A method of 3-D measuring fixture automatic assembly for auto-body part is presented. Locating constraint mapping technique and assembly rule-based reasoning are applied. Calculating algorithm of the position and pose...A method of 3-D measuring fixture automatic assembly for auto-body part is presented. Locating constraint mapping technique and assembly rule-based reasoning are applied. Calculating algorithm of the position and pose for the part model, fixture configuration and fixture elements in virtual auto-body assembly space are given. Transforming fixture element from itself coordinate system space to assembly space with homogeneous transformation matrix is realized. Based on the second development technique of unigraphics(UG), the automated assembly is implemented with application program interface (API) function. Lastly the automated assembly of measuring fixture for rear longeron as a case is implemented.展开更多
For auto-body product, assembly dimensional quality evaluation using tolerance analysis method is a challenging task because there are plenty of elements impacting on the variation stack-up and propagation during asse...For auto-body product, assembly dimensional quality evaluation using tolerance analysis method is a challenging task because there are plenty of elements impacting on the variation stack-up and propagation during assembly process. Traditional method of dimension chain generation based on tolerance charting technique can not suit the case of auto-body assembly. This paper proposed a method to generate dimension chain based on developing a jot chain model of assembly, which can be integrated with important information needed for variation analysis, such as joints types and assembly sequences. The implementation of such a procedure will contribute to rapid evaluation of body dimensional quality in the design stage.展开更多
Purpose–Dimensional quality of sheet metal assemblies is an important factor for the final product.However,the part tolerance is not easily controlled because of the spring back deformation during the stamping proces...Purpose–Dimensional quality of sheet metal assemblies is an important factor for the final product.However,the part tolerance is not easily controlled because of the spring back deformation during the stamping process.Selective assembly is a means to decrease assembly tolerance of the assembly from low-precision components.Therefore,the purpose of this paper is to propose a fully efficient method of selective assembly optimization based on an improved genetic algorithm for optimization toolbox(IGAOT)in MATLAB.Design/methodology/approach–The method of influence coefficient is first applied to calculate the assembly variation of sheet metal components since the traditional rigid assembly variation model cannot be used due to welding deformation.Afterwards,the IGAOT is proposed to generate optimal selective groups,which consists of advantages of genetic algorithm for optimization toolbox(GAOT)and simulated annealing.Findings–The cases of two simple planes and the tail lamp bracket assembly are used to illustrate the flowchart of optimizing combinations of selective groups.These cases prove that the proposed IGAOT has better precision than that of GAOT with the same parameters for selective assembly.Originality/value–The research objective of this paper is to evaluate the changes from rigid bodies to sheet metal parts which are very complex for selective assembly.The method of IGAOT was proposed to the selected groups which has better precision than that of current optimization algorithms.展开更多
Sheet metal is widely used on auto-bodies, plane-bodies and metal furniture, etc. For instance, a typical auto-body commonly consists of hundreds of sheet metal stamping parts. Because of its complexity of structure a...Sheet metal is widely used on auto-bodies, plane-bodies and metal furniture, etc. For instance, a typical auto-body commonly consists of hundreds of sheet metal stamping parts. Because of its complexity of structure and manufacturing process, auto-bodies inevitably have geometrical variation results from a number of different sources, such as the geometrical variation of stamping parts, the transformation of assembly process parameters and even the improper design concept. As more than 30% quality defects of an auto-body are born from the dimensional deviation of Body-In-White originated during the manufacturing process, effective diagnosis and control of dimensional faults are essential to the continuous improvement of the quality of vehicles. Especially during the period of new car launching or model changing when the assembly process was changed and adjusted frequently. For continuously improving the quality of modern cars, rapid dimensional variation causes identification becomes a challenging but essential work. In this paper, main variation causes of auto-body was firstly been cataloged and analyzed, then, a dimensional variation diagnostic reasoning and decision approach was developed through the combination of data mining and knowledge discovery techniques. This approach is driven by variation pattern identification which can be discovered from the dispersive, isolated massive measured data: Correlation Analysis (CA) and Maximal Tree (MT) methods were applied to extract the large variation group from massive multidimensional measured data, while multivariate statistical analysis (MSA) approach was used to discovery the principle variation pattern. A Decision Tree (DT) approach based on the knowledge of product and assembly process was developed to fulfill the "Hypothesis and Validation" characterized variation causes reasoning procedure. An practical application case with sudden and severe dimension variation on rear end panel in up/down direction was analyzed and successfully solved aided by the devloped variation diagnostic method, which have proved that the approach is effective and efficient.展开更多
Friction law is researched in rectangular parts deep drawing using simulation test ma-chine that is used to assess lubricants performance in deep drawing process. Friction coefficientsin different positions on die sur...Friction law is researched in rectangular parts deep drawing using simulation test ma-chine that is used to assess lubricants performance in deep drawing process. Friction coefficientsin different positions on die surface in deep drawing process are measured through probe sensors.Friction coefficients of flange corner, near straight border and far straight border are verified anddescribed quantitatively. It plays an important role in using appropriate lubricants in auto-bodypanel deep drawing process.展开更多
文摘A method of 3-D measuring fixture automatic assembly for auto-body part is presented. Locating constraint mapping technique and assembly rule-based reasoning are applied. Calculating algorithm of the position and pose for the part model, fixture configuration and fixture elements in virtual auto-body assembly space are given. Transforming fixture element from itself coordinate system space to assembly space with homogeneous transformation matrix is realized. Based on the second development technique of unigraphics(UG), the automated assembly is implemented with application program interface (API) function. Lastly the automated assembly of measuring fixture for rear longeron as a case is implemented.
基金National Natural Science Foundation of China(No.50375092)
文摘For auto-body product, assembly dimensional quality evaluation using tolerance analysis method is a challenging task because there are plenty of elements impacting on the variation stack-up and propagation during assembly process. Traditional method of dimension chain generation based on tolerance charting technique can not suit the case of auto-body assembly. This paper proposed a method to generate dimension chain based on developing a jot chain model of assembly, which can be integrated with important information needed for variation analysis, such as joints types and assembly sequences. The implementation of such a procedure will contribute to rapid evaluation of body dimensional quality in the design stage.
文摘Purpose–Dimensional quality of sheet metal assemblies is an important factor for the final product.However,the part tolerance is not easily controlled because of the spring back deformation during the stamping process.Selective assembly is a means to decrease assembly tolerance of the assembly from low-precision components.Therefore,the purpose of this paper is to propose a fully efficient method of selective assembly optimization based on an improved genetic algorithm for optimization toolbox(IGAOT)in MATLAB.Design/methodology/approach–The method of influence coefficient is first applied to calculate the assembly variation of sheet metal components since the traditional rigid assembly variation model cannot be used due to welding deformation.Afterwards,the IGAOT is proposed to generate optimal selective groups,which consists of advantages of genetic algorithm for optimization toolbox(GAOT)and simulated annealing.Findings–The cases of two simple planes and the tail lamp bracket assembly are used to illustrate the flowchart of optimizing combinations of selective groups.These cases prove that the proposed IGAOT has better precision than that of GAOT with the same parameters for selective assembly.Originality/value–The research objective of this paper is to evaluate the changes from rigid bodies to sheet metal parts which are very complex for selective assembly.The method of IGAOT was proposed to the selected groups which has better precision than that of current optimization algorithms.
文摘Sheet metal is widely used on auto-bodies, plane-bodies and metal furniture, etc. For instance, a typical auto-body commonly consists of hundreds of sheet metal stamping parts. Because of its complexity of structure and manufacturing process, auto-bodies inevitably have geometrical variation results from a number of different sources, such as the geometrical variation of stamping parts, the transformation of assembly process parameters and even the improper design concept. As more than 30% quality defects of an auto-body are born from the dimensional deviation of Body-In-White originated during the manufacturing process, effective diagnosis and control of dimensional faults are essential to the continuous improvement of the quality of vehicles. Especially during the period of new car launching or model changing when the assembly process was changed and adjusted frequently. For continuously improving the quality of modern cars, rapid dimensional variation causes identification becomes a challenging but essential work. In this paper, main variation causes of auto-body was firstly been cataloged and analyzed, then, a dimensional variation diagnostic reasoning and decision approach was developed through the combination of data mining and knowledge discovery techniques. This approach is driven by variation pattern identification which can be discovered from the dispersive, isolated massive measured data: Correlation Analysis (CA) and Maximal Tree (MT) methods were applied to extract the large variation group from massive multidimensional measured data, while multivariate statistical analysis (MSA) approach was used to discovery the principle variation pattern. A Decision Tree (DT) approach based on the knowledge of product and assembly process was developed to fulfill the "Hypothesis and Validation" characterized variation causes reasoning procedure. An practical application case with sudden and severe dimension variation on rear end panel in up/down direction was analyzed and successfully solved aided by the devloped variation diagnostic method, which have proved that the approach is effective and efficient.
文摘Friction law is researched in rectangular parts deep drawing using simulation test ma-chine that is used to assess lubricants performance in deep drawing process. Friction coefficientsin different positions on die surface in deep drawing process are measured through probe sensors.Friction coefficients of flange corner, near straight border and far straight border are verified anddescribed quantitatively. It plays an important role in using appropriate lubricants in auto-bodypanel deep drawing process.