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Research on collaborative task assignment method of assembly line 装配线协同任务分配方法研究
IF 2.1 4区 计算机科学 Q2 Engineering Pub Date : 2021-12-22 DOI: 10.1108/aa-08-2020-0114
Weilei Shen, Qiangqiang Jiang, Yang Yang
PurposeThe purpose of this paper is to construct a task assignment model for U-shaped production lines with collaborative task, which is optimized by minimizing the number of workers and balancing the workload of the operators. The ultimate goal is to increase productivity by increasing the U-line balance and balancing the load on the operators.Design/methodology/approachFirst, task selection and update mechanism are analyzed and the task selection mechanism suitable for collaborative task is proposed. Second, M-COMOSAL is obtained by improving the original COMOSAL. Finally, The M-COMOSAL algorithm and the COMAOSAL algorithm are used to perform job assignment on the double-acting clutch U-shaped assembly line.FindingsAccording to the allocation scheme obtained by M-COMSOAL, the beat can be adjusted according to the change of order demand. The final allocation scheme is superior to the COMSOAL algorithm in terms of number of workers, working time, production tempo and balance rate. In particular, compared with the old scheme, the new scheme showed a decrease of 16.7% in the number of employees and a 18.8% increase in the production line balance rate. Thus, the method is helpful to reduce the number of operators and balance the workload.Originality/valueThe new algorithm proposed in this paper for the assignment of collaborative task can minimize the number of workers and balance the load of operators, which is of great significance for improving the balance rate of U-shaped production lines and the utilization of personnel or equipment.
目的建立具有协同任务的U型生产线的任务分配模型,该模型通过最小化工人数量和平衡操作员工作量来进行优化。最终目标是通过增加U型线平衡和平衡操作员的负载来提高生产力。设计/方法论/方法首先,分析了任务选择和更新机制,提出了适合协同任务的任务选择机制。第二,M-COMOSAL是在原有COMOSAL的基础上改进得到的。最后,将M-COMOSAL算法和COMOSAL方法应用于双作用离合器U形装配线上的作业分配。Findings根据M-COMSOAL获得的分配方案,节拍可以根据订单需求的变化进行调整。最终的分配方案在工人数量、工作时间、生产节奏和平衡率方面优于COMSOAL算法。特别是,与旧方案相比,新方案的员工人数减少了16.7%,生产线平衡率增加了18.8%。因此,该方法有助于减少操作员数量和平衡工作量。独创性/价值本文提出的协同任务分配新算法可以最大限度地减少工人数量,平衡操作员的工作量,这对提高U型生产线的平衡率和人员或设备的利用率具有重要意义。
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引用次数: 1
A peg-in-hole controller for cable-driven serial robots with compliant wrist based on cable tensions and joint positions 基于电缆张力和关节位置的柔性手腕电缆驱动串行机器人孔内钉控制器
IF 2.1 4区 计算机科学 Q2 Engineering Pub Date : 2021-12-21 DOI: 10.1108/aa-04-2021-0043
Ya’Nan Lou, Pengkun Quan, Haoyu Lin, Zhuo Liang, Dongbo Wei, Shichun Di
PurposeThis purpose of this paper is to design a peg-in-hole controller for a cable-driven serial robot with compliant wrist (CDSR-CW) using cable tensions and joint positions. The peg is connected to the robot link through a CW. It is required that the controller does not rely on any external sensors such as 6-axis wrist force/torque (F/T) sensor, and only the compliance matrix’s estimated value of the CW is known.Design/methodology/approachFirst, the peg-in-hole assembly system based on a CDSR-CW is analyzed. Second, a characterization algorithm using micro cable tensions and joint positions to express the elastic F/T at the CW is established. Next, under the premise of only knowing the compliance matrix’s estimate, a peg-in-hole controller based on force/position hybrid control is proposed.FindingsThe experiment results show that the plug contact F/T can be tracked well. This verifies the validity and correctness of the characterization algorithm and peg-in-hole controller for CDSR-CWs in this paper.Originality/valueFirst, to the authors’ knowledge, there is no relevant work about the peg-in-hole assembly task using a CDSR-CW. Besides, the proposed characterization algorithm for the elastic F/T makes the peg-in-hole controller get rid of the dependence on the F/T sensor, which expands the application scenarios of the peg-in-hole controller. Finally, the controller does not require an accurate compliance matrix, which also increases its applicability.
目的本文的目的是利用电缆张力和关节位置为具有柔顺手腕的电缆驱动串行机器人(CDSR-CW)设计一种插孔控制器。销钉通过CW连接到机器人连杆。要求控制器不依赖于任何外部传感器,例如6轴手腕力/扭矩(F/T)传感器,并且只有顺应性矩阵的CW的估计值是已知的。设计/方法/途径首先,分析了基于CDSR-CW的孔内装配系统。其次,建立了一种利用微索张力和接头位置来表达连续波弹性F/T的表征算法。其次,在只知道柔度矩阵估计的前提下,提出了一种基于力/位置混合控制的嵌孔控制器。实验结果表明,插塞接触F/T可以很好地跟踪。这验证了本文提出的CDSR CWs特征化算法和孔内控制器的有效性和正确性。独创性/价值首先,据作者所知,目前还没有关于使用CDSR-CW的钻孔装配任务的相关工作。此外,所提出的弹性F/T的特征化算法使孔内控制器摆脱了对F/T传感器的依赖,拓展了孔内控制器的应用场景。最后,控制器不需要精确的顺应性矩阵,这也增加了它的适用性。
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引用次数: 0
Continuous ergonomic risk perception for manual assembly operations using wearable multi-sensor posture estimation 使用可穿戴多传感器姿态估计的手动装配操作的连续人体工程学风险感知
IF 2.1 4区 计算机科学 Q2 Engineering Pub Date : 2021-12-21 DOI: 10.1108/aa-03-2021-0027
Wei Fang, Mingyu Fu, Lianyu Zheng
PurposeThis paper aims to perform the real-time and accurate ergonomics analysis for the operator in the manual assembly, with the purpose of identifying potential ergonomic injuries when encountering labor-excessive and unreasonable assembly operations.Design/methodology/approachInstead of acquiring body data for ergonomic evaluation by arranging many observers around, this paper proposes a multi-sensor based wearable system to track worker’s posture for a continuous ergonomic assessment. Moreover, given the accurate neck postural data from the shop floor by the proposed wearable system, a continuous rapid upper limb assessment method with robustness to occasional posture changes, is proposed to evaluate the neck and upper back risk during the manual assembly operations.FindingsThe proposed method can retrieve human activity data during manual assembly operations, and experimental results illustrate that the proposed work is flexible and accurate for continuous ergonomic assessments in manual assembly operations.Originality/valueBased on the proposed multi-sensor based wearable system for posture acquisition, a real-time and high-precision ergonomics analysis is achieved with the postural data arrived continuously, it can provide a more objective indicator to assess the ergonomics during manual assembly.
本课题旨在对人工装配过程中的操作人员进行实时、准确的人机工程学分析,在遇到劳力过多、不合理的装配操作时,识别潜在的人机工程学伤害。设计/方法/方法:本文提出了一种基于多传感器的可穿戴系统,以跟踪工人的姿势,进行连续的人体工程学评估,而不是通过安排许多观察者来获取人体数据进行人体工程学评估。此外,考虑到所提出的可穿戴系统所提供的准确的车间颈部姿势数据,提出了一种对偶发姿势变化具有鲁棒性的连续快速上肢评估方法,用于评估人工装配过程中颈部和上背部的风险。实验结果表明,该方法能够有效地检索人工装配过程中的人体活动数据,为人工装配过程中的连续人机工程学评估提供了灵活、准确的方法。提出的基于多传感器的可穿戴姿态采集系统,通过连续采集的姿态数据,实现实时、高精度的人机工程学分析,为人工装配过程的人机工程学评估提供更客观的指标。
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引用次数: 2
Fast and accurate detection of surface defect based on improved YOLOv4 基于改进YOLOv4的表面缺陷快速准确检测
IF 2.1 4区 计算机科学 Q2 Engineering Pub Date : 2021-12-02 DOI: 10.1108/aa-04-2021-0044
J. Lian, Junhong He, Yun Niu, Tianze Wang
PurposeThe current popular image processing technologies based on convolutional neural network have the characteristics of large computation, high storage cost and low accuracy for tiny defect detection, which is contrary to the high real-time and accuracy, limited computing resources and storage required by industrial applications. Therefore, an improved YOLOv4 named as YOLOv4-Defect is proposed aim to solve the above problems.Design/methodology/approachOn the one hand, this study performs multi-dimensional compression processing on the feature extraction network of YOLOv4 to simplify the model and improve the feature extraction ability of the model through knowledge distillation. On the other hand, a prediction scale with more detailed receptive field is added to optimize the model structure, which can improve the detection performance for tiny defects.FindingsThe effectiveness of the method is verified by public data sets NEU-CLS and DAGM 2007, and the steel ingot data set collected in the actual industrial field. The experimental results demonstrated that the proposed YOLOv4-Defect method can greatly improve the recognition efficiency and accuracy and reduce the size and computation consumption of the model.Originality/valueThis paper proposed an improved YOLOv4 named as YOLOv4-Defect for the detection of surface defect, which is conducive to application in various industrial scenarios with limited storage and computing resources, and meets the requirements of high real-time and precision.
目前流行的基于卷积神经网络的图像处理技术具有计算量大、存储成本高、微小缺陷检测精度低的特点,与工业应用要求的实时性和准确性高、计算资源和存储空间有限的要求相悖。因此,针对上述问题,提出了一种改进型的YOLOv4,命名为YOLOv4- defect。设计/方法/途径本研究一方面对YOLOv4的特征提取网络进行多维压缩处理,简化模型,通过知识蒸馏提高模型的特征提取能力。另一方面,通过加入更细致的感受场预测尺度来优化模型结构,提高了对微小缺陷的检测性能。结果通过公共数据集NEU-CLS和DAGM 2007以及实际工业现场的钢锭数据集验证了该方法的有效性。实验结果表明,提出的YOLOv4-Defect方法可以大大提高识别效率和准确率,减小模型的尺寸和计算量。独创性/价值本文提出了一种改进的YOLOv4,命名为YOLOv4- defect,用于表面缺陷的检测,有利于在存储和计算资源有限的各种工业场景中应用,满足高实时性和精度的要求。
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引用次数: 2
Prediction of cold rolling gas based on EEMD-LSTM deep learning technology 基于EEMD-LSTM深度学习技术的冷轧气体预测
IF 2.1 4区 计算机科学 Q2 Engineering Pub Date : 2021-12-01 DOI: 10.1108/aa-02-2021-0018
H. Zhai, Wei Xiong, Fujin Li, Jie Yang, Dong-yang Su, Yongjun Zhang
PurposeThe prediction of by-product gas is an important guarantee for the full utilization of resources. The purpose of this research is to predict gas consumption to provide a basis for gas dispatch and reduce the production cost of enterprises.Design/methodology/approachIn this paper, a new method using the ensemble empirical mode decomposition (EEMD) and the back propagation neural network is proposed. Unfortunately, this method does not achieve the ideal prediction. Further, using the advantages of long short-term memory (LSTM) neural network for long-term dependence, a prediction method based on EEMD and LSTM is proposed. In this model, the gas consumption series is decomposed into several intrinsic mode functions and a residual term (r(t)) by EEMD. Second, each component is predicted by LSTM. The predicted values of all components are added together to get the final prediction result.FindingsThe results show that the root mean square error is reduced to 0.35%, the average absolute error is reduced to 1.852 and the R-squared is reached to 0.963.Originality/valueA new gas consumption prediction method is proposed in this paper. The production data collected in the actual production process is non-linear, unstable and contains a lot of noise. But the EEMD method has the unique superiority in the analysis data aspect and may solve these questions well. The prediction of gas consumption is the result of long-term training and needs a lot of prior knowledge. Relying on LSTM can solve the problem of long-term dependence.
目的副产气预测是资源充分利用的重要保证。本研究的目的是预测用气量,为用气调度提供依据,降低企业的生产成本。设计/方法/方法本文提出了一种基于集成经验模态分解(EEMD)和反向传播神经网络的方法。不幸的是,这种方法不能达到理想的预测。在此基础上,利用长短期记忆(LSTM)神经网络对长期依赖的优势,提出了一种基于EEMD和LSTM的预测方法。在该模型中,燃气消耗序列被EEMD分解为几个本征模态函数和一个残差项(r(t))。其次,利用LSTM对各分量进行预测。将各分量的预测值相加得到最终的预测结果。结果表明:均方根误差减小到0.35%,平均绝对误差减小到1.852,r方达到0.963。本文提出了一种新的燃气消耗量预测方法。实际生产过程中采集的生产数据是非线性的、不稳定的,并且含有大量的噪声。而EEMD方法在分析数据方面具有独特的优势,可以很好地解决这些问题。燃气消耗量的预测是长期训练的结果,需要大量的先验知识。依靠LSTM可以解决长期依赖的问题。
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引用次数: 3
Design of adaptive sliding mode controller applied to ultrasonic motor 应用于超声电机的自适应滑模控制器设计
IF 2.1 4区 计算机科学 Q2 Engineering Pub Date : 2021-11-23 DOI: 10.1108/aa-04-2021-0048
Gangfeng Yan
PurposeThe purpose of this paper is to achieve high-precision sliding mode control without chattering; the control parameters are easy to adjust, and the entire controller is easy to use in engineering practice.Design/methodology/approachUsing double sliding mode surfaces, the gain of the control signal can be adjusted adaptively according to the error signal. A kind of sliding mode controller without chattering is designed and applied to the control of ultrasonic motors.FindingsThe results show that for a position signal with a tracking amplitude of 35 mm, the traditional sliding mode control method has a maximum tracking error of 0.3326 mm under the premise of small chattering; the boundary layer sliding mode control method has a maximum tracking error of 0.3927 mm without chattering, and the maximum tracking error of continuous switching adaptive sliding mode control is 0.1589 mm, and there is no chattering. Under the same control parameters, after adding a load of 0.5 kg, the maximum tracking errors of the traditional sliding mode control method, the boundary layer sliding mode control method and the continuous switching adaptive sliding mode control are 0.4292 mm, 0.5111 mm and 0.1848 mm, respectively.Originality/valueThe proposed method not only switches continuously, but also the amplitude of the switching signal is adaptive, while maintaining the robustness of the conventional sliding mode control method, which has strong engineering application value.
本文的目的是实现无抖振的高精度滑模控制;控制参数易于调整,整个控制器在工程实践中易于使用。设计/方法/方法采用双滑模曲面,可以根据误差信号自适应调整控制信号的增益。设计了一种无抖振的滑模控制器,并将其应用于超声波电机的控制中。结果表明:对于跟踪幅度为35 mm的位置信号,在抖振较小的前提下,传统滑模控制方法的最大跟踪误差为0.3326 mm;边界层滑模控制方法的最大跟踪误差为0.3927 mm,无抖振,连续切换自适应滑模控制的最大跟踪误差为0.1589 mm,无抖振。在相同控制参数下,加入0.5 kg载荷后,传统滑模控制方法、边界层滑模控制方法和连续切换自适应滑模控制的最大跟踪误差分别为0.4292 mm、0.5111 mm和0.1848 mm。提出的方法不仅开关连续,而且开关信号的幅度是自适应的,同时保持了传统滑模控制方法的鲁棒性,具有较强的工程应用价值。
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引用次数: 6
Assembly process case matching based on a multilevel assembly ontology method 基于多级装配本体方法的装配过程案例匹配
IF 2.1 4区 计算机科学 Q2 Engineering Pub Date : 2021-11-23 DOI: 10.1108/aa-05-2021-0065
Hanqing Gong, Lingling Shi, Xiangqian Zhai, Yimin Du, Zhijing Zhang
PurposeThe purpose of this study is to achieve accurate matching of new process cases to historical process cases and then complete the reuse of process knowledge and assembly experience.Design/methodology/approachBy integrating case-based reasoning (CBR) and ontology technology, a multilevel assembly ontology is proposed. Under the general framework, the knowledge of the assembly domain is described hierarchically and associatively. On this basis, an assembly process case matching method is developed.FindingsBy fully considering the influence of ontology individual, case structure, assembly scenario and introducing the correction factor, the similarity between non-correlated parts is significantly reduced. Compared with the Triple Matching-Distance Model, the degree of distinction and accuracy of parts matching are effectively improved. Finally, the usefulness of the proposed method is also proved by the matching of four practical assembly cases of precision components.Originality/valueThe process knowledge in historical assembly cases is expressed in a specific ontology framework, which makes up for the defects of the traditional CBR model. The proposed matching method takes into account all aspects of ontology construction and can be used well in cross-ontology similarity calculations.
目的本研究的目的是实现新工艺案例与历史工艺案例的精确匹配,从而完成工艺知识和装配经验的重用。设计/方法论/方法将基于实例推理(CBR)和本体技术相结合,提出了一种多级装配本体。在通用框架下,对装配领域的知识进行了层次化和关联化描述。在此基础上,提出了一种装配工艺案例匹配方法。发现通过充分考虑本体个体、案例结构、装配场景的影响,并引入修正因子,显著降低了不相关部分之间的相似性。与三重匹配距离模型相比,有效地提高了零件匹配的区分程度和精度。最后,通过四个精密零件装配实例的匹配,验证了该方法的有效性。原创性/价值历史装配案例中的过程知识在特定的本体框架中表达,弥补了传统CBR模型的缺陷。所提出的匹配方法考虑了本体构建的各个方面,可以很好地用于跨本体相似度计算。
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引用次数: 4
Full-state modeling and nonlinear control of balloon supported unmanned aerial vehicle 气球支撑无人机全状态建模与非线性控制
IF 2.1 4区 计算机科学 Q2 Engineering Pub Date : 2021-11-18 DOI: 10.1108/aa-03-2021-0031
N. Mazhar, F. Malik, R. A. Azim, A. Raza, Rameez Khan, Qasim Umar Khan
PurposeThe purpose of this study is to provide the full-state mathematical model and devise a nonlinear controller for a balloon-supported unmanned aerial vehicle (BUAV).Design/methodology/approachNewtonian mechanics is used to establish the nonlinear mathematical model of the proposed vehicle assembly which incorporates the dynamics of both balloon and quadrotor UAV. A controllable form of the nine degrees of freedom model is derived. Backstepping control is designed for the proposed model and simulations are performed to assess the tracking performance of the proposed control.FindingsThe results show that the proposed methodology works well for smooth trajectories in presence of wind gusts. Moreover, the final mathematical model is affine and various nonlinear control techniques can be used in the future for improved system performance.Originality/valueMulti-rotor unmanned aerial vehicles (MUAVs) are equipped with controllers but are constrained by smaller flight endurance and payload carrying capability. On the contrary, lighter than air (LTA) aerial vehicles have longer flight times but have poor control performance for outdoor operations. One of the solutions to achieve better flight endurance and payload carrying capability is to augment the LTA balloon to MUAV. The novelty of this research lies in full-order mathematical modeling along with transformation to controllable form for the BUAV assembly.
目的为气球支撑式无人机(BUAV)提供全状态数学模型,并设计非线性控制器。设计/方法/方法采用牛顿力学建立了包含气球和四旋翼无人机动力学的飞行器总成的非线性数学模型。导出了九自由度模型的一种可控形式。针对所提模型设计了反步控制,并进行了仿真以评估所提控制的跟踪性能。研究结果表明,所提出的方法在有阵风的情况下可以很好地实现平滑轨迹。此外,最终的数学模型是仿射的,未来可以使用各种非线性控制技术来提高系统性能。多旋翼无人机(muav)配备了控制器,但受到较小的飞行续航力和有效载荷携带能力的限制。与之相反,轻于空气(LTA)飞行器的飞行时间较长,但在室外作业时控制性能较差。为了获得更好的飞行续航力和有效载荷携带能力,解决方案之一是将LTA气球扩展到MUAV。本研究的新颖之处在于对无人机装配进行了全阶数学建模,并将其转化为可控形式。
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引用次数: 2
Assembly variation analysis of the non-rigid assembly with a deformation gradient model 基于变形梯度模型的非刚性装配变型分析
IF 2.1 4区 计算机科学 Q2 Engineering Pub Date : 2021-11-18 DOI: 10.1108/aa-07-2021-0092
Ibrahim Ajani, Cong Lu
PurposeThis paper aims to develop a mathematical method to analyze the assembly variation of the non-rigid assembly, considering the manufacturing variations and the deformation variations of the non-rigid parts during the assembly process.Design/methodology/approachFirst, this paper proposes a deformation gradient model, which represents the deformation variations during the assembly process by considering the forces and the self-weight of the non-rigid parts. Second, the developed deformation gradient models from the assembly process are integrated into the homogenous transformation matrix to model the deformation variations and manufacturing variations of the deformed non-rigid part. Finally, a mathematical model to analyze the assembly variation propagation is developed to predict the dimensional and geometrical variations due to the manufacturing variations and the deformation variations during the assembly process.FindingsThrough the case study with a crosshead non-rigid assembly, the results indicate that during the assembly process, the individual deformation values of the non-rigid parts are small. However, the cumulative deformation variations of all the non-rigid parts and the manufacturing variations present a target value (w) of −0.2837 mm as compared to a target value of −0.3995 mm when the assembly is assumed to be rigid. The difference in the target values indicates that the influence of the non-rigid part deformation variations during the assembly process on the mechanical assembly accuracy cannot be ignored.Originality/valueIn this paper, a deformation gradient model is proposed to obtain the deformation variations of non-rigid parts during the assembly process. The small deformation variation, which is often modeled using a finite-element method in the existing works, is modeled using the proposed deformation gradient model and integrated into the nominal dimensions. Using the deformation gradient models, the non-rigid part deformation variations can be computed and the accumulated deformation variation can be easily obtained. The assembly variation propagation model is developed to predict the accuracy of the non-rigid assembly by integrating the deformation gradient models into the homogeneous transformation matrix.
目的本文旨在开发一种数学方法来分析非刚性组件的装配变化,考虑非刚性零件在装配过程中的制造变化和变形变化。设计/方法/方法首先,本文提出了一个变形梯度模型,该模型通过考虑非刚性零件的力和自重来表示装配过程中的变形变化。其次,将装配过程中开发的变形梯度模型集成到齐次变换矩阵中,以对变形的非刚性零件的变形变化和制造变化进行建模。最后,建立了一个分析装配变化传播的数学模型,以预测装配过程中由于制造变化和变形变化引起的尺寸和几何变化。通过对十字头非刚性装配的实例研究,结果表明,在装配过程中,非刚性零件的个体变形值较小。然而,所有非刚性零件的累积变形变化和制造变化的目标值(w)为−0.2837 mm,而目标值为−0.3995 当假定组件是刚性的时。目标值的差异表明,装配过程中非刚性零件变形变化对机械装配精度的影响不容忽视。独创性/价值本文提出了一个变形梯度模型来获得非刚性零件在装配过程中的变形变化。在现有工作中,通常使用有限元方法对小变形变化进行建模,使用所提出的变形梯度模型对其进行建模,并将其集成到标称尺寸中。使用变形梯度模型,可以计算非刚性零件的变形变化,并且可以容易地获得累积变形变化。通过将变形梯度模型集成到齐次变换矩阵中,开发了装配变化传播模型来预测非刚性装配的精度。
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引用次数: 2
Discovery of key function module in complex mechanical 3D CAD assembly model for design reuse 复杂机械三维CAD装配模型关键功能模块的发现与设计重用
IF 2.1 4区 计算机科学 Q2 Engineering Pub Date : 2021-11-17 DOI: 10.1108/aa-06-2021-0073
Zhoupeng Han, Chenkai Tian, Zihan Zhou, Qilong Yuan
PurposeComplex mechanical 3D computer-aided design (CAD) model embodies rich implicit design knowledge. Through discovering the key function parts and key function module in 3D CAD assembly model in advance, it can promote the designers’ understanding and reuse efficiency of 3D assembly model in design reuse.Design/methodology/approachAn approach for discovering key function module in complex mechanical 3D CAD assembly model is proposed. First, assembly network for 3D CAD assembly model is constructed, where the topology structure characteristics of 3D assembly model are analyzed based on complex network centrality. The degree centrality, closeness centrality, betweenness centrality and mutual information of node are used to evaluate the importance of the parts in 3D assembly model. Then, a multi-attribute decision model for part-node importance is established, and the comprehensive evaluation for key function parts in 3D assembly model is accomplished by combining Analytic Hierarchy Process and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). Subsequently, a community discovery of function module in assembly model-based Clauset–Newman–Moore (CNM)-Centrality is given in details. Finally, 3D CAD assembly model of worm gear reducer is taken as an example to verify the effectiveness and feasibility of proposed method.FindingsThe key function part in CAD assembly model is evaluated comprehensively considering assembly topology more objectively. In addition, the key function module containing key function part is discovered from CAD assembly model by using CNM-Centrality-based community discovery.Practical implicationsThe approach can be used for discovering important design knowledge from complex CAD assembly model when reusing the assembly model. It can help designers capture and understand the design thinking and intent, improve the reuse efficiency and quality.Originality/valueThe paper first proposes an approach for discovering key function module in complex mechanical 3D CAD assembly model taking advantage of complex network theory, where the key function part is evaluated using node centrality and TOPSIS, and the key function module is identified based on community discovery.
目的复杂机械三维计算机辅助设计(CAD)模型体现了丰富的隐性设计知识。通过提前发现三维CAD装配模型中的关键功能部件和关键功能模块,可以促进设计人员在设计复用中对三维CAD装配模型的理解和复用效率。提出了一种复杂机械三维CAD装配模型中关键功能模块的发现方法。首先,构建三维CAD装配模型的装配网络,基于复杂网络中心性分析三维装配模型的拓扑结构特征;利用节点的度中心性、紧密度中心性、中间度中心性和互信息来评价零件在三维装配模型中的重要性。在此基础上,建立了零件-节点重要性的多属性决策模型,并结合层次分析法和TOPSIS (Order Preference by Similarity by a Ideal Solution)对三维装配模型中关键功能零件进行了综合评价。随后,详细介绍了基于Clauset-Newman-Moore (CNM)中心性的装配模型中功能模块的群体发现。最后以蜗轮减速器的三维CAD装配模型为例,验证了所提方法的有效性和可行性。发现CAD装配模型中关键功能部分的综合评价更客观地考虑了装配拓扑。此外,利用基于cnm - centralality的社团发现,从CAD装配模型中发现包含关键功能部件的关键功能模块。实际意义该方法可用于从复杂的CAD装配模型中发现重要的设计知识。它可以帮助设计师捕捉和理解设计思维和意图,提高重用效率和质量。本文首先利用复杂网络理论提出了一种复杂机械三维CAD装配模型中关键功能模块的发现方法,利用节点中心性和TOPSIS对关键功能部件进行评估,并基于群体发现对关键功能模块进行识别。
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引用次数: 3
期刊
Assembly Automation
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