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International Journal of Computer Integrated Manufacturing最新文献

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Digital twin-based reinforcement learning framework: application to autonomous mobile robot dispatching 基于数字孪生的强化学习框架:应用于自主移动机器人调度
IF 4.1 3区 工程技术 Q1 Engineering Pub Date : 2024-02-15 DOI: 10.1080/0951192x.2024.2314787
Amel Jaoua, Samar Masmoudi, Elisa Negri
This paper proposes a new framework for embedding an Intelligent Digital Twin (DT) in a production system with the objective of achieving more efficient real-time production planning and control. F...
本文提出了在生产系统中嵌入智能数字双胞胎(DT)的新框架,目的是实现更高效的实时生产规划和控制。F...
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引用次数: 0
Effective integration of low-cost digital manufacturing systems: a reference architecture driven approach 低成本数字化制造系统的有效集成:参考架构驱动法
IF 4.1 3区 工程技术 Q1 Engineering Pub Date : 2024-02-11 DOI: 10.1080/0951192x.2024.2314785
J. Kaiser, G. Hawkridge, D. McFarlane, F. Schnicke, K. Kruger
Integration involves the systematic linking of system components, functions and solutions. For digital systems comprising low-cost components, integration enables the sharing of resources and allow...
集成是指系统组件、功能和解决方案之间的系统连接。对于由低成本组件组成的数字系统而言,集成可实现资源共享,并允许...
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引用次数: 0
Manufacturing cloud service recommendation model based on deep feature learning and user preference perception 基于深度特征学习和用户偏好感知的制造云服务推荐模型
IF 4.1 3区 工程技术 Q1 Engineering Pub Date : 2024-02-11 DOI: 10.1080/0951192x.2024.2314781
Shenquan Huang, Yujie Wang, An Long, Xiaohui Zhu, Luchuan Yu
The manufacturing cloud service recommendation model is a key technology for users to quickly discover and obtain the personalized services they need from the increasingly expanding manufacturing c...
制造云服务推荐模型是一项关键技术,可帮助用户从日益扩大的制造云服务中快速发现并获得所需的个性化服务。
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引用次数: 0
A comparative study for the assessment of marker-less mixed reality applications for the operator training 评估用于操作员培训的无标记混合现实应用的比较研究
IF 4.1 3区 工程技术 Q1 Engineering Pub Date : 2024-02-06 DOI: 10.1080/0951192x.2024.2314793
Agnese Brunzini, Marianna Ciccarelli, Mikhailo Sartini, Alessandra Papetti, Michele Germani
With the rising concept of Industry 5.0, the worker’s needs and well-being are placed at the center of the production process. The use of extended reality can be exploited to provide the operator w...
随着工业 5.0 概念的兴起,工人的需求和福祉被置于生产流程的中心。可以利用扩展现实技术为操作员提供...
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引用次数: 0
Smart manufacturing enabled by intelligent technologies 智能技术助力智能制造
IF 4.1 3区 工程技术 Q1 Engineering Pub Date : 2024-01-18 DOI: 10.1080/0951192x.2023.2296185
Yuqian Lu, Lihui Wang, Aydin Nassehi, Jiafu Wan
Published in International Journal of Computer Integrated Manufacturing (Vol. 37, No. 1-2, 2024)
发表于《国际计算机集成制造杂志》(第 37 卷,第 1-2 期,2024 年)
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引用次数: 0
Digital twin and parameter correlation-enabled variant design of production lines 通过数字孪生和参数相关性对生产线进行变型设计
IF 4.1 3区 工程技术 Q1 Engineering Pub Date : 2023-12-22 DOI: 10.1080/0951192x.2023.2294447
Douxi Yan, Jiafeng Yang, Xiaofeng Zhu, Jiewu Leng, Ding Zhang, Yuqian Lu, Qiang Liu
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引用次数: 0
Multi-agent modelling of cyber-physical systems for IEC 61499-based distributed intelligent automation 为基于 IEC 61499 的分布式智能自动化建立网络物理系统多代理模型
IF 4.1 3区 工程技术 Q1 Engineering Pub Date : 2023-12-21 DOI: 10.1080/0951192x.2023.2294442
Guolin Lyu, Robert W. Brennan
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引用次数: 0
Quantum machine learning a new frontier in smart manufacturing: a systematic literature review from period 1995 to 2021 量子机器学习--智能制造的新前沿:1995 年至 2021 年的系统文献综述
IF 4.1 3区 工程技术 Q1 Engineering Pub Date : 2023-12-20 DOI: 10.1080/0951192x.2023.2294441
V. Narwane, A. Gunasekaran, Bhaskar B. Gardas, Pinyarat Sirisomboonsuk
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引用次数: 0
A multi-input parallel convolutional attention network for tool wear monitoring 用于刀具磨损监测的多输入并行卷积注意力网络
IF 4.1 3区 工程技术 Q1 Engineering Pub Date : 2023-12-20 DOI: 10.1080/0951192x.2023.2294440
Qiang Liu, Dingkun Li, Jing Ma, Xudong Wei, Zhengyan Bai
Effective tool wear monitoring is of great importance for machining process. With existing deep learning-based methods, the end-to-end model is often combined with sensor data to predict the state ...
有效监测刀具磨损对加工过程至关重要。在现有的基于深度学习的方法中,端到端模型通常与传感器数据相结合,以预测刀具磨损的状态。
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引用次数: 0
Adaptive radial basis function neural network sliding mode control of robot manipulator based on improved genetic algorithm 基于改进遗传算法的机器人机械手自适应径向基函数神经网络滑模控制
IF 4.1 3区 工程技术 Q1 Engineering Pub Date : 2023-12-19 DOI: 10.1080/0951192x.2023.2294439
Hang Li, Xiaobing Hu, Xuejian Zhang, Haijun Chen, Yunchen Li
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引用次数: 0
期刊
International Journal of Computer Integrated Manufacturing
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