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A multi-threaded parallel iterative greedy algorithm for distributed flowshop group scheduling problems with preventive maintenance

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international JOURNAL OF automation AND control 2025年第3期19卷 265-286页

作者： Sun, Xiaobin Sang, Hongyan Wu, Wanzhong Zhao, Yasheng Han, Qiuyang Liaocheng Univ Sch Comp Sci Liaocheng 252000 Peoples R China

In actual production, factories not only pursue productivity, but also pay attention to the reliability and stability of the production process. For the continuity of production machines, this paper investigates the distributed flow shop group scheduling problem with preventive maintenance (DFGSP/PM). In order to minimise the makespan, a mathematical model of DFGSP/PM is developed and a multi-threaded parallel iterative greedy (MPIG) algorithm is proposed. A greedy NEH (GNEH) method is designed to generate the initial solution. In order to couple the two subproblems of DFGSP/PM, a two-stage destruction and reconstruction is designed. A multi-threaded parallel local search strategy (MPLS) is introduced to improve the search efficiency of the MPIG, so that the optimal insertion positions of the groups in the sequence can be searched faster and the two subproblems can be coupled effectively. Effectiveness analysis has demonstrated that the proposed MPIG significantly reduces computation time and expands the search space.

关键词： distributed flowshop scheduling preventive maintenance iterative greedy algorithm group scheduling parallel computing

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Application and optimization of networked battery maintenance mode in power system

Application and optimization of networked battery maintenanc...

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2024 international conference on Physics, Photonics, and Optical Engineering, ICPPOE 2024

作者： Duan, Xuesong Zhang, Jinjia Li, Yuhao Li, Hongchao Wang, Wei State Grid Henan Electric Power Company State Grid Zhenping County Power Supply Company 474250 China

ISBN: (数字)9781510689121

ISBN: (纸本)9781510689114

Traditional battery maintenance methods have some problems, such as low efficiency, difficult to find potential problems in time and accurately, which affect the stability and reliability of power system. This paper studies the application and optimization of networked battery maintenance mode in power system. By integrating sensor technology, network communication and data analysis, this mode realizes real-time monitoring and maintenance automation of battery state. Aiming at the challenges of lack of real-time and accuracy, optimization strategies such as deploying 5G base stations, adopting advanced algorithms and machine learning technologies are proposed. In addition, a big data analysis platform based on cloud computing is built, and machine learning and data mining are used to predict battery performance decline, and intelligent maintenance algorithms are developed. Experiments show that this mode improves voltage stability, capacity retention and internal resistance control, reduces maintenance cost and improves efficiency. These achievements provide theoretical and practical guidance for the stable operation of power system and efficient maintenance of battery. © 2025 SPIE.

关键词： Batteries Data transmission Resistance Data analysis Data modeling Machine learning Telecommunications Cloud computing Decision making Reliability

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2D Sheet Temperature Estimation for Multi-Stage Press Hardening in a Progressive Die 11

2D Sheet Temperature Estimation for Multi-Stage Press Harden...

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11th Vienna international conference on Mathematical Modelling, MATHMOD 2025

作者： Baumann, Henry Nazarenus, Jakob Martschin, Juri Tekkaya, Erman Meurer, Thomas Digital Process Engineering Group MVM Karlsruhe Institute of Technology Hertzstr. 16 Karlsruhe76187 Germany Multimedia Information Processing Group Kiel University Hermann-Rodewald Straße 3 Kiel24118 Germany Institute of Forming Technology and Lightweight Components TU Dortmund University Baroper Str. 303 Dortmund44227 Germany

During a multi-stage press hardening process, where a metal sheet undergoes rapid austenitization, tempering, and forming, the spatial-Temporal temperature development is a driving factor and its control enables it to reach desired product properties. A two-dimensional model extension is proposed, which enables a precise and computationally efficient temperature modeling along the whole metal sheet. Thereupon, a Kalman filter with a time-varying stage dependent output matrix is used to estimate the spatial-Temporal temperature development of the sheet based on measurements from a thermal imaging camera. Both the proposed modeling approach and the estimation scheme are validated experimentally. Copyright © 2025 The Authors.

关键词： Kalman filters

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UAV control in Multi-access Edge computing Using Markov Decision process 1st

UAV Control in Multi-access Edge Computing Using Markov Dec...

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1st international conference on Intelligent Systems, Blockchain, and Communication Technologies, ISBCom 2024

作者： Elghitani, Fadi Fayed, Ibraheem M. National Telecommunication Institute Cairo Egypt

ISBN: (纸本)9783031823763

Cloud computing is the pradigim where service providers carry-on computational tasks for their customers. Multi-access Edge computing (MEC) is a recent form of service where the computational tasks are carried in a distributed manner at the edge of the network to be as close to customer as possible. This new pradigim have the advantage of lowering the latency, making the pradigim suitable for real-time applications. One promising way to deploy MEC is to mount the servers over a UAV which can be moved dynamically to become closer to users. In this paper, we address the challenges associated with UAV-mounted servers like energy consumption and path routing. We propose a UAV control mechanism based on continuous-time Markov Decision process (CT-MDP). We demonstrated the advantage of the proposed mechanism in terms of task-satisfaction rate and policy computational time. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Markov processes

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Exploiting Asymmetries in Diffusively Coupled Oscillators to Enable Frequency Tunability in Neuromorphic Devices 11

Exploiting Asymmetries in Diffusively Coupled Oscillators to...

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11th Vienna international conference on Mathematical Modelling, MATHMOD 2025

作者： Johann Rolf, Hermann Folke Meurer, Thomas Digital Process Engineering Group Institute of Mechanical Process Engineering and Mechanics Hertzstr. 16 KarlsruheD-76187 Germany

By exploiting controllable asymmetries, consensus in networks can be adjusted. In case of coupled oscillators, the characteristic frequencies of the network can be controlled. This property is called frequency tunability and it is, e.g., induced by changing the asymmetry between the damping of the oscillators or the coupling between the oscillators. Subsequently, the frequency tunability of two diffusively coupled Andronov-Hopf oscillators is investigated by analyzing the emergence of Andronov-Hopf bifurcations. This is done by investigating the local dynamics of the corresponding system. It turns out that the number of critical points of the Andronov-Hopf bifurcation is determined by analyzing a polynomial whose degree changes based on the choice of the bifurcation parameter. Thus, this polynomial is analyzed in terms of two different bifurcation parameters: (i) symmetric damping and (ii) symmetric coupling. In case of (i), the system has two critical points, which correspond to Andronov-Hopf bifurcations. In contrast to this, for (ii) the number of critical points varies between one and three depending on the asymmetric damping. Copyright © 2025 The Authors.

关键词： Damping

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computing Performance Analysis of IEC 61499 Distributed automation Systems

Computing Performance Analysis of IEC 61499 Distributed Auto...

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IEEE international conference on Industrial Technology (ICIT)

作者： Tuojian Lyu Valeriy Vyatkin Department of Electrical Engineering and Automation Aalto University Espoo Finland Department of Computer Science Computer and Space Engineering Luleå Tekniska Universitet Sweden

ISBN: (数字)9798331521950

ISBN: (纸本)9798331521967

This work analyzes the computing performance of distributed control systems in IEC 61499 on two hardware devices, Dell XPS workstation and Raspi 4B. Based on the test IEC 61499 application, three different system configurations are tested to simulate the distribution options of singleprocess and single-thread, multi-threading, and multi-process on both hardware platforms. Experimental results show that multiprocess configurations yield more consistent execution time due to dedicated resource allocation, while multi-threading, though resource-efficient, can lead to latency variability. These results aim at help in choosing optimal configurations and selecting hardware for performance in distributed automation systems.

关键词： Performance evaluation automation Decentralized control Hardware Performance analysis Workstations Resource management IEC Standards

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Edge computing for Real-Time Decision-Making in Industrial automation Systems - A Comprehensive Review

Edge Computing for Real-Time Decision-Making in Industrial A...

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Advancements in Electrical, Electronics, Communication, computing and automation (ICAECA), international conference on

作者： R. Raffik V. J. Balamurugan N. Gopinath Pandian Department of Mechatronics Engineering Kumaraguru College of Technology Coimbatore Tamil Nadu India

ISBN: (数字)9798331525439

ISBN: (纸本)9798331525446

The real-time decision-making potential brought by edge computing is disrupting industrial automation, transcending the speed-and-bandwidth limitations of traditional cloud computing. By enabling on-site data processing, edge computing effectively low-latency and responsive applications, e.g., predictive maintenance, process optimization, and autonomous robotics. This paper discusses edge computing architecture and deployment models, its hardware and software components, and networking infrastructure. The objectives to review are to analyze how edge computing facilitates real-time decision-making in automated industrial processes. The discourse is then fully addressed around the different core technologies, advantages, concerns, real-life instances, and future trends toward increasing efficiencies, lowering latencies, and making smart manufacturing possible. Integration of AI and machine learning at the edge levels make real-time analytics, thus improving efficiency and agility. Key challenges under consideration include security, scalability, and economic impact, along with their applications in the real world. Future direction encompasses AI-based analytics, energy-efficient edge devices, and seamless interoperability poised to change its status from enabler to disrupter concerning industrial automation.

关键词： automation Reviews Decision making process control Real-time systems Energy efficiency Security Optimization Interoperability Edge computing

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Research on anomaly detection of underwater sensor networks based on LSCF neural network 24

Research on anomaly detection of underwater sensor networks ...

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2nd international conference on Frontiers of Intelligent Manufacturing and automation, CFIMA 2024

作者： Qian, Junlei Li, Yihang Jia, Tao Zeng, Kai North China University of Science and Technology Tangshan Iron and Steel Enterprise Process Control and Optimization Technology Innovation Center Tangshan China North China University of Science and Technology Tangshan China

ISBN: (纸本)9798400710681

To address the difficulties in detecting anomalous data in underwater sensor networks and the issue of concept drift in streaming data, a method by constructing an LSTM-CNN Fusion network is proposed. The Long Short-Term Memory neural network and the One-Dimensional Convolutional Neural Network are used as the two base learners of the LSCF network. The Adaptive Sliding Window drift detector is utilized to detect whether data drift occurs. The two base learners are trained independently, and their prediction results are combined through soft voting. The performance of the model is validated using two public datasets, with results showing detection accuracies of 97% and 95% for anomalous data, significantly higher than the average detection accuracy of other models. © 2024 Copyright held by the owner/author(s).

关键词： Convolutional neural networks

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A Game Theory-based Reverse Vickrey Auction for Dynamic Pricing in Edge computing 3

A Game Theory-based Reverse Vickrey Auction for Dynamic Pric...

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3rd international conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Rasane, Atharva Tapale, Manisha Dept. Computer Science and Engineering KLE Technological University’s Dr. M. S. Sheshgiri College Belagavi India

ISBN: (纸本)9798331527549

Low-latency communication is critical for effectively functioning Internet of Things (IoT) systems, including applications in healthcare monitoring, industrial automation, and smart cities. However, the vast number of IoT Devices often overwhelms cloud providers, necessitating the adoption of edge computing to reduce latency and distribute computational load. This paper introduces a novel dynamic pricing mechanism for edge computing based on a reverse Vickrey auction, leveraging game theory to balance competitive pricing with profitability for Edge Servers. We develop utility functions for both IoT Devices and Edge Servers, optimizing the markup to maximize edge server utility while adhering to the budget constraints of IoT Devices. Simulations were conducted with 10 Edge Servers and 50 IoT Devices over 2,000 time units. Results show that the proposed mechanism significantly reduces wait times, with most tasks completed within 10-time units. Moreover, dynamic pricing increases Edge Server profits by up to 10 times in some instances compared to fixed markup approaches. Notably, one server’s total profit rose from 7,702 to 76,130 and another from 57,965 to 94,298, underscoring the enhanced profitability and utilization. These findings confirm that our reverse Vickrey auction strategy effectively balances low-latency demand with sustainable operational revenue for Edge Servers, offering a robust and scalable solution for edge-centric IoT environments. © 2025 IEEE.

关键词： Budget control

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Skill Learning Using process Mining for Large Language Model Plan Generation

Skill Learning Using Process Mining for Large Language Mode...

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international Workshops which were held in conjunction with the 6th international conference on process Mining, ICPM 2024

作者： Redis, Andrei Cosmin Sani, Mohammadreza Fani Zarrin, Bahram Burattin, Andrea Technical University of Denmark Lyngby Denmark Microsoft Development Center Copenhagen Lyngby Denmark

ISBN: (纸本)9783031822247

Large language models (LLMs) hold promise for generating plans for complex tasks, but their effectiveness is limited by sequential execution, lack of control flow models, and difficulties in skill retrieval. Addressing these issues is crucial for improving the efficiency and interpretability of plan generation as LLMs become more central to automation and decision-making. We introduce a novel approach to skill learning in LLMs by integrating process mining techniques, leveraging process discovery for skill acquisition, process models for skill storage, and conformance checking for skill retrieval. Our methods enhance text-based plan generation by enabling flexible skill discovery, parallel execution, and improved interpretability. Experimental results suggest the effectiveness of our approach, with our skill retrieval method surpassing state-of-the-art accuracy baselines under specific conditions. © The Author(s) 2025.

关键词： Contrastive Learning

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