The Experts below are selected from a list of 180375 Experts worldwide ranked by ideXlab platform

Stephan Le G Roux - One of the best experts on this subject based on the ideXlab platform.

  • standard method for microct based additive Manufacturing Quality control 1 porosity analysis
    MethodsX, 2018
    Co-Authors: Anton Du Plessis, Andre Beerlink, Lerato Tshabalala, Philip Sperling, Shaik Hoosain, Ntombi Mathe, Stephan Le G Roux
    Abstract:

    MicroCT is a well-established technique that is used to analyze the interior of objects non-destructively, and it is especially useful for void or porosity analysis. Besides its widespread use, few standards exist and none for additive Manufacturing as yet. This is due to the inherent differences in part design, sizes and geometries, which results in different scan resolutions and qualities. This makes direct comparison between different scans of additively manufactured parts almost impossible. In addition, different image analysis methodologies can produce different results. In this method paper, we present a simplified 10 mm cube-shaped coupon sample as a standard size for detailed analysis of porosity using microCT, and a simplified workflow for obtaining porosity information. The aim is to be able to obtain directly comparable porosity information from different samples from the same AM system and even from different AM systems, and to potentially correlate detailed morphologies of the pores or voids with improper process parameters. The method is applied to two examples of different characteristic types of voids in AM: sub-surface lack of fusion due to improper contour scanning, and tree-like pores growing in the build direction. This standardized method demonstrates the capability for microCT to not only quantify porosity, but also identify void types which can be used to improve AM process optimization.

  • standard method for microct based additive Manufacturing Quality control 2 density measurement
    MethodsX, 2018
    Co-Authors: Anton Du Plessis, Andre Beerlink, Lerato Tshabalala, Philip Sperling, Shaik Hoosain, Ntombi Mathe, Stephan Le G Roux
    Abstract:

    Abstract MicroCT is best known for its ability to detect and quantify porosity or defects, and to visualize its 3D distribution. However, it is also possible to obtain accurate volumetric measurements from parts – this can be used in combination with the part mass to provide a good measure of its average density. The advantage of this density-measurement method is the ability to combine the density measurement with visualization and other microCT analyses of the same sample. These other analyses may include detailed porosity or void analysis (size and distribution) and roughness assessment, obtainable with the same scan data. Simple imaging of the interior of the sample allows the detection of unconsolidated powder, open porosity to the surface or the presence of inclusions. The CT density method presented here makes use of a 10?mm cube sample and a simple data analysis workflow, facilitating standardization of the method. A laboratory microCT scanner is required at 15?µm voxel size, suitable software to allow sub-voxel precise edge determination of the scanned sample and hence an accurate total volume measurement, and a scale with accuracy to 3 digits. • MicroCT-based mean density measurement method. • Accurate volume measurement and scale mass. • 10 mm cube sample allows standardization and automation of workflow.

  • standard method for microct based additive Manufacturing Quality control 4 metal powder analysis
    MethodsX, 2018
    Co-Authors: Anton Du Plessis, Andre Beerlink, Philip Sperling, Willie Du Preez, Stephan Le G Roux
    Abstract:

    X-ray micro computed tomography (microCT) can be applied to analyse powder feedstock used in additive Manufacturing. In this paper, we demonstrate a dedicated workflow for this analysis method, specifically for Ti6Al4V powder typically used in commercial powder bed fusion (PBF) additive Manufacturing (AM) systems. The methodology presented includes sample size requirements, scan conditions and settings, reconstruction and image analysis procedures. We envisage this method will support standardization in powder analysis in the additive Manufacturing community. This is aimed at ultimately improving the Quality of additively manufactured parts, through the identification of impurities and defects in powders. •MicroCT analysis of metal powders for additive Manufacturing•Method describes a standard workflow simplifying usage of the technique•Sample requirements and image analysis workflow is described.

Anton Du Plessis - One of the best experts on this subject based on the ideXlab platform.

  • standard method for microct based additive Manufacturing Quality control 1 porosity analysis
    MethodsX, 2018
    Co-Authors: Anton Du Plessis, Andre Beerlink, Lerato Tshabalala, Philip Sperling, Shaik Hoosain, Ntombi Mathe, Stephan Le G Roux
    Abstract:

    MicroCT is a well-established technique that is used to analyze the interior of objects non-destructively, and it is especially useful for void or porosity analysis. Besides its widespread use, few standards exist and none for additive Manufacturing as yet. This is due to the inherent differences in part design, sizes and geometries, which results in different scan resolutions and qualities. This makes direct comparison between different scans of additively manufactured parts almost impossible. In addition, different image analysis methodologies can produce different results. In this method paper, we present a simplified 10 mm cube-shaped coupon sample as a standard size for detailed analysis of porosity using microCT, and a simplified workflow for obtaining porosity information. The aim is to be able to obtain directly comparable porosity information from different samples from the same AM system and even from different AM systems, and to potentially correlate detailed morphologies of the pores or voids with improper process parameters. The method is applied to two examples of different characteristic types of voids in AM: sub-surface lack of fusion due to improper contour scanning, and tree-like pores growing in the build direction. This standardized method demonstrates the capability for microCT to not only quantify porosity, but also identify void types which can be used to improve AM process optimization.

  • standard method for microct based additive Manufacturing Quality control 2 density measurement
    MethodsX, 2018
    Co-Authors: Anton Du Plessis, Andre Beerlink, Lerato Tshabalala, Philip Sperling, Shaik Hoosain, Ntombi Mathe, Stephan Le G Roux
    Abstract:

    Abstract MicroCT is best known for its ability to detect and quantify porosity or defects, and to visualize its 3D distribution. However, it is also possible to obtain accurate volumetric measurements from parts – this can be used in combination with the part mass to provide a good measure of its average density. The advantage of this density-measurement method is the ability to combine the density measurement with visualization and other microCT analyses of the same sample. These other analyses may include detailed porosity or void analysis (size and distribution) and roughness assessment, obtainable with the same scan data. Simple imaging of the interior of the sample allows the detection of unconsolidated powder, open porosity to the surface or the presence of inclusions. The CT density method presented here makes use of a 10?mm cube sample and a simple data analysis workflow, facilitating standardization of the method. A laboratory microCT scanner is required at 15?µm voxel size, suitable software to allow sub-voxel precise edge determination of the scanned sample and hence an accurate total volume measurement, and a scale with accuracy to 3 digits. • MicroCT-based mean density measurement method. • Accurate volume measurement and scale mass. • 10 mm cube sample allows standardization and automation of workflow.

  • standard method for microct based additive Manufacturing Quality control 4 metal powder analysis
    MethodsX, 2018
    Co-Authors: Anton Du Plessis, Andre Beerlink, Philip Sperling, Willie Du Preez, Stephan Le G Roux
    Abstract:

    X-ray micro computed tomography (microCT) can be applied to analyse powder feedstock used in additive Manufacturing. In this paper, we demonstrate a dedicated workflow for this analysis method, specifically for Ti6Al4V powder typically used in commercial powder bed fusion (PBF) additive Manufacturing (AM) systems. The methodology presented includes sample size requirements, scan conditions and settings, reconstruction and image analysis procedures. We envisage this method will support standardization in powder analysis in the additive Manufacturing community. This is aimed at ultimately improving the Quality of additively manufactured parts, through the identification of impurities and defects in powders. •MicroCT analysis of metal powders for additive Manufacturing•Method describes a standard workflow simplifying usage of the technique•Sample requirements and image analysis workflow is described.

Philip Sperling - One of the best experts on this subject based on the ideXlab platform.

  • Standard method for microCT-based additive Manufacturing Quality control 3: Surface roughness
    MethodsX, 2018
    Co-Authors: Anton Du Plessis, Andre Beerlink, Oelof Kruger, Lerato Tshabalala, Philip Sperling, Shaik Hoosain, Stephan G. Le Roux
    Abstract:

    The use of microCT of 10 mm coupon samples produced by AM has the potential to provide useful information of mean density and detailed porosity information of the interior of the samples. In addition, the same scan data can be used to provide surface roughness analysis of the as-built surfaces of the same coupon samples. This can be used to compare process parameters or new materials. While surface roughness is traditionally done using tactile probes or with non-contact interferometric techniques, the complex surfaces in AM are sometimes difficult to access and may be very rough, with undercuts and may be difficult to accurately measure using traditional techniques which are meant for smoother surfaces. This standard workflow demonstrates on a coupon sample how to acquire surface roughness results, and compares the results from roughly the same area of the same sample with tactile probe results. The same principle can be applied to more complex parts, keeping in mind the resolution limit vs sample size of microCT.

  • standard method for microct based additive Manufacturing Quality control 1 porosity analysis
    MethodsX, 2018
    Co-Authors: Anton Du Plessis, Andre Beerlink, Lerato Tshabalala, Philip Sperling, Shaik Hoosain, Ntombi Mathe, Stephan Le G Roux
    Abstract:

    MicroCT is a well-established technique that is used to analyze the interior of objects non-destructively, and it is especially useful for void or porosity analysis. Besides its widespread use, few standards exist and none for additive Manufacturing as yet. This is due to the inherent differences in part design, sizes and geometries, which results in different scan resolutions and qualities. This makes direct comparison between different scans of additively manufactured parts almost impossible. In addition, different image analysis methodologies can produce different results. In this method paper, we present a simplified 10 mm cube-shaped coupon sample as a standard size for detailed analysis of porosity using microCT, and a simplified workflow for obtaining porosity information. The aim is to be able to obtain directly comparable porosity information from different samples from the same AM system and even from different AM systems, and to potentially correlate detailed morphologies of the pores or voids with improper process parameters. The method is applied to two examples of different characteristic types of voids in AM: sub-surface lack of fusion due to improper contour scanning, and tree-like pores growing in the build direction. This standardized method demonstrates the capability for microCT to not only quantify porosity, but also identify void types which can be used to improve AM process optimization.

  • standard method for microct based additive Manufacturing Quality control 2 density measurement
    MethodsX, 2018
    Co-Authors: Anton Du Plessis, Andre Beerlink, Lerato Tshabalala, Philip Sperling, Shaik Hoosain, Ntombi Mathe, Stephan Le G Roux
    Abstract:

    Abstract MicroCT is best known for its ability to detect and quantify porosity or defects, and to visualize its 3D distribution. However, it is also possible to obtain accurate volumetric measurements from parts – this can be used in combination with the part mass to provide a good measure of its average density. The advantage of this density-measurement method is the ability to combine the density measurement with visualization and other microCT analyses of the same sample. These other analyses may include detailed porosity or void analysis (size and distribution) and roughness assessment, obtainable with the same scan data. Simple imaging of the interior of the sample allows the detection of unconsolidated powder, open porosity to the surface or the presence of inclusions. The CT density method presented here makes use of a 10?mm cube sample and a simple data analysis workflow, facilitating standardization of the method. A laboratory microCT scanner is required at 15?µm voxel size, suitable software to allow sub-voxel precise edge determination of the scanned sample and hence an accurate total volume measurement, and a scale with accuracy to 3 digits. • MicroCT-based mean density measurement method. • Accurate volume measurement and scale mass. • 10 mm cube sample allows standardization and automation of workflow.

  • standard method for microct based additive Manufacturing Quality control 4 metal powder analysis
    MethodsX, 2018
    Co-Authors: Anton Du Plessis, Andre Beerlink, Philip Sperling, Willie Du Preez, Stephan Le G Roux
    Abstract:

    X-ray micro computed tomography (microCT) can be applied to analyse powder feedstock used in additive Manufacturing. In this paper, we demonstrate a dedicated workflow for this analysis method, specifically for Ti6Al4V powder typically used in commercial powder bed fusion (PBF) additive Manufacturing (AM) systems. The methodology presented includes sample size requirements, scan conditions and settings, reconstruction and image analysis procedures. We envisage this method will support standardization in powder analysis in the additive Manufacturing community. This is aimed at ultimately improving the Quality of additively manufactured parts, through the identification of impurities and defects in powders. •MicroCT analysis of metal powders for additive Manufacturing•Method describes a standard workflow simplifying usage of the technique•Sample requirements and image analysis workflow is described.

Andre Beerlink - One of the best experts on this subject based on the ideXlab platform.

  • Standard method for microCT-based additive Manufacturing Quality control 3: Surface roughness
    MethodsX, 2018
    Co-Authors: Anton Du Plessis, Andre Beerlink, Oelof Kruger, Lerato Tshabalala, Philip Sperling, Shaik Hoosain, Stephan G. Le Roux
    Abstract:

    The use of microCT of 10 mm coupon samples produced by AM has the potential to provide useful information of mean density and detailed porosity information of the interior of the samples. In addition, the same scan data can be used to provide surface roughness analysis of the as-built surfaces of the same coupon samples. This can be used to compare process parameters or new materials. While surface roughness is traditionally done using tactile probes or with non-contact interferometric techniques, the complex surfaces in AM are sometimes difficult to access and may be very rough, with undercuts and may be difficult to accurately measure using traditional techniques which are meant for smoother surfaces. This standard workflow demonstrates on a coupon sample how to acquire surface roughness results, and compares the results from roughly the same area of the same sample with tactile probe results. The same principle can be applied to more complex parts, keeping in mind the resolution limit vs sample size of microCT.

  • standard method for microct based additive Manufacturing Quality control 1 porosity analysis
    MethodsX, 2018
    Co-Authors: Anton Du Plessis, Andre Beerlink, Lerato Tshabalala, Philip Sperling, Shaik Hoosain, Ntombi Mathe, Stephan Le G Roux
    Abstract:

    MicroCT is a well-established technique that is used to analyze the interior of objects non-destructively, and it is especially useful for void or porosity analysis. Besides its widespread use, few standards exist and none for additive Manufacturing as yet. This is due to the inherent differences in part design, sizes and geometries, which results in different scan resolutions and qualities. This makes direct comparison between different scans of additively manufactured parts almost impossible. In addition, different image analysis methodologies can produce different results. In this method paper, we present a simplified 10 mm cube-shaped coupon sample as a standard size for detailed analysis of porosity using microCT, and a simplified workflow for obtaining porosity information. The aim is to be able to obtain directly comparable porosity information from different samples from the same AM system and even from different AM systems, and to potentially correlate detailed morphologies of the pores or voids with improper process parameters. The method is applied to two examples of different characteristic types of voids in AM: sub-surface lack of fusion due to improper contour scanning, and tree-like pores growing in the build direction. This standardized method demonstrates the capability for microCT to not only quantify porosity, but also identify void types which can be used to improve AM process optimization.

  • standard method for microct based additive Manufacturing Quality control 2 density measurement
    MethodsX, 2018
    Co-Authors: Anton Du Plessis, Andre Beerlink, Lerato Tshabalala, Philip Sperling, Shaik Hoosain, Ntombi Mathe, Stephan Le G Roux
    Abstract:

    Abstract MicroCT is best known for its ability to detect and quantify porosity or defects, and to visualize its 3D distribution. However, it is also possible to obtain accurate volumetric measurements from parts – this can be used in combination with the part mass to provide a good measure of its average density. The advantage of this density-measurement method is the ability to combine the density measurement with visualization and other microCT analyses of the same sample. These other analyses may include detailed porosity or void analysis (size and distribution) and roughness assessment, obtainable with the same scan data. Simple imaging of the interior of the sample allows the detection of unconsolidated powder, open porosity to the surface or the presence of inclusions. The CT density method presented here makes use of a 10?mm cube sample and a simple data analysis workflow, facilitating standardization of the method. A laboratory microCT scanner is required at 15?µm voxel size, suitable software to allow sub-voxel precise edge determination of the scanned sample and hence an accurate total volume measurement, and a scale with accuracy to 3 digits. • MicroCT-based mean density measurement method. • Accurate volume measurement and scale mass. • 10 mm cube sample allows standardization and automation of workflow.

  • standard method for microct based additive Manufacturing Quality control 4 metal powder analysis
    MethodsX, 2018
    Co-Authors: Anton Du Plessis, Andre Beerlink, Philip Sperling, Willie Du Preez, Stephan Le G Roux
    Abstract:

    X-ray micro computed tomography (microCT) can be applied to analyse powder feedstock used in additive Manufacturing. In this paper, we demonstrate a dedicated workflow for this analysis method, specifically for Ti6Al4V powder typically used in commercial powder bed fusion (PBF) additive Manufacturing (AM) systems. The methodology presented includes sample size requirements, scan conditions and settings, reconstruction and image analysis procedures. We envisage this method will support standardization in powder analysis in the additive Manufacturing community. This is aimed at ultimately improving the Quality of additively manufactured parts, through the identification of impurities and defects in powders. •MicroCT analysis of metal powders for additive Manufacturing•Method describes a standard workflow simplifying usage of the technique•Sample requirements and image analysis workflow is described.

Carlos A Escobar - One of the best experts on this subject based on the ideXlab platform.

  • process monitoring for Quality a model selection criterion for genetic programming
    International Conference on Evolutionary Multi-criterion Optimization, 2019
    Co-Authors: Carlos A Escobar, Diana M Wegner, Abhinav Gaur, Ruben Moralesmenendez
    Abstract:

    Process Monitoring for Quality is a Manufacturing Quality philosophy aimed at defect detection through binary classification that is founded on big data and big models. Genetic Programming (GP) algorithms have been successfully applied by following the big models learning paradigm for rare Quality event detection (classification). Since it is a bias-free technique unmarred by human preconceptions, it can potentially generate better solutions (models) compared with the best human efforts. However, since GP uses random search methods based on Darwinian philosophy of “survival of the fittest”, hundreds, or even thousands of models need to be created to find a good solution. In this context, model selection becomes a critical step in the process of finding the final model to be deployed at the plant. A three-objective optimization model selection criterion (\(3D-GP\)) is introduced for analyzing highly/ultra unbalanced data structures. It uses three competing attributes – prediction, separability, complexity – to project candidate models into a three-dimensional space to select the final model that solves the posed tradeoff between them the best.

  • process monitoring for Quality a model selection criterion
    Manufacturing letters, 2018
    Co-Authors: Carlos A Escobar, Ruben Moralesmenendez
    Abstract:

    Abstract The new big data driven Manufacturing Quality philosophy, Process Monitoring for Quality (PMQ), proposes Big Data — Big Models, a new modeling paradigm that includes a big data-driven learning process that requires many models to be created to find the final one. Since many candidates are created, one of the main challenges is to select the model that efficiently solves the tradeoff between complexity and prediction. Most mature Manufacturing organizations generate only a few Defects Per Million of Opportunities (DPMO); therefore, Manufacturing-derived data sets for classification of Quality tend to be highly unbalanced. The Penalized Maximum Probability of Correct Decision (PMPCD) is developed to solve the posed tradeoff. According to simulation and experimental results, the model selection criterion induces parsimony by selecting the model with the minimum number of features needed for an effective/efficient defect detection.