due to the complex geometric shapes, high precision design dimensions, and specific material characteristics of automobile wheel hubs, there are stringent requirements for processing procedures, efficiency, and stability. To meet these demands, enterprises commonly adopt intelligent manufacturing production lines. Key challenges include establishing adaptive intelligent capabilities for the "processing-measurement-compensation-processing" cycle, constructing digital twin models of wheel hub production lines for real-time synchronization in virtual reality production, optimizing equipment and process interfaces, and improving fixture systems. Integrating discrete CNC machining, inspection, and assembly organically is crucial for smart manufacturing engineers. This article provides targeted discussions on core technologies and development directions in this field. © 2024 IEEE.

关键词： Smart manufacturing

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