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检索条件"任意字段=Conference on Advanced Process Control and Automation"

共 4412 条记录，以下是1-10 订阅

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Heuristic Tuning and Decoupling Strategies for Multivariable Systems: An Integrated TIA Portal and Matlab-Simulink Approach 10th

Heuristic Tuning and Decoupling Strategies for Multivariab...

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10th International conference on Science, Technology and Innovation for Society, CITIS 2024

作者： Salazar, Diego Pavón, Wilson Montalvo, William Zambrano, Julio Cesar Automation and Control Postgraduate Program Universidad Politécnica Salesiana Quito Ecuador Automation and Control Postgraduate Program Universidad Politécnica Salesiana Cuenca Ecuador

ISBN: (纸本)9783031870644

This paper proposes a comprehensive solution to the advanced control problem of multivariable systems using Siemens’ TIA (Totally Integrated automation) Portal LSIM (Linear Simulation) package. The process model is validated via Matlab-Simulink to compare and support the implementation of the TIA Portal. The control system is then developed using the Relative Gain Array (RGA) concept to minimize cross-coupling effects between inputs. The study demonstrates how decoupling functions and precise tuning improve system performance, reducing interference and enhancing stability. The results confirm that this integrated control framework improves system efficiency, reliability, and adaptability for industrial applications. © The Author(s) 2025.

关键词： Three term control systems

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Data-Driven automation in Welding: Leveraging advanced Machine Learning for Quality and Efficiency 27

Data-Driven Automation in Welding: Leveraging Advanced Machi...

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27th International conference on advanced Communications Technology, ICACT 2025

作者： Khan, Muhammad Omair Mozumder, Md Ariful Islam Azam, Ibad Ullah Akter, Shifat Shima Joo, Mon-Il Kim, Hee Cheol Institute of Digital Anti-Aging Healthcare Inje University Gimhae-si Korea Republic of Department of Industrial & Management Engineering Inje University Gimhae-si Korea Republic of

ISBN: (纸本)9791188428137

automation in manufacturing has played an important role in optimizing the welding process by attaining the utmost level of quality control with high operational efficiency. This paper analyzes 15,000 welding observations that belonged to the Hanthec organization. Through comparative analysis of SVM, MLP, and Decision Tree algorithms, our research establishes an effective machine learning framework for welding parameter optimization. The Decision Tree model obtained an excellent performance with the best accuracy of 80% and perfect recall. High correlations between power and thermal aspects as high as 0.96 have been obtained. The developed framework enables systematic parameter selection and demonstrates the potential for automated decision-making in industrial welding applications, contributing to improved manufacturing quality and reliability. ©20XX IEEE.

关键词： Smart manufacturing

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process regulation control using Echo State Networks: An ESN-based deep neural network approach for PID control 6

Process regulation control using Echo State Networks: An ESN...

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6th International conference on Industry 4.0 and Smart Manufacturing, ISM 2024

作者： Bonci, Andrea Longarini, Lorenzo Longhi, Sauro Pompei, Geremia Prist, Mariorosario Politechnic University of Marche Ancona60131 Italy Institute for Chemical-physical Processes National Research Council of Italy Pisa56126 Italy

In automation systems, Proportional-Integral-Derivative (PID) controllers are extensively used for their simplicity, reliability, and ability to maintain desired process levels by continuously adjusting control inputs to minimize the error between the set-point and the actual process variable. Despite the advantages, they have to face challenges such as handling non-linearities, sensitivity to parameter tuning, limited adaptability to changing process dynamics, and susceptibility to disturbances. For these reasons, various advanced control strategies and adaptive algorithms based on deep neural network are being developed and implemented. The aim of the proposed study is to introduce an innovative method for the regulation of processes, using an ESN-based deep neural network model. As preliminary results a case study on a heating system is considered. The model was trained using data generated under the control of a PID controller and tested on a using a TCLab module. The results indicate that the trained model effectively predicts the outputs of the heating system and the corresponding temperature values in alignment with the target temperatures. This study would be a starting point for a future deep methodological exploration of the mathematical aspects of ESN models to ensure the long-term stability of the system and its limitations. © 2024 The Authors. Published by Elsevier B.V.

关键词： Three term control systems

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Design and Internal Structure Analysis of an automation-Based Smart Dining Table 24

Design and Internal Structure Analysis of an Automation-Base...

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4th International Joint conference on Robotics and Artificial Intelligence, JCRAI 2024

作者： Yan, Shimao Wang, Xuechun Hao, Hanlin Dong, Xinran Wan, Weixin School of Mechanical and Automation Zhixing College Hubei University The Zhixing College of Hubei University Hubei Wuhan China School of Power and Mechanical Engineering Wuhan University The Zhixing College of Hubei University hubei Wuhan China School of Computer and Information Engineering Zhixing College Hubei University The Zhixing College of Hubei University Wuhan China

ISBN: (纸本)9798400710100

In response to the increasing societal demand for time-saving and labor-efficient solutions in table cleaning, this paper presents the design of a novel smart dining table that supersedes manual cleaning tasks. The introduced smart table integrates automatic cleaning, dish handling, and waste collection functionalities, optimizing spatial utilization to automate the entire process from storage, disinfection, categorization, washing, to drying. This comprehensive automation not only reduces the physical effort required for post-meal cleanup but also ensures a more hygienic and efficient dining *** article meticulously outlines the primary operational units of the smart table. It begins with an in-depth examination of the internal structure of the tabletop cleaning robot, which features advanced sensors and navigation systems to ensure thorough and precise cleaning. The design of a flexible four-claw mechanism is discussed, enabling the robot to securely handle various types of dishes and utensils. Additionally, the development of a cleaning tank conveyance system is explored, detailing how it efficiently transports dirty dishes to the washing station. Theoretical computations for the control panel are provided, highlighting the sophisticated algorithms that manage the table's operations. A materials analysis of the internal conveyor mechanism within the table is also presented, emphasizing durability and efficiency. By offering integrated smart services, this innovation enables users to better enjoy a comfortable and healthy dining experience, significantly enhancing the overall quality of life. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Washing

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State-space modelling approach for control and observer design in property-controlled reverse flow forming 11

State-space modelling approach for control and observer desi...

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11th Vienna International conference on Mathematical Modelling, MATHMOD 2025

作者： Kersting, Lukas Arian, Bahman Vasquez, Julian Rozo Trächtler, Ansgar Homberg, Werner Walther, Frank Fraunhofer IEM Paderborn33102 Germany Paderborn33098 Germany Dortmund44227 Germany Heinz Nixdorf Institute Paderborn University Paderborn33102 Germany

Flexible, metal forming processes such as flow forming are exposed to many disturbances that affect geometry and material properties during forming and reduce the reproducibility of those processes. In this context, closed-loop property control is a feasible solution for process improvement. To include advanced controllers and observers in closed-loop property control concepts, mathematical models in terms of state-space models are advantageous. However, especially in case of flow forming these models are not spread due to the complex process kinematics, nonlinearity of the process and spatial dimensions of the workpiece. This makes mathematic state-space modelling challenging. Thus, a model has to be newly developed. This paper therefore presents a novel discrete-Time state-space model for flow forming. The model treats the workpiece geometry as discrete and represents the complex process kinematics in the form of a local sampling of the roller trajectory. It can be shown that the model is valid and that the resulting system dynamics especially results the from the displacement between roller and sensor which is considered in the model. Thus, the result of this paper is a valid state-space model that can be prospectively used in a model-based state observer for flow forming. This state observer could later extent a closed-loop property control to enable more complex property structures than before. Copyright © 2025 The Authors.

关键词： State space methods

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Integrative automation of Cybersecurity Systems through advanced Data Science Methodologies: Enhancing Predictive Analytics and Real-Time Threat Mitigation 4

Integrative Automation of Cybersecurity Systems through Adva...

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4th International conference on Power, control and Computing Technologies, ICPC2T 2025

作者： Das, Subhranil Kumari, Rashmi Singh, Raghwendra Kishore School of Computer Science University of Petroleum and Energy Studies Uttarakhand Dehradun India School of Computer Science Engineering and Technology Bennett University Greater Noida India School of CS & AI SR University Warangal India

ISBN: (纸本)9798331530402

Due to emergence in Corona disease, the digital revolution become more intensified which makes more prevalent in day-to-day activities. As a result, cloud service providers become more frequent. Therefore, system integration is essential throughout a partner ecosystem. Unbelievably many edge devices are sending IoT data to the cloud. The system becomes automated due to the organizational structures which resulted in developing new technologies. This new" Integration ecosystem" is where there is just one platform forall the system. According tothe survey of 4, 500 decisionmakers, data protection-rather than business process optimization or processautomation-was the primary argument for employing AI withinorganizations. Using ML algorithmsto automatically identify cyberattacks is referred to as automating cyber security systems. By leveraging automation, cyber security systems can swiftly identify and respond to attacks, reducing the amount of time needed to avert possible harm. With the considerations in mind, we proposed Automating Cyber Security Systems with Data Science Practices in which we will be talking about how various cyber security systems can effectively utilize current data science practices to automate their workflow. © 2025 IEEE.

关键词： Predictive analytics

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The design and implementation of a maintenance platform for rail vehicle air conditioning systems 4

The design and implementation of a maintenance platform for ...

引用

2024 4th International conference on Intelligent Traffic Systems and Smart City, ITSSC 2024

作者： Liu, Yuheng Wu, Huazhu School of Automation and Electrical Engineering Dalian Jiaotong University 794 Huanghe Road Shahekou District Dalian116028 China

ISBN: (纸本)9781510686304

With the rapid development of urban rail transit, there are efficiency issues in the assembly, commissioning, daily operation, and maintenance of urban rail air conditioning systems. In addition, there is a shortage of professional commissioning and maintenance personnel, which makes it difficult for existing railway colleges and manufacturers to meet the growing demand for training modes and equipment. Therefore, this article proposes and designs a comprehensive and practical urban rail air conditioning simulation training system. The system adopts a real air conditioning unit combined with a fault injection system, and uses Unity3D software for dynamic demonstration. Through 3D animation simulation of the working principle and operation process of the air conditioning system, it enhances the intuitiveness and practicality of the training. The system realizes the switching between centralized control mode and local control mode of train air conditioning, as well as fault simulation and diagnosis functions, comprehensively demonstrating the actual operating status of the air conditioning system. This simulation training platform not only effectively enhances students' practical operation and fault handling abilities, but also provides advanced technical support for improving the maintenance efficiency of rail transit air conditioning systems, which has important practical significance for teaching and practice in the rail transit industry. © 2025 SPIE.

关键词： Personnel training

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Semantic segmentation for virtual-real fusion data processing in nonferrous metal process industry 24

Semantic segmentation for virtual-real fusion data processin...

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8th International conference on Computer Science and Application Engineering, CSAE 2024

作者： Yin, Zhiqiang Zhao, Defeng Feng, Yong Li, Yingna School of Information Engineering and Automation Kunming University of Science and Technology Yunnan Kunming China Yunnan Radio Co. Ltd. Yunnan Kunming China

ISBN: (纸本)9798400718090

By combining high-precision virtual models and actual data, virtual-real fusion technology can significantly improve the production efficiency, quality control and safety of non-ferrous metal process industry, and optimize the production process. In the data processing of virtual-real fusion, environmental understanding is the basis for the correct interaction between virtual objects and the real world in the virtual-real fusion. Virtual-real convergence, especially in Augmented Reality (AR), often requires advanced image understanding techniques to improve user experience and provide more interactivity. Semantic segmentation plays a key role in this process, so this paper proposes a semantic segmentation method that uses RGB and point cloud images as well as deep image fusion to solve the heterogeneous problem of multi-source data in virtual-real fusion data processing, and improve the ability of machine vision system to understand the real world environment in virtual-real fusion. Firstly, Agent Attention is introduced for the decoder stage processing features, which combines the advantages of traditional attention and linear attention. Secondly, a feature fusion method is introduced for adaptive fusion of features between various stages. Experiments were carried out on the NYU Depth Dataset V2 and KITTI-360 data sets, and the segmentation results of the proposed method were 53.7% and 56.7% respectively on mIoU. In addition, the method is applied to the field of ore segmentation, and the mIoU reaches 81.7%, which also achieves good segmentation effect. © 2024 Copyright held by the owner/author(s).

关键词： Semantic Segmentation

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A Robust Methodology for Rig Equipment automation Leveraging Computer Vision

A Robust Methodology for Rig Equipment Automation Leveraging...

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

作者： Li, Z. Mahajan, N. Mathur, A. Koritala, C. Nabors Corporate Services HoustonTX United States

ISBN: (纸本)9781959025641

Introducing an advanced artificial intelligence (AI) system leveraging computer vision technology to automate rig operations in the oil and gas industry. Our approach uniquely addresses the challenges of deploying computer vision technology in harsh rig environments, ensuring consistent operation under variable conditions. The system reduces manual labor, enhances safety, and improves operational efficiency with a 95% accuracy rate. Tested over two years across diverse geographical locations, it demonstrates robust performance. We detail the process of data preprocessing and constructing a training dataset with images of diverse pipes and environmental conditions to enhance model robustness. We evaluate computer vision models such as YOLOs (You Only Look Once) [Redmon 2016] and RetinaNet [Ross 2017], employing heuristics and statistical smoothing to stabilize results. Additionally, we review camera selection, calibration methods, and settings adaptation for various rig conditions and high-speed operations. The paper discusses the server setup and inference methodology needed at the edge to achieve high-speed inference, high accuracy, and continuous model improvement. One specific application of our approach is automating iron roughneck positioning during the tripping phase—a sector previously limited to trip-in operations due to challenges related to trip-out operations such as mud-covered pipes, thin joints, and variable lighting conditions. The proposed methodology achieves approximately 95% accuracy, with 95% of connections automated without human input, underscoring its efficiency and reducing the workload on drillers. This automation enhances safety, accelerates operations, and maintains high precision across diverse environmental conditions, including adverse weather and day-night cycles. Trained and tested across various rig environments, the system overcomes traditional challenges such as mud interference with camera operations and the detection of mud-cover

关键词： Budget control

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Unraveling the AI Revolution in Management control Through Comprehensive Bibliometric Analysis 1st

Unraveling the AI Revolution in Management Control Through C...

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1st International conference on Electrical Systems and Smart Technologies, ICESST 2024

作者： Radi, Chama Ababou, Mariame Rabiai, Sara Fez Business School Private University of Fez Fez Morocco University Mohammed I Oujda Oujda Morocco Ibn Zohr University Agadir Morocco

ISBN: (纸本)9783031867040

Nowadays, artificial intelligence has become one of the pillars of companies’ business efficiency. To analyze trends in this field, we conducted a bibliometric study of 301 articles published in the Scopus database between 2006 and 2024. The analysis is based on quantitative indicators such as keyword occurrence networks and bibliographic citations. Using this approach, we were able to identify six clusters, each emphasizing specific aspects of integrating AI into business performance. First, digital transformation and AI for business performance, second, decision support systems and performance measurement in industry and supply chains. Third, advanced analytics and machine learning for industry and business optimization. Fourth, new technologies for business process automation and efficiency improvement. Fifth, data-driven strategic management to improve business performance and customer satisfaction. Finally, AI-based human resource management and natural language processing for corporate intelligence. Our findings indicate the growing importance of AI in various aspects of business management. However, our study also revealed research gaps. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Human resource management

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