Robotics and Computer-integrated Manufacturing最新文献_第7页

A learning-guided hybrid genetic algorithm and multi-neighborhood search for the integrated process planning and scheduling problem with reconfigurable manufacturing cells

IF 9.1 1区计算机科学

Robotics and Computer-integrated Manufacturing Pub Date : 2024-12-16 DOI: 10.1016/j.rcim.2024.102919

Yiwen Hu , Hongliang Dong , Jianhua Liu , Cunbo Zhuang , Feng Zhang

{"title":"A learning-guided hybrid genetic algorithm and multi-neighborhood search for the integrated process planning and scheduling problem with reconfigurable manufacturing cells","authors":"Yiwen Hu , Hongliang Dong , Jianhua Liu , Cunbo Zhuang , Feng Zhang","doi":"10.1016/j.rcim.2024.102919","DOIUrl":"10.1016/j.rcim.2024.102919","url":null,"abstract":"<div><div>Integrated process planning and scheduling (IPPS) is a crucial component of an intelligent manufacturing system. While most existing studies have focused on the manufacturing workshop, less attention has been given to the assembly and test workshops, which typically include reconfigurable manufacturing cells (RMCs). Therefore, this paper focuses on IPPS with reconfigurable manufacturing cells (IPPS_RMCs) in the context of assembly and test workshops. The objective of IPPS_RMCs is to minimize the makespan and total weighted tardiness, taking into account priority constraints and capability conversion limits of RMCs. To address and optimize this problem, a learning-guided hybrid genetic algorithm (LG_HGA) is proposed, which utilizes chromosome encoding to solve the process planning and scheduling problem synchronously. The LG_HGA incorporates NSGA-II as the global search and employs a learning-guided multi-neighborhood search (LG_MNS) to achieve a better balance between exploration and exploitation. In the global search phase, a problem-based methodology for gene operation is introduced. The LG_MNS consists of four neighborhood structures, based on critical paths and heuristic rules. Additionally, the learning-guided mechanism involves using a decision tree regression model to learn data from the knowledge base and determine how to perform local search. Through case tests of various sizes, the experimental results demonstrate that LG_HGA outperforms several advanced multi-objective evolutionary algorithms due to the proposed improved genetic operations, neighborhood structure, and learning mechanism.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"93 ","pages":"Article 102919"},"PeriodicalIF":9.1,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143150955","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Towards intelligent cooperative robotics in additive manufacturing: Past, present, and future 面向增材制造中的智能协作机器人：过去、现在和未来

IF 9.1 1区计算机科学

Robotics and Computer-integrated Manufacturing Pub Date : 2024-12-13 DOI: 10.1016/j.rcim.2024.102925

Sean Rescsanski , Rainer Hebert , Azadeh Haghighi , Jiong Tang , Farhad Imani

{"title":"Towards intelligent cooperative robotics in additive manufacturing: Past, present, and future","authors":"Sean Rescsanski , Rainer Hebert , Azadeh Haghighi , Jiong Tang , Farhad Imani","doi":"10.1016/j.rcim.2024.102925","DOIUrl":"10.1016/j.rcim.2024.102925","url":null,"abstract":"<div><div>Additive manufacturing (AM) technologies have undergone significant advancements through the integration of cooperative robotics additive manufacturing (C-RAAM) platforms. By deploying AM processes on the end effectors of multiple robotic arms, not only are traditional constraints such as limited build volumes circumvented, but systems also achieve accelerated fabrication speeds, cooperative sensing capabilities, and in-situ multi-material deposition. Despite advancements, challenges remain, particularly regarding defect generation including voids, cracks, and residual stress. Various factors contribute to these issues, including toolpath planning (i.e., slicing strategies), part decomposition for cooperative printing, and motion planning (i.e., path and trajectory planning). This review first examines the critical aspects of system control for C-RAAM systems consisting of slicing and motion planning. The methods for the mitigation of defects through the adjustment of these aspects and the process parameters of AM methods are then described in the context of how they modify the AM process: pre-process, inter-layer (i.e., during layer pauses), and mid-layer (i.e., during material deposition). The application of advanced sensing technologies, including high-resolution cameras, laser scanners, and thermal imaging, for capturing of micro, meso, and macro-scale defects is explored. The role of digital twins is analyzed, emphasizing their capability to simulate and predict manufacturing outcomes, enabling preemptive adjustments to prevent defects. Finally, the outlook and future opportunities for developing next-generation C-RAAM systems are outlined.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"93 ","pages":"Article 102925"},"PeriodicalIF":9.1,"publicationDate":"2024-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142816574","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Sim2Joint: Dynamic hybrid model for solder joint prediction across Sim2Real Sim2Joint：基于Sim2Real的焊点预测动态混合模型

IF 9.1 1区计算机科学

Robotics and Computer-integrated Manufacturing Pub Date : 2024-12-13 DOI: 10.1016/j.rcim.2024.102926

Nieqing Cao , Jaewoo Kim , Abdelrahman Farrag , Daehan Won , Sang Won Yoon

{"title":"Sim2Joint: Dynamic hybrid model for solder joint prediction across Sim2Real","authors":"Nieqing Cao , Jaewoo Kim , Abdelrahman Farrag , Daehan Won , Sang Won Yoon","doi":"10.1016/j.rcim.2024.102926","DOIUrl":"10.1016/j.rcim.2024.102926","url":null,"abstract":"<div><div>The objective of this research is to predict the solder joint’s fillet profile before its formation. Solder joints are crucial for the structural and operational reliability of electronic assemblies, yet their integrity can be compromised by defects such as cold joints, voids, or insufficient solder. Traditional physics-based simulations attempt to model these phenomena but often fall short due to simplifications that fail to capture real-world variability. Conversely, data-driven approaches leverage historical data from Surface Mount Technology (SMT) lines to predict joint quality, though their effectiveness can be hampered by data noise and imbalance. Addressing these limitations, this research introduces a hybrid modeling framework named Sim2Joint, which combines physics knowledge-based simulations with the adaptability of data-driven methods. By introducing Sim2Real in the joint simulation domain, Sim2Joint bridges the gap between simulation and real-world situations by integrating dynamic weights for printing and placing factors with real-world data, enhancing prediction accuracy and reliability. The framework also includes uncertainty quantification to provide more reliable solder joint fillet profile predictions, thereby enabling better decision-making and optimization in SMT processes. Sim2Joint is validated against various baselines, showcasing its capability to adapt to real-time changes and improve the predictive performance of solder joint quality assessments.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"93 ","pages":"Article 102926"},"PeriodicalIF":9.1,"publicationDate":"2024-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142816573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A flexible fixture system with integrated position optimization for large thin-walled component assembly 大型薄壁构件装配柔性夹具集成位置优化系统

IF 9.1 1区计算机科学

Robotics and Computer-integrated Manufacturing Pub Date : 2024-12-12 DOI: 10.1016/j.rcim.2024.102929

Changhui Liu , Ke Jin , Yixi Zhao , Xiaojia Liu , Jianzhi Sun , Xin Li , Qirong Tang

引用次数: 0

A multi-agent reinforcement learning based scheduling strategy for flexible job shops under machine breakdowns

IF 9.1 1区计算机科学

Robotics and Computer-integrated Manufacturing Pub Date : 2024-12-10 DOI: 10.1016/j.rcim.2024.102923

Lingling Lv, Jiaxin Fan, Chunjiang Zhang, Weiming Shen

{"title":"A multi-agent reinforcement learning based scheduling strategy for flexible job shops under machine breakdowns","authors":"Lingling Lv, Jiaxin Fan, Chunjiang Zhang, Weiming Shen","doi":"10.1016/j.rcim.2024.102923","DOIUrl":"10.1016/j.rcim.2024.102923","url":null,"abstract":"<div><div>In a highly disrupted workshop environment, machine failures may occur frequently, requiring real-time schedule repair strategies. This paper proposes a type-aware multi-agent deep reinforcement learning (MADRL) to address real-time schedule repair for the flexible job shop scheduling problem under machine breakdowns. First, the problem is modeled as a multi-agent Markov decision process. At each decision point, the relationships among machine agents and operations are represented using a heterogeneous graph. Based on the graph, machine node embeddings are obtained based on a meta-path type-aware (MPTA) recurrent neural network. Meanwhile, a heterogeneous graph attention network is introduced to aggregate the features of nodes in the heterogeneous graph, forming operation embeddings available for each machine agent’s selection. The type-aware process of obtaining machine node embeddings and operation embeddings utilizes a hypernetwork to achieve parameter adaptation of node types, edge types, and node locations. Finally, performing a cross-attention mechanism on machine node embedding and its candidate operation embeddings for selection. Compared with the heuristic rules and MADRL algorithms, numerical experiment results indicate that the proposed MADRL achieves the minimum stability objective while reducing the makespan of the schedule affected by machine breakdowns.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"93 ","pages":"Article 102923"},"PeriodicalIF":9.1,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143151891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A mixed reality-based aircraft cable harness installation assistance system with fully occluded gesture recognition 基于混合现实技术的飞机电缆线束安装辅助系统，具有完全隐蔽的手势识别功能

IF 9.1 1区计算机科学

Robotics and Computer-integrated Manufacturing Pub Date : 2024-12-10 DOI: 10.1016/j.rcim.2024.102930

Zhuo Wang , Weichu Li , Jiacheng Zhang , Yiliang Zhou , Shisong Chen , Yuwei Dai , Jiale Song , Yeming Cheng , Xiaoting Du

{"title":"A mixed reality-based aircraft cable harness installation assistance system with fully occluded gesture recognition","authors":"Zhuo Wang , Weichu Li , Jiacheng Zhang , Yiliang Zhou , Shisong Chen , Yuwei Dai , Jiale Song , Yeming Cheng , Xiaoting Du","doi":"10.1016/j.rcim.2024.102930","DOIUrl":"10.1016/j.rcim.2024.102930","url":null,"abstract":"<div><div>In limited visibility human-machine environments, there has been little discussion on hand motion parameter extraction, behavioral intention data analysis, and the effectiveness of 3D assembly instructions. To address this issue, we developed a mixed reality system for fully occluded gesture recognition (Fog-MR), which supports the extraction of complete hand motion models, the determination of a directional relationship between hand motion models and task intentions, and provides timely, natural visual feedback for hand operations. Firstly, a 3D hand pose registration method for cyber-physical objects is proposed, which uses BundleFusion to obtain a 3D point cloud model of virtual hands in VR space. Secondly, a hand motion feature spectral clustering analysis method based on a hand reconstruction model is constructed, combining a dual autoencoder network and mutual information metrics to achieve precise matching of hand behavioral intentions. Finally, a new industrial mixed reality visual prompt is designed, providing operators with more vivid and specific operational guidance. Experimental data indicate that compared to our previously developed mixed reality assembly system (Ug-MR), Fog-MR system significantly improves the motion synchronization accuracy between virtual hands and operator's hands, the accuracy of clustering hand motion parameters, and the naturalness of 3D assembly instructions that express behavioral intentions. These improvements significantly reduce the frequency of errors and omissions in such human-machine collaborative assembly processes, which is crucial for enhancing the reliability of high-precision manual operations.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"93 ","pages":"Article 102930"},"PeriodicalIF":9.1,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142816576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Exploring the Integration of cloud manufacturing and cyber-physical systems in the era of industry 4.0 – An OPC UA approach 探索工业4.0时代云制造与网络物理系统的集成——一种OPC UA方法

IF 9.1 1区计算机科学

Robotics and Computer-integrated Manufacturing Pub Date : 2024-12-09 DOI: 10.1016/j.rcim.2024.102927

Tang Ji, Xun Xu

{"title":"Exploring the Integration of cloud manufacturing and cyber-physical systems in the era of industry 4.0 – An OPC UA approach","authors":"Tang Ji, Xun Xu","doi":"10.1016/j.rcim.2024.102927","DOIUrl":"10.1016/j.rcim.2024.102927","url":null,"abstract":"<div><div>The convergence of Cloud Manufacturing and Cyber-Physical Systems (CPS) presents an opportunity worth exploring. This paper looks into integrating these two concepts by utilising the OPC Unified Architecture (OPC UA) as a key communication protocol. Following a critical review of the relevant concepts, the authors propose a conceptual hybrid architecture that relies on OPC UA to facilitate seamless data exchange and interoperability across different levels of manufacturing systems. The proposed architecture addresses current challenges in integrating Cloud Manufacturing and CPS, including the need for real-time monitoring, adaptive control, and efficient data management. Through this approach, enterprises can optimise manufacturing processes by enhancing real-time capabilities and utilising cloud resources effectively. The paper outlines the key components of this architecture, including communication protocol levels, OPC UA functions, and the relationship between cloud services and manufacturing systems. It offers a clear path toward smarter manufacturing environments.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"93 ","pages":"Article 102927"},"PeriodicalIF":9.1,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142816609","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Uncertainty quantification and dynamic characteristics identification for predicting milling stability lobe based on surrogate model 基于代理模型的铣削稳定性预测的不确定性量化与动态特性识别

IF 9.1 1区计算机科学

Robotics and Computer-integrated Manufacturing Pub Date : 2024-12-07 DOI: 10.1016/j.rcim.2024.102922

Guanying Huo , Yizhang Luo , Xin Jiang , Cheng Su , Zhiming Zheng

{"title":"Uncertainty quantification and dynamic characteristics identification for predicting milling stability lobe based on surrogate model","authors":"Guanying Huo , Yizhang Luo , Xin Jiang , Cheng Su , Zhiming Zheng","doi":"10.1016/j.rcim.2024.102922","DOIUrl":"10.1016/j.rcim.2024.102922","url":null,"abstract":"<div><div>The prediction of chatter-free machining parameters suffers from inaccuracies in dynamic milling model inputs and simplification in milling process modeling, which may lead to a significant mismatch between the predicted stability boundary of the mathematical model and actual physical experiments. This study proposes a novel stability analysis method for milling operations based on a surrogate model that considers the effects of both uncertainties and variations in model inputs. The uncertainties of inputs are quantified by considering the statistical distribution of both cutting force coefficients and modal parameters, and the variations of modal parameters are identified through operational modal analysis (OMA). Furthermore, the proposed method introduces the statistical Kriging surrogate model of the spectral radius in the model parameter domain to propagate uncertainties to the stability lobe diagram (SLD). The confidence interval of the predicted stability boundary is obtained using the estimated prediction variance of the generated Kriging surrogate model. Finally, a mathematical measurement of SLD quality is presented, based on the similarities both in shape and position between the predicted and experimental stability boundaries. The cutting experimental verification and numerical analysis indicated that the robustness and accuracy of the SLD are considerably improved compared to the state-of-the-art methods. Thus, the proposed method holds significant promise for practical engineering applications in controlling milling stability on machining equipment such as CNC tools and industrial robots.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"93 ","pages":"Article 102922"},"PeriodicalIF":9.1,"publicationDate":"2024-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142788953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Empower dexterous robotic hand for human-centric smart manufacturing: A perception and skill learning perspective 为以人为中心的智能制造赋予灵巧的机器人手：感知和技能学习的视角

IF 9.1 1区计算机科学

Robotics and Computer-integrated Manufacturing Pub Date : 2024-12-06 DOI: 10.1016/j.rcim.2024.102909

Benhua Gao , Junming Fan , Pai Zheng

{"title":"Empower dexterous robotic hand for human-centric smart manufacturing: A perception and skill learning perspective","authors":"Benhua Gao , Junming Fan , Pai Zheng","doi":"10.1016/j.rcim.2024.102909","DOIUrl":"10.1016/j.rcim.2024.102909","url":null,"abstract":"<div><div>Recent rapid developments of dexterous robotic hands have greatly enhanced the manipulative capabilities of robots, enabling them to perform industrial tasks in human-like dexterity. These advancements not only enhance operational efficiency but also liberate human operators from monotonous tasks, allowing them to focus on creative and intellectually demanding. Despite the considerable attention robotic hands have garnered, existing reviews tend to focus on isolated topics, failing to provide a comprehensive perspective of the manufacturing sector. To empower robotic hands in human-centric smart manufacturing, this paper explores the latest research on holistic perception and dexterous skill learning of robotic hands. Specifically, the perceptual challenges in dexterous manipulation concerning different entities are investigated, including human hand perception, object inside-hand and outside-hand perception based on vision or tactility, and hand-object interactions, which help robots accurately understand environmental information. Furthermore, learning-based control methods are discussed, enhancing the execution capabilities of robotic hands through learning from scratch and learning from human demonstrations. Lastly, this paper identifies current challenges and offers several promising directions for future developments.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"93 ","pages":"Article 102909"},"PeriodicalIF":9.1,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142788895","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A survey on recent trends in robotics and artificial intelligence in the furniture industry 一项关于家具行业机器人和人工智能最新趋势的调查

IF 9.1 1区计算机科学

Robotics and Computer-integrated Manufacturing Pub Date : 2024-12-06 DOI: 10.1016/j.rcim.2024.102920

Andrea Brunello , Giuliano Fabris , Alessandro Gasparetto , Angelo Montanari , Nicola Saccomanno , Lorenzo Scalera

引用次数: 0