The Experts below are selected from a list of 1116 Experts worldwide ranked by ideXlab platform

Gao Qingfeng - One of the best experts on this subject based on the ideXlab platform.

  • assembly sequence planning method based on semantic engineering information and precedence Constraint matrix
    Computer Simulation, 2008
    Co-Authors: Gao Qingfeng
    Abstract:

    Virtual Assembly, a key branch of virtual manufacturing, not only provides an effective way to reduce cost of product development and shorten time to market, but also improves quality of product itself. An assembly sequence planning method mainly was proposed based on two parts: one is semantic engineering information (SEI) derived from human-computer interaction (HCI) dialogs, the other is precedence Constraint matrix (PCM) deduced by each component’s Mating Constraint relations, geometric figure, topology information and movable direction set (MDS). After modification of original interference, it is easy to generate all feasible even optimal assembly sequences according to PCM at the engineering point. In the end, a simulative model was taken to verify the method’s validity in an application development system of Pro/Engineer (Pro/E) named virtual assembly support system (VASS) 2000.

Yuankun Gui - One of the best experts on this subject based on the ideXlab platform.

  • IMECE2008-68236 A VARIANT MODULE DIVISION METHOD ON EXTENSION LOGIC FOR ASSEMBLY PROCESS
    2020
    Co-Authors: Yanwei Zhao, Li Xing, Meiyan Zhang, Yuankun Gui
    Abstract:

    ABSTRACT The paper's focus is on the module division dynamically in the virtual assembly sequencing process for the product family, which will affect the module variant quality seriously. Most research merely divides the module on their functions, without paying the attention on which the module division is beneficial for the latter assembly process. Considered assembly relationships as a key Constraint, a new variant module division measure based on Extension Logic is presented. Since the tolerances existing everywhere in the assembly process, the connection analysis is employed to build a Constraint function on the tolerance. Physical Constraints contain Mating and combination Constraints. After the dynamical position for different parts, the Mating Constraint is defined as the movement opposition between two mechanical elements including face alignment Mating, shaft and hole Mating or face against Mating. Then the extension radiation model could be generated. According the average value of the relationship function to realize the module division, the product structure is divided into several sub-assemblies. As the main problem in virtual assembly is process collisions, a modified integer coded Particle Swarm Optimization Algorithm is used. Here every part is mapped to corresponding particle. The result is performed in the virtual environment of software DELMIA. At last the extension cluster method in this paper is compared with the direct dynamic cluster method. A case study is performed on virtual assembly of high power Light Emitting Diodes automatic sorting machine manufactured by a factory

Yanwei Zhao - One of the best experts on this subject based on the ideXlab platform.

  • IMECE2008-68236 A VARIANT MODULE DIVISION METHOD ON EXTENSION LOGIC FOR ASSEMBLY PROCESS
    2020
    Co-Authors: Yanwei Zhao, Li Xing, Meiyan Zhang, Yuankun Gui
    Abstract:

    ABSTRACT The paper's focus is on the module division dynamically in the virtual assembly sequencing process for the product family, which will affect the module variant quality seriously. Most research merely divides the module on their functions, without paying the attention on which the module division is beneficial for the latter assembly process. Considered assembly relationships as a key Constraint, a new variant module division measure based on Extension Logic is presented. Since the tolerances existing everywhere in the assembly process, the connection analysis is employed to build a Constraint function on the tolerance. Physical Constraints contain Mating and combination Constraints. After the dynamical position for different parts, the Mating Constraint is defined as the movement opposition between two mechanical elements including face alignment Mating, shaft and hole Mating or face against Mating. Then the extension radiation model could be generated. According the average value of the relationship function to realize the module division, the product structure is divided into several sub-assemblies. As the main problem in virtual assembly is process collisions, a modified integer coded Particle Swarm Optimization Algorithm is used. Here every part is mapped to corresponding particle. The result is performed in the virtual environment of software DELMIA. At last the extension cluster method in this paper is compared with the direct dynamic cluster method. A case study is performed on virtual assembly of high power Light Emitting Diodes automatic sorting machine manufactured by a factory

Li Xing - One of the best experts on this subject based on the ideXlab platform.

  • IMECE2008-68236 A VARIANT MODULE DIVISION METHOD ON EXTENSION LOGIC FOR ASSEMBLY PROCESS
    2020
    Co-Authors: Yanwei Zhao, Li Xing, Meiyan Zhang, Yuankun Gui
    Abstract:

    ABSTRACT The paper's focus is on the module division dynamically in the virtual assembly sequencing process for the product family, which will affect the module variant quality seriously. Most research merely divides the module on their functions, without paying the attention on which the module division is beneficial for the latter assembly process. Considered assembly relationships as a key Constraint, a new variant module division measure based on Extension Logic is presented. Since the tolerances existing everywhere in the assembly process, the connection analysis is employed to build a Constraint function on the tolerance. Physical Constraints contain Mating and combination Constraints. After the dynamical position for different parts, the Mating Constraint is defined as the movement opposition between two mechanical elements including face alignment Mating, shaft and hole Mating or face against Mating. Then the extension radiation model could be generated. According the average value of the relationship function to realize the module division, the product structure is divided into several sub-assemblies. As the main problem in virtual assembly is process collisions, a modified integer coded Particle Swarm Optimization Algorithm is used. Here every part is mapped to corresponding particle. The result is performed in the virtual environment of software DELMIA. At last the extension cluster method in this paper is compared with the direct dynamic cluster method. A case study is performed on virtual assembly of high power Light Emitting Diodes automatic sorting machine manufactured by a factory

Meiyan Zhang - One of the best experts on this subject based on the ideXlab platform.

  • IMECE2008-68236 A VARIANT MODULE DIVISION METHOD ON EXTENSION LOGIC FOR ASSEMBLY PROCESS
    2020
    Co-Authors: Yanwei Zhao, Li Xing, Meiyan Zhang, Yuankun Gui
    Abstract:

    ABSTRACT The paper's focus is on the module division dynamically in the virtual assembly sequencing process for the product family, which will affect the module variant quality seriously. Most research merely divides the module on their functions, without paying the attention on which the module division is beneficial for the latter assembly process. Considered assembly relationships as a key Constraint, a new variant module division measure based on Extension Logic is presented. Since the tolerances existing everywhere in the assembly process, the connection analysis is employed to build a Constraint function on the tolerance. Physical Constraints contain Mating and combination Constraints. After the dynamical position for different parts, the Mating Constraint is defined as the movement opposition between two mechanical elements including face alignment Mating, shaft and hole Mating or face against Mating. Then the extension radiation model could be generated. According the average value of the relationship function to realize the module division, the product structure is divided into several sub-assemblies. As the main problem in virtual assembly is process collisions, a modified integer coded Particle Swarm Optimization Algorithm is used. Here every part is mapped to corresponding particle. The result is performed in the virtual environment of software DELMIA. At last the extension cluster method in this paper is compared with the direct dynamic cluster method. A case study is performed on virtual assembly of high power Light Emitting Diodes automatic sorting machine manufactured by a factory