Purpose The 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/approach First, 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. Findings According 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/value The 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.
{"title":"Research on collaborative task assignment method of assembly line","authors":"Weilei Shen, Qiangqiang Jiang, Yang Yang","doi":"10.1108/aa-08-2020-0114","DOIUrl":"https://doi.org/10.1108/aa-08-2020-0114","url":null,"abstract":"\u0000Purpose\u0000The 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.\u0000\u0000\u0000Design/methodology/approach\u0000First, 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.\u0000\u0000\u0000Findings\u0000According 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.\u0000\u0000\u0000Originality/value\u0000The 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.\u0000","PeriodicalId":55448,"journal":{"name":"Assembly Automation","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2021-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45637540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Purpose This 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/approach First, 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. Findings The 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/value First, 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.
{"title":"A peg-in-hole controller for cable-driven serial robots with compliant wrist based on cable tensions and joint positions","authors":"Ya’Nan Lou, Pengkun Quan, Haoyu Lin, Zhuo Liang, Dongbo Wei, Shichun Di","doi":"10.1108/aa-04-2021-0043","DOIUrl":"https://doi.org/10.1108/aa-04-2021-0043","url":null,"abstract":"\u0000Purpose\u0000This 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.\u0000\u0000\u0000Design/methodology/approach\u0000First, 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.\u0000\u0000\u0000Findings\u0000The 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.\u0000\u0000\u0000Originality/value\u0000First, 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.\u0000","PeriodicalId":55448,"journal":{"name":"Assembly Automation","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41675469","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Purpose This 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/approach Instead 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. Findings The 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/value Based 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.
{"title":"Continuous ergonomic risk perception for manual assembly operations using wearable multi-sensor posture estimation","authors":"Wei Fang, Mingyu Fu, Lianyu Zheng","doi":"10.1108/aa-03-2021-0027","DOIUrl":"https://doi.org/10.1108/aa-03-2021-0027","url":null,"abstract":"\u0000Purpose\u0000This 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.\u0000\u0000\u0000Design/methodology/approach\u0000Instead 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.\u0000\u0000\u0000Findings\u0000The 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.\u0000\u0000\u0000Originality/value\u0000Based 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.\u0000","PeriodicalId":55448,"journal":{"name":"Assembly Automation","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47091767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Purpose The 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/approach On 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. Findings The 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/value This 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.
{"title":"Fast and accurate detection of surface defect based on improved YOLOv4","authors":"J. Lian, Junhong He, Yun Niu, Tianze Wang","doi":"10.1108/aa-04-2021-0044","DOIUrl":"https://doi.org/10.1108/aa-04-2021-0044","url":null,"abstract":"\u0000Purpose\u0000The 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.\u0000\u0000\u0000Design/methodology/approach\u0000On 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.\u0000\u0000\u0000Findings\u0000The 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.\u0000\u0000\u0000Originality/value\u0000This 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.\u0000","PeriodicalId":55448,"journal":{"name":"Assembly Automation","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2021-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48427327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
H. Zhai, Wei Xiong, Fujin Li, Jie Yang, Dong-yang Su, Yongjun Zhang
Purpose The 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/approach In 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. Findings The 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/value A 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.
{"title":"Prediction of cold rolling gas based on EEMD-LSTM deep learning technology","authors":"H. Zhai, Wei Xiong, Fujin Li, Jie Yang, Dong-yang Su, Yongjun Zhang","doi":"10.1108/aa-02-2021-0018","DOIUrl":"https://doi.org/10.1108/aa-02-2021-0018","url":null,"abstract":"\u0000Purpose\u0000The 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.\u0000\u0000\u0000Design/methodology/approach\u0000In 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.\u0000\u0000\u0000Findings\u0000The 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.\u0000\u0000\u0000Originality/value\u0000A 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.\u0000","PeriodicalId":55448,"journal":{"name":"Assembly Automation","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44657879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Purpose The 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/approach Using 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. Findings The 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/value The 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.
{"title":"Design of adaptive sliding mode controller applied to ultrasonic motor","authors":"Gangfeng Yan","doi":"10.1108/aa-04-2021-0048","DOIUrl":"https://doi.org/10.1108/aa-04-2021-0048","url":null,"abstract":"\u0000Purpose\u0000The 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.\u0000\u0000\u0000Design/methodology/approach\u0000Using 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.\u0000\u0000\u0000Findings\u0000The 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.\u0000\u0000\u0000Originality/value\u0000The 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.\u0000","PeriodicalId":55448,"journal":{"name":"Assembly Automation","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2021-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43200443","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hanqing Gong, Lingling Shi, Xiangqian Zhai, Yimin Du, Zhijing Zhang
Purpose The 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/approach By 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. Findings By 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/value The 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.
{"title":"Assembly process case matching based on a multilevel assembly ontology method","authors":"Hanqing Gong, Lingling Shi, Xiangqian Zhai, Yimin Du, Zhijing Zhang","doi":"10.1108/aa-05-2021-0065","DOIUrl":"https://doi.org/10.1108/aa-05-2021-0065","url":null,"abstract":"\u0000Purpose\u0000The 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.\u0000\u0000\u0000Design/methodology/approach\u0000By 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.\u0000\u0000\u0000Findings\u0000By 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.\u0000\u0000\u0000Originality/value\u0000The 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.\u0000","PeriodicalId":55448,"journal":{"name":"Assembly Automation","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2021-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43938925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
N. Mazhar, F. Malik, R. A. Azim, A. Raza, Rameez Khan, Qasim Umar Khan
Purpose The 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/approach Newtonian 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. Findings The 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/value Multi-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.
{"title":"Full-state modeling and nonlinear control of balloon supported unmanned aerial vehicle","authors":"N. Mazhar, F. Malik, R. A. Azim, A. Raza, Rameez Khan, Qasim Umar Khan","doi":"10.1108/aa-03-2021-0031","DOIUrl":"https://doi.org/10.1108/aa-03-2021-0031","url":null,"abstract":"\u0000Purpose\u0000The 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).\u0000\u0000\u0000Design/methodology/approach\u0000Newtonian 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.\u0000\u0000\u0000Findings\u0000The 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.\u0000\u0000\u0000Originality/value\u0000Multi-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.\u0000","PeriodicalId":55448,"journal":{"name":"Assembly Automation","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2021-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44877277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Purpose This 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/approach First, 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. Findings Through 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/value In 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.
{"title":"Assembly variation analysis of the non-rigid assembly with a deformation gradient model","authors":"Ibrahim Ajani, Cong Lu","doi":"10.1108/aa-07-2021-0092","DOIUrl":"https://doi.org/10.1108/aa-07-2021-0092","url":null,"abstract":"\u0000Purpose\u0000This 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.\u0000\u0000\u0000Design/methodology/approach\u0000First, 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.\u0000\u0000\u0000Findings\u0000Through 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.\u0000\u0000\u0000Originality/value\u0000In 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.\u0000","PeriodicalId":55448,"journal":{"name":"Assembly Automation","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2021-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46888749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Purpose Complex 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/approach An 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. Findings The 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 implications The 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/value The 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。
{"title":"Discovery of key function module in complex mechanical 3D CAD assembly model for design reuse","authors":"Zhoupeng Han, Chenkai Tian, Zihan Zhou, Qilong Yuan","doi":"10.1108/aa-06-2021-0073","DOIUrl":"https://doi.org/10.1108/aa-06-2021-0073","url":null,"abstract":"\u0000Purpose\u0000Complex 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.\u0000\u0000\u0000Design/methodology/approach\u0000An 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.\u0000\u0000\u0000Findings\u0000The 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.\u0000\u0000\u0000Practical implications\u0000The 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.\u0000\u0000\u0000Originality/value\u0000The 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.\u0000","PeriodicalId":55448,"journal":{"name":"Assembly Automation","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2021-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44823263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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