The Experts below are selected from a list of 309 Experts worldwide ranked by ideXlab platform

Daining Fang - One of the best experts on this subject based on the ideXlab platform.

  • effect of Manufacturing Defect on mechanical performance of plain weave carbon epoxy composite based on 3d geometrical reconstruction
    Composite Structures, 2018
    Co-Authors: Panding Wang, Haosen Chen, C S Wang, Daining Fang
    Abstract:

    Abstract The investigation on the effect of Manufacturing Defect on the mechanical performance of composite is essential for the design and application in practice. In this study, the plain weave carbon fiber reinforced polymer (CFRP) laminates are fabricated by the autoclave process and vacuum bag process (VBP), respectively. Uniaxial tensile testes are conducted with a digital image correlation (DIC) system to obtain the macroscopic mechanical performance and local strain distribution. The internal microDefects of composite laminates are captured by micron-resolution computed tomography (μCT) detection technique, including the size and distribution of void, total volume fraction and geometrical parameters of yarns. Based on the Texgen software and Monte-Carlo algorithm, virtual samples with various void contents are constructed to evaluate the impact of Defect using finite element solver ABAQUS/Standard. To substantiate this work, we present a comparative study considering both autoclave and VBP. The effect of void Defect on the mechanical performances of CFRP laminate is analyzed through finite element method (FEM). The results reveal that the effect of void Defect on the surface strain distribution of laminate is significant, especially the value of maximum strain, which will increase obviously with the void Defect content. In addition, the overall stiffness predicted by numerical simulation, taking the effect of void Defect into account, is lower than that of theoretical.

  • Effect of Manufacturing Defect on mechanical performance of plain weave carbon/epoxy composite based on 3D geometrical reconstruction
    Composite Structures, 2018
    Co-Authors: Panding Wang, Haosen Chen, Changxian Wang, Daining Fang
    Abstract:

    Abstract The investigation on the effect of Manufacturing Defect on the mechanical performance of composite is essential for the design and application in practice. In this study, the plain weave carbon fiber reinforced polymer (CFRP) laminates are fabricated by the autoclave process and vacuum bag process (VBP), respectively. Uniaxial tensile testes are conducted with a digital image correlation (DIC) system to obtain the macroscopic mechanical performance and local strain distribution. The internal microDefects of composite laminates are captured by micron-resolution computed tomography (μCT) detection technique, including the size and distribution of void, total volume fraction and geometrical parameters of yarns. Based on the Texgen software and Monte-Carlo algorithm, virtual samples with various void contents are constructed to evaluate the impact of Defect using finite element solver ABAQUS/Standard. To substantiate this work, we present a comparative study considering both autoclave and VBP. The effect of void Defect on the mechanical performances of CFRP laminate is analyzed through finite element method (FEM). The results reveal that the effect of void Defect on the surface strain distribution of laminate is significant, especially the value of maximum strain, which will increase obviously with the void Defect content. In addition, the overall stiffness predicted by numerical simulation, taking the effect of void Defect into account, is lower than that of theoretical.

Cedo Nedic - One of the best experts on this subject based on the ideXlab platform.

  • Stereo vision-based repair of metallic components
    Rapid Prototyping Journal, 2017
    Co-Authors: Renwei Liu, Frank Liou, T Sparks, Zhiyuan Wang, Cedo Nedic
    Abstract:

    (2017),"Piezoelectric component fabrication using projection-based stereolithography of barium titanate ceramic suspensions", Access to this document was granted through an Emerald subscription provided by emerald-srm:172729 [] For Authors If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.com Emerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services. Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. Abstract Purpose – This paper aims to investigate a stereo vision-based hybrid (additive and subtractive) Manufacturing process using direct laser metal deposition, computer numerical control (CNC) machining and in-process scanning to repair metallic components automatically. The focus of this work was to realize automated alignment and adaptive tool path generation that can repair metallic components after a single setup. Design/methodology/approach – Stereo vision was used to detect the Defect area for automated alignment. After the Defect is located, a laser displacement sensor is used to scan the Defect area before and after laser metal deposition. The scan is then processed by an adaptive algorithm to generate a tool path for repairing the Defect. Findings – The hybrid Manufacturing processes for repairing metallic component combine the advantages of free-form fabrication from additive Manufacturing with the high-accuracy offered by CNC machining. A Ti-6Al-4V component with a Manufacturing Defect was repaired by the proposed process. Compared to previous research on repairing worn components, introducing stereo vision and laser scanning dramatically simplifies the manual labor required to extract and reconstruct the Defect area's geometry. Originality/value – This paper demonstrates an automated metallic component repair process by integrating stereo vision and a laser displacement sensor into a hybrid Manufacturing system. Experimental results and microstructure analysis shows that the Defect area could be repaired feasibly and efficiently with acceptable heat affected zone using the proposed approach.

  • Rapid Prototyping Journal Stereo vision-based repair of metallic components Stereo vision-based repair of metallic components
    Rapid Prototyping Journal Rapid Prototyping Journal Iss Rapid Prototyping Journal, 2017
    Co-Authors: Renwei Liu, Frank Liou, Cedo Nedic, T Sparks, Zhiyuan Wang, Frank Liou Cedo
    Abstract:

    (2017),"Piezoelectric component fabrication using projection-based stereolithography of barium titanate ceramic suspensions", Access to this document was granted through an Emerald subscription provided by emerald-srm:172729 [] For Authors If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.com Emerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services. Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. Abstract Purpose – This paper aims to investigate a stereo vision-based hybrid (additive and subtractive) Manufacturing process using direct laser metal deposition, computer numerical control (CNC) machining and in-process scanning to repair metallic components automatically. The focus of this work was to realize automated alignment and adaptive tool path generation that can repair metallic components after a single setup. Design/methodology/approach – Stereo vision was used to detect the Defect area for automated alignment. After the Defect is located, a laser displacement sensor is used to scan the Defect area before and after laser metal deposition. The scan is then processed by an adaptive algorithm to generate a tool path for repairing the Defect. Findings – The hybrid Manufacturing processes for repairing metallic component combine the advantages of free-form fabrication from additive Manufacturing with the high-accuracy offered by CNC machining. A Ti-6Al-4V component with a Manufacturing Defect was repaired by the proposed process. Compared to previous research on repairing worn components, introducing stereo vision and laser scanning dramatically simplifies the manual labor required to extract and reconstruct the Defect area's geometry. Originality/value – This paper demonstrates an automated metallic component repair process by integrating stereo vision and a laser displacement sensor into a hybrid Manufacturing system. Experimental results and microstructure analysis shows that the Defect area could be repaired feasibly and efficiently with acceptable heat affected zone using the proposed approach.

Renwei Liu - One of the best experts on this subject based on the ideXlab platform.

  • Stereo vision-based repair of metallic components
    Rapid Prototyping Journal, 2017
    Co-Authors: Renwei Liu, Frank Liou, T Sparks, Zhiyuan Wang, Cedo Nedic
    Abstract:

    (2017),"Piezoelectric component fabrication using projection-based stereolithography of barium titanate ceramic suspensions", Access to this document was granted through an Emerald subscription provided by emerald-srm:172729 [] For Authors If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.com Emerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services. Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. Abstract Purpose – This paper aims to investigate a stereo vision-based hybrid (additive and subtractive) Manufacturing process using direct laser metal deposition, computer numerical control (CNC) machining and in-process scanning to repair metallic components automatically. The focus of this work was to realize automated alignment and adaptive tool path generation that can repair metallic components after a single setup. Design/methodology/approach – Stereo vision was used to detect the Defect area for automated alignment. After the Defect is located, a laser displacement sensor is used to scan the Defect area before and after laser metal deposition. The scan is then processed by an adaptive algorithm to generate a tool path for repairing the Defect. Findings – The hybrid Manufacturing processes for repairing metallic component combine the advantages of free-form fabrication from additive Manufacturing with the high-accuracy offered by CNC machining. A Ti-6Al-4V component with a Manufacturing Defect was repaired by the proposed process. Compared to previous research on repairing worn components, introducing stereo vision and laser scanning dramatically simplifies the manual labor required to extract and reconstruct the Defect area's geometry. Originality/value – This paper demonstrates an automated metallic component repair process by integrating stereo vision and a laser displacement sensor into a hybrid Manufacturing system. Experimental results and microstructure analysis shows that the Defect area could be repaired feasibly and efficiently with acceptable heat affected zone using the proposed approach.

  • Rapid Prototyping Journal Stereo vision-based repair of metallic components Stereo vision-based repair of metallic components
    Rapid Prototyping Journal Rapid Prototyping Journal Iss Rapid Prototyping Journal, 2017
    Co-Authors: Renwei Liu, Frank Liou, Cedo Nedic, T Sparks, Zhiyuan Wang, Frank Liou Cedo
    Abstract:

    (2017),"Piezoelectric component fabrication using projection-based stereolithography of barium titanate ceramic suspensions", Access to this document was granted through an Emerald subscription provided by emerald-srm:172729 [] For Authors If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.com Emerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services. Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. Abstract Purpose – This paper aims to investigate a stereo vision-based hybrid (additive and subtractive) Manufacturing process using direct laser metal deposition, computer numerical control (CNC) machining and in-process scanning to repair metallic components automatically. The focus of this work was to realize automated alignment and adaptive tool path generation that can repair metallic components after a single setup. Design/methodology/approach – Stereo vision was used to detect the Defect area for automated alignment. After the Defect is located, a laser displacement sensor is used to scan the Defect area before and after laser metal deposition. The scan is then processed by an adaptive algorithm to generate a tool path for repairing the Defect. Findings – The hybrid Manufacturing processes for repairing metallic component combine the advantages of free-form fabrication from additive Manufacturing with the high-accuracy offered by CNC machining. A Ti-6Al-4V component with a Manufacturing Defect was repaired by the proposed process. Compared to previous research on repairing worn components, introducing stereo vision and laser scanning dramatically simplifies the manual labor required to extract and reconstruct the Defect area's geometry. Originality/value – This paper demonstrates an automated metallic component repair process by integrating stereo vision and a laser displacement sensor into a hybrid Manufacturing system. Experimental results and microstructure analysis shows that the Defect area could be repaired feasibly and efficiently with acceptable heat affected zone using the proposed approach.

Panding Wang - One of the best experts on this subject based on the ideXlab platform.

  • effect of Manufacturing Defect on mechanical performance of plain weave carbon epoxy composite based on 3d geometrical reconstruction
    Composite Structures, 2018
    Co-Authors: Panding Wang, Haosen Chen, C S Wang, Daining Fang
    Abstract:

    Abstract The investigation on the effect of Manufacturing Defect on the mechanical performance of composite is essential for the design and application in practice. In this study, the plain weave carbon fiber reinforced polymer (CFRP) laminates are fabricated by the autoclave process and vacuum bag process (VBP), respectively. Uniaxial tensile testes are conducted with a digital image correlation (DIC) system to obtain the macroscopic mechanical performance and local strain distribution. The internal microDefects of composite laminates are captured by micron-resolution computed tomography (μCT) detection technique, including the size and distribution of void, total volume fraction and geometrical parameters of yarns. Based on the Texgen software and Monte-Carlo algorithm, virtual samples with various void contents are constructed to evaluate the impact of Defect using finite element solver ABAQUS/Standard. To substantiate this work, we present a comparative study considering both autoclave and VBP. The effect of void Defect on the mechanical performances of CFRP laminate is analyzed through finite element method (FEM). The results reveal that the effect of void Defect on the surface strain distribution of laminate is significant, especially the value of maximum strain, which will increase obviously with the void Defect content. In addition, the overall stiffness predicted by numerical simulation, taking the effect of void Defect into account, is lower than that of theoretical.

  • Effect of Manufacturing Defect on mechanical performance of plain weave carbon/epoxy composite based on 3D geometrical reconstruction
    Composite Structures, 2018
    Co-Authors: Panding Wang, Haosen Chen, Changxian Wang, Daining Fang
    Abstract:

    Abstract The investigation on the effect of Manufacturing Defect on the mechanical performance of composite is essential for the design and application in practice. In this study, the plain weave carbon fiber reinforced polymer (CFRP) laminates are fabricated by the autoclave process and vacuum bag process (VBP), respectively. Uniaxial tensile testes are conducted with a digital image correlation (DIC) system to obtain the macroscopic mechanical performance and local strain distribution. The internal microDefects of composite laminates are captured by micron-resolution computed tomography (μCT) detection technique, including the size and distribution of void, total volume fraction and geometrical parameters of yarns. Based on the Texgen software and Monte-Carlo algorithm, virtual samples with various void contents are constructed to evaluate the impact of Defect using finite element solver ABAQUS/Standard. To substantiate this work, we present a comparative study considering both autoclave and VBP. The effect of void Defect on the mechanical performances of CFRP laminate is analyzed through finite element method (FEM). The results reveal that the effect of void Defect on the surface strain distribution of laminate is significant, especially the value of maximum strain, which will increase obviously with the void Defect content. In addition, the overall stiffness predicted by numerical simulation, taking the effect of void Defect into account, is lower than that of theoretical.

Chingyao Wang - One of the best experts on this subject based on the ideXlab platform.

  • a novel Manufacturing Defect detection method using association rule mining techniques
    Expert Systems With Applications, 2005
    Co-Authors: Weichou Chen, Shianshyong Tseng, Chingyao Wang
    Abstract:

    In recent years, Manufacturing processes have become more and more complex, and meeting high-yield target expectations and quickly identifying root-cause machinesets, the most likely sources of Defective products, also become essential issues. In this paper, we first define the root-cause machineset identification problem of analyzing correlations between combinations of machines and the Defective products. We then propose the Root-cause Machine Identifier (RMI) method using the technique of association rule mining to solve the problem efficiently and effectively. The experimental results of real datasets show that the actual root-cause machinesets are almost ranked in the top 10 by the proposed RMI method.