Robotics and Computer-integrated Manufacturing最新文献_第5页

Strategic algorithm for cable wiring using dual arm with compliance control 带柔度控制的双臂电缆布线策略算法

IF 9.1 1区计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Robotics and Computer-integrated Manufacturing

Pub Date : 2024-12-24 DOI: 10.1016/j.rcim.2024.102924

Youngsu Cho , Minsu Cho , Jongwoo Park, Byung-Kil Han, Young Hun Lee, Sung-Hyuk Song, Chanhun Park, Dong Il Park

A variety of electronic products are in daily use to serve a variety of needs. Electronic products require different types of cable harnesses for production. Nowadays, user preferences vary and change quickly. Therefore, a variety of small-volume products are made, and producing various kinds of complex harnesses to satisfy people’s needs is difficult. In robotic automation, the wiring harness assembly process in the manufacturing of deformable objects is challenging. Because of the characteristics of a deformable object, the manufacturing task cannot be standardized. However, relying solely on image sensors is not advisable, due to the challenges involved in recognizing complex cables with image sensors. Additionally, even when cable recognition is possible, it requires too much time. To address these issues, this paper introduces a strategic algorithm for the wiring harness assembly process. The algorithm minimizes the dependence on image sensors by enabling the use of a robotic dual-arm system. The proposed method includes techniques such as cable estimation, frictional models, and trajectory planning in the algorithms. On the basis of these methods, for a provided assembly board, the algorithm outputs a systematic process for wiring harness assembly. Experimental results validate the algorithm, demonstrating its good performance.

各种各样的电子产品在日常使用中服务于各种需求。电子产品需要不同类型的电缆线束进行生产。如今，用户偏好变化很大，变化很快。因此，制作各种小批量产品，生产各种复杂的线束来满足人们的需求是很困难的。在机器人自动化中，可变形物体制造中的线束装配过程具有挑战性。由于可变形物体的特性，制造任务无法标准化。然而，仅仅依靠图像传感器是不可取的，因为使用图像传感器识别复杂电缆所涉及的挑战。此外，即使有线识别是可能的，也需要太多的时间。针对这些问题，本文提出了一种线束装配过程的策略算法。该算法通过启用机器人双臂系统，最大限度地减少了对图像传感器的依赖。该方法在算法中包含了电缆估计、摩擦模型和轨迹规划等技术。在这些方法的基础上，对于所提供的装配板，该算法输出线束装配的系统化过程。实验结果验证了该算法的有效性。

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引用次数: 0

Robotic grinding of curved parts with two degrees of freedom active compliant force-controlled end-effector using decoupling control algorithm 基于解耦控制算法的二自由度主动柔性末端执行器曲面零件机器人磨削研究

IF 9.1 1区计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Robotics and Computer-integrated Manufacturing

Pub Date : 2024-12-23 DOI: 10.1016/j.rcim.2024.102935

Haiqing Chen, Jixiang Yang, Han Ding

This paper proposes a novel two degrees of freedom (2-DOF) active compliant force-controlled end-effector (EE) using decoupling control algorithm to improve grinding efficiency, material removal accuracy, and surface quality of the curved parts for robotic grinding. First, a robotic grinding system is described, which consists of an industrial robot for tool-path control and a novel 2-DOF compliant EE to improve grinding efficiency and compliance. Second, the dynamic relationship between the friction coefficient and the normal force is established to develop an online prediction model for the normal force. The tangential tool tip displacement model is also established. A force-position decoupling control algorithm, which comprises force–position decoupling and fuzzy force–position switching controllers, is then proposed to improve the normal force and the tangential tool tip displacement control accuracy of the 2-DOF compliant EE. Finally, the developed methodology is validated through grinding experiments to confirm its effectiveness. The grinding results show that under the premise of ensuring the neglectable tangential tool tip displacement error to the original grinding process, the developed 2-DOF compliant EE with decoupling control demonstrates similar high force control accuracy and grinding depth accuracy to the 1-DOF compliant EE, and the machining efficiency is improved by approximately 30 % compared to that of the 1-DOF compliant EE. Compared with the traditional 2-DOF rigid EE using hybrid control, the normal force and tangential tool tip displacement control errors of the developed 2-DOF compliant EE with decoupling control are reduced by approximately 60 % and 33 %, respectively, and the overshoot is reduced from 30 % to almost 0. The developed 2-DOF compliant EE with decoupling control improves the grinding depth accuracy and surface quality compared to the traditional 2-DOF rigid EE with hybrid control.

为了提高机器人磨削加工曲面零件的磨削效率、材料去除精度和表面质量，提出了一种采用解耦控制算法的二自由度主动柔性末端执行器。首先，介绍了一种机器人磨削系统，该系统由一个用于刀具轨迹控制的工业机器人和一个新型的2自由度柔性EE组成，以提高磨削效率和顺应性。其次，建立摩擦系数与法向力之间的动态关系，建立法向力在线预测模型；建立了切向刀尖位移模型。提出了一种由力-位置解耦和模糊力-位置切换控制器组成的力-位置解耦控制算法，以提高二自由度柔性机械臂的法向力和切向刀尖位移控制精度。最后，通过磨削实验验证了该方法的有效性。磨削结果表明，在保证刀尖切向位移误差对原磨削过程可忽略不计的前提下，采用解耦控制的二自由度柔性EE具有与一自由度柔性EE相似的高力控制精度和磨削深度精度，加工效率比一自由度柔性EE提高了约30%。与采用混合控制的传统2-DOF刚性EE相比，采用解耦控制的2-DOF柔性EE法向力和切向刀尖位移控制误差分别降低了约60%和33%，超调量从30%降至接近0。采用解耦控制的二自由度柔性EE与传统的混合控制的二自由度刚性EE相比，提高了磨削深度精度和表面质量。

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引用次数: 0

DFGAT for recognizing design features from a B-rep model for mechanical parts 从机械零件的B-rep模型中识别设计特征的DFGAT

IF 9.1 1区计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Robotics and Computer-integrated Manufacturing

Pub Date : 2024-12-21 DOI: 10.1016/j.rcim.2024.102938

Jun Hwan Park , Seungeun Lim , Changmo Yeo , Youn-Kyoung Joung , Duhwan Mun

Design feature recognition plays a crucial role in digital manufacturing and is a key technology in automatic design verification. Traditional methods and deep learning approaches provide various strategies for feature recognition. However, these methods primarily address part classification or machining feature recognition, with limited research focusing on design feature recognition. To address this gap, a novel deep learning network called the design feature graph attention network (DFGAT) was proposed specifically for design feature recognition. In this study, the original boundary representation (B-rep) model is first converted into graph representation. Design feature recognition is then achieved using the DFGAT, which is based on the GAT. Additionally, the dataset generation process was generalized to efficiently train the deep learning model. To validate the performance of the DFGAT, experiments were conducted to recognize the representative faces of design features, such as snap-fit hooks, cups, and plates, in the EIF_Panel, Real_Panel, and Anemometer models. The experiments demonstrated F1-scores of 0.9924, 0.9982, and 1.0000.

设计特征识别在数字化制造中起着至关重要的作用，也是自动设计验证的一项关键技术。传统方法和深度学习方法为特征识别提供了各种策略。然而，这些方法主要针对零件分类或加工特征识别，而针对设计特征识别的研究却非常有限。针对这一空白，我们提出了一种专门用于设计特征识别的新型深度学习网络--设计特征图注意力网络（DFGAT）。在这项研究中，首先将原始的边界表示（B-rep）模型转换为图表示。然后使用基于 GAT 的 DFGAT 实现设计特征识别。此外，还对数据集生成过程进行了通用化，以高效地训练深度学习模型。为了验证 DFGAT 的性能，我们在 EIF_Panel、Real_Panel 和 Anemometer 模型中对设计特征的代表面进行了识别实验，如卡扣式挂钩、杯子和盘子。实验结果表明，F1 分数分别为 0.9924、0.9982 和 1.0000。

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引用次数: 0

A contour error prediction method for tool path correction using a multi-feature hybrid model in robotic milling systems 机器人铣削系统中使用多特征混合模型进行刀具路径修正的轮廓误差预测方法

IF 9.1 1区计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Robotics and Computer-integrated Manufacturing

Pub Date : 2024-12-21 DOI: 10.1016/j.rcim.2024.102936

Shizhong Tan , Congcong Ye , Chengxing Wu , Jixiang Yang , Han Ding

Achieving high precision in robotic milling presents significant challenges due to inherent errors caused by various factors such as robot stiffness deformation and uneven machining allowances in large workpieces. Traditional error corrected methods often fall short in effectively addressing the complexity and dynamic nature of such errors. To address these challenges, a contour error prediction model has been proposed by using a combination of Gaussian Processes and a CNN-BiLSTM architecture. Firstly, extract the potential error features, including the robot's posture and stiffness information, as well as the workpiece's machining allowance during the milling process. Then, process these features to create a uniformly structured training set. Subsequently, develop a CNN-BiLSTM neural network model to realize an accurate contour error prediction, where the CNN layers are responsible for extracting hidden local features from the structured data, while the BiLSTM layers capture temporal correlations and hidden features related to tool path. Finally, validate on a saddle-shaped workpiece with surface features similar to those found in aero-engine casing cavities. The results demonstrate that the fusion-based error prediction model effectively reduces the maximum contour error from 0.9629 mm to 0.4881 mm, and decreases the mean absolute contour error from 0.7171 mm to 0.3048mm, representing reductions of 49.30 % and 57.40 %, respectively. These reductions well validate the effectiveness of the proposed method.

由于机器人刚度变形和大型工件加工余量不均等各种因素造成的固有误差，在机器人铣削加工中实现高精度是一项重大挑战。传统的误差修正方法往往无法有效解决此类误差的复杂性和动态性。为了应对这些挑战，我们结合高斯过程和 CNN-BiLSTM 架构，提出了一种轮廓误差预测模型。首先，提取潜在误差特征，包括机器人的姿势和刚度信息，以及铣削过程中工件的加工余量。然后，处理这些特征，创建结构统一的训练集。然后，开发一个 CNN-BiLSTM 神经网络模型来实现精确的轮廓误差预测，其中 CNN 层负责从结构化数据中提取隐藏的局部特征，而 BiLSTM 层则捕捉与刀具路径相关的时间相关性和隐藏特征。最后，在一个鞍形工件上进行验证，该工件的表面特征与航空发动机机壳型腔中的表面特征相似。结果表明，基于融合的误差预测模型有效地将最大轮廓误差从 0.9629 毫米减少到 0.4881 毫米，将平均绝对轮廓误差从 0.7171 毫米减少到 0.3048 毫米，分别减少了 49.30 % 和 57.40 %。这些误差的减少充分验证了建议方法的有效性。

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引用次数: 0

Synthesis and prototyping of a backdrivable parallel robot for metal finishing tasks

IF 9.1 1区计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Robotics and Computer-integrated Manufacturing

Pub Date : 2024-12-20 DOI: 10.1016/j.rcim.2024.102934

Pierre-Luc Beaulieu, Thierry Laliberté, Simon Foucault, Clément Gosselin

This article presents the synthesis, control and experimental validation of a backdrivable three-degree-of-freedom translational mini robot used to control the interaction between a robot and a machined part during finishing tasks, such as polishing, sanding and deburring without requiring the use of a force/torque sensor. The mini robot acts as an active contact flange, allowing an industrial robot (the macro robot) to adapt to a part using an impedance control algorithm. Firstly, different three-degree-of-freedom parallel robot architectures are compared and the most suitable architecture is selected. Geometrical properties are chosen for the robot and the physical capabilities of the architecture are predicted to ensure that the design criteria are satisfied. An impedance control algorithm is then developed for the mini robot. The macro-mini system is formed by installing the mini robot on a gantry robot. Sanding tests are carried out in order to validate the performance of the system and the mini robot is compared to other contact flanges already available on the market. Finally, a method allowing the determination of the magnitude of the friction forces in the mini robot is presented and a preliminary friction compensation algorithm is developed. As opposed to existing tools, the novel mini robot proposed in this work is based on a compact parallel architecture, which makes it possible to ensure the backdrivability of the system in three directions. An impedance control algorithm can therefore be implemented thereby providing stability even with stiff environments and eliminating the need for a force/torque sensor.

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引用次数: 0

A unified sampling method for optimal feature coverage and robot placement 优化特征覆盖和机器人位置的统一采样方法

IF 9.1 1区计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Robotics and Computer-integrated Manufacturing

Pub Date : 2024-12-19 DOI: 10.1016/j.rcim.2024.102932

Domenico Spensieri, Edvin Å blad, Raad Salman, Johan S. Carlson

Designing a robot line includes the critical decision about the number of robots needed to carry out all the tasks in the stations and their placement. Similarly, having a robot manipulator mounted on a mobile base, such as an Automated Guided Vehicle (AGV), needs a careful choice of the base positions to minimize cycle time for the operations. In this paper, we solve both the robot placement and the AGV positioning problems by relating them to feature coverage applications, where the challenge is to place cameras (or other sensors) to inspect all points on a workpiece for metrology tasks. These similarities allow us to design an efficient divide&conquer-based algorithm which can be adapted to solve all three problems above, where finding the minimum number of positions for sensors, AGVs and robots is crucial to reduce cycle time and costs.

The algorithm is divided in two parts: the first one is responsible for identifying candidate positions, whereas the second solves a set covering problem. We show that these two parts can even be interlaced to obtain high-quality solutions in short time.

A successful computational study has been carried out with both artificial instances and three industrial scenarios, ranging from laser sensor inspection cells in the aerospace industry, to an automated cleaning room, and ending with a stud welding station for automotive applications.

The results show that geometric and industrial tests, even accounting for kinematics and distance queries, can be handled with high accuracy in reasonable computing time.

机器人生产线的设计包括对在各工位执行所有任务所需的机器人数量及其位置进行关键决策。同样，将机器人机械手安装在移动底座（如自动导引车（AGV））上，也需要谨慎选择底座位置，以尽量缩短操作周期。在本文中，我们通过将机器人放置和 AGV 定位问题与特征覆盖应用联系起来来解决这两个问题，在特征覆盖应用中，我们面临的挑战是放置摄像头（或其他传感器）来检测工件上的所有点，以完成计量任务。这些相似之处使我们能够设计出一种基于分而治之的高效算法，该算法可用于解决上述所有三个问题，在这些问题中，找到传感器、AGV 和机器人的最小位置数对于减少周期时间和成本至关重要。

{"title":"A unified sampling method for optimal feature coverage and robot placement","authors":"Domenico Spensieri, Edvin Å blad, Raad Salman, Johan S. Carlson","doi":"10.1016/j.rcim.2024.102932","DOIUrl":"10.1016/j.rcim.2024.102932","url":null,"abstract":"<div><div>Designing a robot line includes the critical decision about the number of robots needed to carry out all the tasks in the stations and their placement. Similarly, having a robot manipulator mounted on a mobile base, such as an Automated Guided Vehicle (AGV), needs a careful choice of the base positions to minimize cycle time for the operations. In this paper, we solve both the robot placement and the AGV positioning problems by relating them to feature coverage applications, where the challenge is to place cameras (or other sensors) to inspect all points on a workpiece for metrology tasks. These similarities allow us to design an efficient divide&conquer-based algorithm which can be adapted to solve all three problems above, where finding the minimum number of positions for sensors, AGVs and robots is crucial to reduce cycle time and costs.</div><div>The algorithm is divided in two parts: the first one is responsible for identifying candidate positions, whereas the second solves a set covering problem. We show that these two parts can even be interlaced to obtain high-quality solutions in short time.</div><div>A successful computational study has been carried out with both artificial instances and three industrial scenarios, ranging from laser sensor inspection cells in the aerospace industry, to an automated cleaning room, and ending with a stud welding station for automotive applications.</div><div>The results show that geometric and industrial tests, even accounting for kinematics and distance queries, can be handled with high accuracy in reasonable computing time.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"93 ","pages":"Article 102932"},"PeriodicalIF":9.1,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142867626","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

Jerk-optimal force and motion synchronous planning for a 3-DOF translational force-controlled end-effector 3-DOF 平移力控末端执行器的 "搐动 "优化力和运动同步规划

IF 9.1 1区计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Robotics and Computer-integrated Manufacturing

Pub Date : 2024-12-19 DOI: 10.1016/j.rcim.2024.102931

Guolong Zhang , Guilin Yang , Yimin Deng , Chin-yin Chen , Zaojun Fang , Junjie Li

The 3-DOF Translational Force-controlled End-effector (TFE) based on 3-P(UU)₂ Parallel Mechanism (PM) and pneumoelectric actuator is developed for polishing process performed by industrial robots, in which synchronous force and motion planning is critical to enhance the polishing performance. However, conventional planning methods are mainly developed to generate the trajectory for robotic motion control. Utilizing periodic splines, a new jerk-optimal Force and Motion Synchronous Planning (FMSP) method is proposed for the 3-DOF TFE to improve the force control stability between the tool and environment. Both the kinematics of the 3-DOF translational PM and the dynamics of the hybrid serial-parallel and macro-mini robotic system are established through screw theory. By introducing septuple B-splines for motion trajectory and cubic splines for contact force with periodic boundary conditions, the jerk-optimal performance index of motion and force is employed to formulate the FMSP model in Cartesian space. Simulation and experimental results demonstrate that the high-order continuity of the active driving force, moving acceleration and jerk-optimal performance index generated by FMSP is preferable compared to the Trajectory Planning with Point-to-point Force (TPWPF) and the Force-motion Linear Interpolation (FMLI) methods. The unloaded force peaks caused by the motion impact are reduced by 21 % and 22.6 % along x and y direction, respectively. Furthermore, the peaks of the contact force between the tool and workpiece decrease by 31.5 % and 20.4 % owing to slighter systemic vibration and impact. The FMSP method for force-controlled end-effector shows great potential in robotic continuous contact operations.

基于3-P(UU)2并联机构（PM）和气动执行器的3-DOF平移力控制末端执行器（TFE）用于工业机器人的抛光过程，其中同步力和运动规划是提高抛光性能的关键。然而，传统的规划方法主要用于生成机器人运动控制的轨迹。为了提高刀具与环境之间的力控制稳定性，提出了一种基于周期样条曲线的三自由度TFE力与运动同步优化规划方法。利用螺旋理论建立了平移式三自由度永磁机器人的运动学和串-并联和宏-微型混合机器人系统的动力学。通过在周期边界条件下引入七次b样条运动轨迹和三次接触力，利用运动和力的跳变最优性能指标在笛卡尔空间中建立了FMSP模型。仿真和实验结果表明，与点对点力轨迹规划（TPWPF）和力-运动线性插值（FMLI）方法相比，FMSP生成的主动驱动力、运动加速度和跳变优化性能指标具有较高的连续性。运动冲击引起的卸载力峰值沿x和y方向分别降低了21%和22.6%。此外，由于较轻的系统振动和冲击，刀具与工件之间的接触力峰值降低了31.5%和20.4%。力控末端执行器的FMSP方法在机器人连续接触操作中显示出巨大的潜力。

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引用次数: 0

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 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

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

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.

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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 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

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

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.

通过集成协作机器人增材制造（C-RAAM）平台，增材制造（AM）技术取得了重大进展。通过在多个机械臂的末端执行器上部署增材制造工艺，不仅可以规避诸如有限的构建体积等传统限制，而且还可以实现加速的制造速度、协同传感能力和原位多材料沉积。尽管取得了进步，但挑战仍然存在，特别是关于缺陷的产生，包括空洞、裂纹和残余应力。各种因素导致了这些问题，包括刀具路径规划（即，切片策略），协作打印的零件分解，以及运动规划（即，路径和轨迹规划）。本文首先考察了C-RAAM系统控制的关键方面，包括切片和运动规划。通过调整这些方面和增材制造方法的工艺参数来减轻缺陷的方法，然后在如何修改增材制造工艺的背景下进行描述：预处理、层间（即在层暂停期间）和中间层（即在材料沉积期间）。应用先进的传感技术，包括高分辨率相机，激光扫描仪和热成像，捕捉微，中观和宏观尺度的缺陷进行了探索。分析了数字孪生的作用，强调了它们模拟和预测制造结果的能力，从而能够先发制人地进行调整以防止缺陷。最后，概述了发展下一代C-RAAM系统的前景和未来机遇。

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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 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

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

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.

本研究的目的是在焊点形成之前预测其圆角轮廓。焊点对于电子组件的结构和操作可靠性至关重要，但其完整性可能因冷接头、空洞或焊料不足等缺陷而受到损害。传统的基于物理的模拟试图对这些现象进行建模，但由于无法捕捉到现实世界的可变性，因此往往无法进行简化。相反，数据驱动的方法利用表面贴装技术（SMT）生产线的历史数据来预测接头质量，尽管它们的有效性可能会受到数据噪声和不平衡的阻碍。针对这些限制，本研究引入了一个名为Sim2Joint的混合建模框架，该框架将基于物理知识的仿真与数据驱动方法的适应性相结合。通过在联合仿真领域引入Sim2Real， Sim2Joint通过将打印和放置因素的动态权重与现实世界数据相结合，弥合了模拟和现实世界情况之间的差距，提高了预测的准确性和可靠性。该框架还包括不确定性量化，以提供更可靠的焊点圆角轮廓预测，从而在SMT工艺中实现更好的决策和优化。Sim2Joint在各种基线下进行了验证，展示了其适应实时变化的能力，并提高了焊点质量评估的预测性能。

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引用次数: 0