IET Collaborative Intelligent Manufacturing最新文献

Agent-based simulation system for optimising resource allocation in production process

IF 2.5

IET Collaborative Intelligent Manufacturing Pub Date : 2025-02-17 DOI: 10.1049/cim2.70020

Jingjing Zhao, Fan Zhang

{"title":"Agent-based simulation system for optimising resource allocation in production process","authors":"Jingjing Zhao, Fan Zhang","doi":"10.1049/cim2.70020","DOIUrl":"https://doi.org/10.1049/cim2.70020","url":null,"abstract":"Efficient sequencing of processes and resource allocation are critical in production planning scenarios, such as manufacturing workshops and construction projects, to enhance efficiency and reduce operational costs. Resource allocation in such environments is often challenged by temporal constraints, process interdependencies, and resource limitations, which complicate scheduling and increase the risk of delays. This study presents a multi-agent-based simulation system to address these challenges. A scheduling optimisation model is developed to simulate and optimise resource allocation in complex processes with network structures and temporal constraints. The primary objective is to minimise production completion time while ensuring effective resource allocation. Additionally, an adaptive, partially distributed Agent-Based Modelling and Simulation framework is proposed to simulate the execution logic of real-world processes, integrating key factors such as resource limitations, process interdependencies, and real-time decision-making. A priority-based genetic algorithm is also designed and embedded into the multi-agent system to further optimise process sequencing and resource distribution. Simulation experiments across varying case scales validate the model and algorithm. This study highlights the potential of agent-based simulation for solving complex engineering challenges and provides new insights for addressing resource allocation problems in network-structured, time-constrained environments.","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"7 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.70020","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143431243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Automatic multimode identification of complex industrial processes based on network community detection with manifold similarity

IF 2.5

IET Collaborative Intelligent Manufacturing Pub Date : 2025-02-07 DOI: 10.1049/cim2.70019

Yan-Ning Sun, Hai-Bo Qiao, Hong-Wei Xu, Wei Qin, Zeng-Gui Gao, Li-Lan Liu

{"title":"Automatic multimode identification of complex industrial processes based on network community detection with manifold similarity","authors":"Yan-Ning Sun, Hai-Bo Qiao, Hong-Wei Xu, Wei Qin, Zeng-Gui Gao, Li-Lan Liu","doi":"10.1049/cim2.70019","DOIUrl":"https://doi.org/10.1049/cim2.70019","url":null,"abstract":"Complex industrial processes usually exhibit multimode characteristics, meaning that statistical features of process data, such as mean, variance, and correlation, vary across different modes. Extracting critical information from these distinct modes can significantly enhance the accuracy and robustness of data-driven models in process monitoring, condition evaluation, and quality improvement. Consequently, the multimode identification of industrial data becomes a paramount concern in data-driven modelling. However, existing methods for multimode identification require prior knowledge to predetermine the number of modes and struggle to describe the similarity between high-dimensional samples effectively. To address this issue, this study introduces an automatic multimode identification method based on complex network community detection. In this approach, each data sample is considered as a node, and manifold similarity is calculated to construct the complex network model. The method leverages weighted geodesic distances to capture the data's manifold structure and potential density, enabling better distinction between high-dimensional samples in different modes. The greedy search algorithm with modularity maximisation is employed to partition nodes into modes without manual selection of the number of modes. Furthermore, a node degree-based indicator is developed for online mode monitoring. Experimental studies on two examples demonstrate the effectiveness of the proposed method in uncovering multimode characteristics of complex industrial processes, highlighting its promising application potential.","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"7 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.70019","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143362694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Agent-based digital twins for collaborative machine intelligence solutions

IF 2.5

IET Collaborative Intelligent Manufacturing Pub Date : 2025-01-11 DOI: 10.1049/cim2.70018

Yiming He, Weiming Shen

引用次数: 0

An experimental anomaly detection framework for a conveyor motor system using recurrent neural network and dendritic gated neural network

IF 2.5

IET Collaborative Intelligent Manufacturing Pub Date : 2025-01-08 DOI: 10.1049/cim2.70017

Kahiomba Sonia Kiangala, Zenghui Wang

{"title":"An experimental anomaly detection framework for a conveyor motor system using recurrent neural network and dendritic gated neural network","authors":"Kahiomba Sonia Kiangala, Zenghui Wang","doi":"10.1049/cim2.70017","DOIUrl":"https://doi.org/10.1049/cim2.70017","url":null,"abstract":"Machine breakdowns are alarming threats to factories. They can substantially decrease productivity, cause financial losses, and create unsafe work environments for operators. Early detection of system anomalies is crucial to prevent and fix machine threats before they become fatalities. With the advent of digitalisation and smart manufacturing, various artificial intelligence (AI) and machine learning (ML) techniques contribute to implementing efficient anomaly detection systems with more accurate results. In this research, the design of an experimental anomaly detection platform (ADP) was suggested for a conveyor motor system. The ADP analyses time-series conveyor motor parameters and accurately classifies whether they would cause a faulty system. The authors build a classification ML model using dendritic gated neural networks (DGNN) to achieve better accuracy. Dendritic Neural Networks are highly immune to forgetting, contributing to better performance than regular artificial neural networks (ANNs) using backpropagation. The ADP also includes a fault detection platform section for the conveyor motors' time-series parameters with recurrent neural networks (RNN) ML regression models to predict motor sensor values. When training ML classification models, the predicted time-series parameters can also serve data augmentation purposes. This regression section contributes to a more robust and double-layered ADP, preventing threats from the time-series inputs to the output classification level. The ADP solution suits small traditional factories with limited historical data records. The experimental results show the benefits of using our ADP built on the DGNN ML model over several classification models such as ANN, convolutional neural network (CNN), and support vector machine (SVM).","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"7 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.70017","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143113264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhancement of first carbon hit rate in converter steelmaking through integrated learning-based data cleansing

IF 2.5

IET Collaborative Intelligent Manufacturing Pub Date : 2025-01-07 DOI: 10.1049/cim2.70016

Lingyun Yang, Qianchuan Zhao, Tan Li, Mu Gu, Kaiwu Yang, Weining Song

引用次数: 0

Development of an artificial intelligence model for wire electrical discharge machining of Inconel 625 in biomedical applications 生物医学用铬镍铁合金625线材放电加工人工智能模型的建立

IF 2.5

IET Collaborative Intelligent Manufacturing Pub Date : 2024-12-04 DOI: 10.1049/cim2.70015

Pasupuleti Thejasree, Natarajan Manikandan, Neeraj Sunheriya, Jayant Giri, Rajkumar Chadge, T. Sathish, Ajay Kumar, Muhammad Imam Ammarullah

{"title":"Development of an artificial intelligence model for wire electrical discharge machining of Inconel 625 in biomedical applications","authors":"Pasupuleti Thejasree, Natarajan Manikandan, Neeraj Sunheriya, Jayant Giri, Rajkumar Chadge, T. Sathish, Ajay Kumar, Muhammad Imam Ammarullah","doi":"10.1049/cim2.70015","DOIUrl":"https://doi.org/10.1049/cim2.70015","url":null,"abstract":"Superalloys, particularly nickel alloys such as Inconel 625, are increasingly used in biomedical engineering for manufacturing critical components such as implants and surgical instruments due to their exceptional mechanical properties and corrosion resistance. However, traditional machining methods often struggle with these materials due to their high strength and thermal conductivity. This study investigates the application of Wire Electrical Discharge Machining (WEDM) as an advanced method for processing Inconel 625 in biomedical contexts. The authors develop an Adaptive Neuro-Fuzzy Inference System for forecasting WEDM parameters using grey-based data. The model's variable inputs are analysed through analysis of variance (ANOVA) and Taguchi design, aiming to optimise process performance attributes relevant to biomedical applications. Comparative studies between predicted and experimental data demonstrate a high degree of accuracy, indicating that the proposed model effectively enhances the machining process. The results suggest that this intelligent system supports decision-making in the production of high-quality biomedical devices and components.","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"6 4","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.70015","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142859994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Integrated modelling and simulation method of hybrid systems based on X language 基于X语言的混合动力系统综合建模与仿真方法

IF 2.5

IET Collaborative Intelligent Manufacturing Pub Date : 2024-12-02 DOI: 10.1049/cim2.70006

Kunyu Xie, Lin Zhang, Xiaohan Wang, Kunyu Wang, Yingjie Li

{"title":"Integrated modelling and simulation method of hybrid systems based on X language","authors":"Kunyu Xie, Lin Zhang, Xiaohan Wang, Kunyu Wang, Yingjie Li","doi":"10.1049/cim2.70006","DOIUrl":"https://doi.org/10.1049/cim2.70006","url":null,"abstract":"Model-based systems engineering is now leading the way in supporting the design of complex products or systems. The integration of modelling and simulation of continuous-discrete hybrid systems is the key of model-based systems engineering. But the existing languages, formalisms and tools cannot support the unified modelling and simulation of hybrid systems and therefore reduces the efficiency of complex system development. To address this issue, this paper develops a design method of complex hybrid systems, which integrates modelling and simulation of the continuous-discrete hybrid behaviour. Specifically, the authors provided a modelling method of hybrid systems based on the X language, a simulation method based on XDEVS, and a compilation algorithm to transform the hybrid model constructed with X language into XDEVS simulation files. In this way, the X language hybrid model can be automatically translated into XDEVS simulation files by a compiler. The simulation files can then be simulated by the XDEVS simulation engine. The obtained simulation results will be used to verify whether the design scheme meets the design requirements of the hybrid system. Finally, the correctness and feasibility of the proposed method are verified using a car-driving model.","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"6 4","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.70006","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142762084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

RETRACTION: A flight control method for unmanned aerial vehicles based on vibration suppression 缩回：一种基于振动抑制的无人机飞行控制方法

IF 2.5

IET Collaborative Intelligent Manufacturing Pub Date : 2024-11-28 DOI: 10.1049/cim2.70014

{"title":"RETRACTION: A flight control method for unmanned aerial vehicles based on vibration suppression","authors":"","doi":"10.1049/cim2.70014","DOIUrl":"https://doi.org/10.1049/cim2.70014","url":null,"abstract":"RETRACTION: X. Wang, X. Zhang, H. Gong, J. Jiang, H. M. Rai: A flight control method for unmanned aerial vehicles based on vibration suppression. IET Collaborative Intelligent Manufacturing 3, no. 3, 252–261 (2021). https://doi.org/10.1049/cim2.12027.The above article, published online on 26 March 2021 in Wiley Online Library (wileyonlinelibrary.com) has been retracted by agreement between the journal's Editors-in-Chief; Liang Gao and Weiming Shen; the Institution of Engineering and Technology; and John Wiley & Sons Ltd.This article was published as part of a guest-edited special issue. Following an investigation, the IET, John Wiley & Sons Ltd and the journal have determined that the article was not reviewed in line with the journal's peer review standards and there is evidence that the peer review process of the corresponding special issue underwent systematic manipulation. In addition, the manuscript contains flaws and inconsistencies. Accordingly, we cannot vouch for the integrity or reliability of the content and have taken the decision to retract the article. The authors have been informed of the decision to retract.","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"6 4","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.70014","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142749221","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

RETRACTION: Research on dispersion compensation using avalanche photodiode and pin photodiode 摘要：利用雪崩光电二极管和引脚光电二极管进行色散补偿的研究

IF 2.5

IET Collaborative Intelligent Manufacturing Pub Date : 2024-11-28 DOI: 10.1049/cim2.70010

{"title":"RETRACTION: Research on dispersion compensation using avalanche photodiode and pin photodiode","authors":"","doi":"10.1049/cim2.70010","DOIUrl":"https://doi.org/10.1049/cim2.70010","url":null,"abstract":"RETRACTION: Y. Ma, Q. Chen, S. Wang, S. Sharma, S. Khanna: Research on dispersion compensation using avalanche photodiode and pin photodiode. IET Collaborative Intelligent Manufacturing 3, no. 3, 205–214 (2021). https://doi.org/10.1049/cim2.12000.The above article, published online on 17 December 2020 in Wiley Online Library (wileyonlinelibrary.com) has been retracted by agreement between the journal's Editors-in-Chief; Liang Gao and Weiming Shen; the Institution of Engineering and Technology; and John Wiley & Sons Ltd.This article was published as part of a guest-edited special issue. Following an investigation, the IET, John Wiley & Sons Ltd and the journal have determined that the article was not reviewed in line with the journal's peer review standards and there is evidence that the peer review process of the special issue underwent systematic manipulation. Furthermore, mistakes and inconsistencies were found in different figures of this manuscript. Accordingly, we cannot vouch for the integrity or reliability of the content and have taken the decision to retract the article. The authors have been informed of the decision to retract.","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"6 4","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.70010","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142749222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

RETRACTION: A novel method of material demand forecasting for power supply chains in industrial applications 摘要：工业应用中电力供应链材料需求预测的新方法

IF 2.5

IET Collaborative Intelligent Manufacturing Pub Date : 2024-11-28 DOI: 10.1049/cim2.70012

{"title":"RETRACTION: A novel method of material demand forecasting for power supply chains in industrial applications","authors":"","doi":"10.1049/cim2.70012","DOIUrl":"https://doi.org/10.1049/cim2.70012","url":null,"abstract":"RETRACTION: Y. Xiao, Z. Jun, H. Lei, A. Sharma, A. Sharma: A novel method of material demand forecasting for power supply chains in industrial applications. IET Collaborative Intelligent Manufacturing 3, no. 3, 273–280 (2021). https://doi.org/10.1049/cim2.12007.The above article, published online on 21 February 2021 in Wiley Online Library (wileyonlinelibrary.com) has been retracted by agreement between the journal's Editors-in-Chief; Liang Gao and Weiming Shen; the Institution of Engineering and Technology; and John Wiley & Sons Ltd.This article was published as part of a guest-edited special issue. Following an investigation, the IET, John Wiley & Sons Ltd and the journal have determined that the article was not reviewed in line with the journal's peer review standards and there is evidence that the peer review process of the special issue underwent systematic manipulation. In addition, most graphs are missing relevant units and descriptors so that the results are not comprehensible. Accordingly, we cannot vouch for the integrity or reliability of the content and have taken the decision to retract the article. The authors have been informed and they disagree with the retraction.","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"6 4","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.70012","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142749142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0