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Presents a method of Max‐Fit biarc curve fitting technique to improve the accuracy of STL files and to reduce the file size for rapid prototyping. STL file has been widely accepted as a de facto standard file format for the rapid prototyping industry. However, STL format is an approximated representation of a true solid/surface model, and a huge amount of STL data is needed to provide sufficient accuracy for rapid prototyping. Presents a Max‐Fit biarc curve fitting technique to reconstruct STL slicing data for rapid prototyping. The Max‐Fit algorithm progresses through the STL slicing intersection points to find the most efficient biarc curve fitting, while improving the accuracy. Our results show that the proposed biarc curve‐fitting technique can significantly improve the accuracy of poorly generated STL files by smoothing the intersection points for rapid prototyping. Therefore, less strict requirements (i.e. loose triangle tolerances) can be used while generating the STL files.

This paper aims to convert surface data directly to a three-dimensional (3D) stereolithography (STL) part. The Geographic Information Systems (GIS) data available for a terrain are the data of its surface. It doesn’t have information for a solid model. The data need to be converted into a three-dimensional (3D) solid model for making physical models by additive manufacturing (AM).

A methodology has been developed to make the wall and base of the part and tessellates the part with triangles. A program has been written which gives output of the part in STL file format. The elevation data are interpolated and any singularity present is removed. Extensive search techniques are used.

AM technologies are increasingly being used for terrain modeling. However, there is not enough work done to convert the surface data into 3D solid model. The present work aids in this area.

The methodology removes data loss associated with intermediate file formats. Terrain models can be created in less time and less cost. Intricate geometries of terrain can be created with ease and great accuracy.

The terrain models can be used for GIS education, educating the community for catchment management, conservation management, etc.

The work allows direct and automated conversion of GIS surface data into a 3D STL part. It removes intermediate steps and any data loss associated with intermediate file formats.

For part models with complex shape features or freeform shapes, the existing build orientation determination methods may have issues, such as difficulty in defining features and costly computation. To deal with these issues, this paper aims to introduce a new statistical method to develop fast automatic decision support tools for additive manufacturing build orientation determination.

The proposed method applies a non-supervised machine learning method, K-Means Clustering with Davies–Bouldin Criterion cluster measuring, to rapidly decompose a surface model into facet clusters and efficiently generate a set of meaningful alternative build orientations. To evaluate alternative build orientations at a generic level, a statistical approach is defined.

A group of illustrative examples and comparative case studies are presented in the paper for method validation. The proposed method can help production engineers solve decision problems related to identifying an optimal build orientation for complex and freeform CAD models, especially models from the medical and aerospace application domains with much efficiency.

The proposed method avoids the limitations of traditional feature-based methods and pure computation-based methods. It provides engineers a new efficient decision-making tool to rapidly determine the optimal build orientation for complex and freeform CAD models.

Additive manufactured (AM) skull models are increasingly used to plan complex surgical cases and design custom implants. The accuracy of such constructs depends on the standard tessellation language (STL) model, which is commonly obtained from computed tomography (CT) data. The aims of this study were to assess the image quality and the accuracy of STL models acquired using different CT scanners and acquisition parameters.

Images of three dry human skulls were acquired using two multi-detector row computed tomography (MDCT) scanners, a dual energy computed tomography (DECT) scanner and one cone beam computed tomography (CBCT) scanner. Different scanning protocols were used on each scanner. All images were ranked according to their image quality and converted into STL models. The STL models were compared to gold standard models.

Image quality differed between the MDCT, DECT and CBCT scanners. Images acquired using low-dose MDCT protocols were preferred over images acquired using routine protocols. All CT-based STL models demonstrated non-uniform geometrical deviations of up to +0.9 mm. The largest deviations were observed in CBCT-derived STL models.

While patient-specific AM constructs can be fabricated with great accuracy using AM technologies, their design is more challenging because it is dictated by the correctness of the STL model. Inaccurate STL models can lead to ill-fitting implants that can cause complications after surgery.

This paper suggests that CT imaging technologies and their acquisition parameters affect the accuracy of medical AM constructs.

The purpose of this paper is to use rapid prototyping (RP) technology to build physical models based on axisymmetric finite element (FE) simulation deformation results. To this end, an algorithm which extracts stereolithography (STL) model from axisymmetric ring element mesh is developed and realized by MATLAB programming.

The algorithm first identifies boundary element edges, which compose the contour(s) of an axisymmetric ring FE mesh. Then, the identified contour edges are around the symmetry axis revolved a specific angle, at certain intervals according to certain approximate criterion, to generate new nodes to form a group of oriented triangles whose normal vectors conform to the right-handed rule. Finally, a completely closed STL model is obtained by necessary triangulation processing and rotation mapping based on original mesh.

It is validated that the extracted STL model is sound and the proposed algorithm is feasible, right and characterized by linear time complexity for extracting STL model from either triangular, quadrilateral, or mixed triangular/quadrilateral axisymmetric mesh.

Color is important for expressing FE simulation results, which is not involved in STL model. Among the alternative data file formats, VRML representation is an applicable one that is complimentary to existing RP processes and suitable for color 3D printing. Based on the current work, coloring VRML model could be extracted from axisymmetric FE simulation results conveniently.

The study of this paper provides a RP-based materialized mode to characterize axisymmetric FE simulation deformation results, which is more intuitive and visible than the computer graphics-based visualization.

Pores and shrink holes are unavoidable defects in the die-casting mass production process which may significantly influence the strength, fatigue and fracture behaviour as well as the life span of structures, especially if they are subjected to high static and dynamic loads. Such defects should be considered during the design process or after production, where the defects could be detected with the help of computed tomography (CT) measurements. However, this is usually not done in today's mass production environments. This paper deals with the stress analysis of die-cast structural parts with pores found from CT measurements or that are artificially placed within a structure.

In this paper the authors illustrate two general methodologies to take into account the porosity of die-cast components in the stress analysis. The detailed geometry of a die-cast part including all discontinuities such as pores and shrink holes can be included via STL data provided by CT measurements. The first approach is a combination of the finite element method (FEM) and the finite cell method (FCM), which extends the FEM if the real geometry cuts finite elements. The FCM is only applied in regions with pores. This procedure has the advantage that all simulations with different pore distributions, real or artificial, can be calculated without changing the base finite element mesh. The second approach includes the pore information as STL data into the original CAD model and creates a new adapted finite element mesh for the simulation. Both methods are compared and evaluated for an industrial problem.

The STL data of defects which the authors received from CT measurements could not be directly applied without repairing them. Therefore, for FEM applications an appropriate repair procedure is proposed. The first approach, which combines the FEM with the FCM, the authors have realized within the commercial software tool Abaqus. This combination performs well, which is demonstrated for test examples, and is also applied for a complex industrial project. The developed in-house code still has some limitations which restrict broader application in industry. The second pure FEM-based approach works well without limitations but requires increasing computational effort if many different pore distributions are to be investigated.

A new simulation approach which combines the FEM with the FCM has been developed and implemented into the commercial Abaqus FEM software. This approach the authors have applied to simulate a real engineering die-cast structure with pores. This approach could become a preferred way to consider pores in practical applications, where the porosity can be derived either from CT measurements or are artificially adopted for design purposes. The authors have also shown how pores can be considered in the standard FEM analysis as well.

The purpose of the present work is to develop a methodology for making physical models of catchment areas and terrains by rapid prototyping (RP) using geographic information systems (GIS) data. It is also intended to reduce data loss by minimising intermediate data translations.

The GIS data of a catchment area or a terrain were directly translated to an stereo lithography (STL) file. The STL surface was then manipulated in Magics‐RP to obtain a solid STL part, which can then be downloaded to a RP machine to obtain a physical model or representation of a terrain or catchtment area.

Intricate geometries of landforms were created with ease and great accuracy in RP machines. Terrain models were created in less time and lower cost than with conventional methods.

DEM ASCII XYZ (digital elevation model) data were used to input the required GIS data of specific terrains. Software can be developed for translation and manipulation of DEM, STL and other relevant file formats. This will eliminate any data loss associated with intermediate file transfer.

Terrain models were created with ease and great accuracy in RP machines. It takes less time and can be done more cost‐effectively. Terrain models have intricate geometries and for complex models, it may take months to make using conventional methods.

STL surfaces were obtained directly from GIS data for terrain modeling. This work fulfils the need of terrain modeling for catchment management, town‐planning, road‐transport planning, architecture, military applications, geological education, etc.

This paper aims to compare the automatic segmentation of medical data and conversion to stereolithography (STL) skull models using open-source software versus commercial software.

Both open-source and commercial software used automatic segmentation and post-processing of the data without user intervention, thus avoiding human error. Detailed steps were provided for comparisons and easier to be repeated by other researchers. The results of segmentation, which were converted to STL format were compared using geometric analysis.

STL skull models produced using open-source software are comparable with the one produced using commercial software. A comparison of STL skull model produced using InVesalius with STL skull model produced using MIMICS resulted in an average dice similarity coefficient (DSC) of 97.6 ± 0.04 per cent and Hausdorff distance (HD) of 0.01 ± 0.005 mm. Inter-rater study for repeatability on MIMICS software yielded an average DSC of 100 per cent and HD of 0.

The application of open-source software will benefit the small research institutions or hospitals to produce and virtualise three-dimensional model of the skulls for teaching or clinical purposes without having to purchase expensive commercial software. It is also easily reproduceable by other researchers.

This study is one of the first comparative evaluations of an open-source software with propriety commercial software in producing accurate STL skull models. Inaccurate STL models can lead to inaccurate pre-operative planning or unfit implant.

This paper proposes a tolerant slicing algorithm for processing slice contours for Layered Manufacturing (LM). The algorithm aims to overcome the constraints of computer memory and the computation instability commonly inherent in conventional slicing methodologies. It minimizes memory usage by adopting a pick‐and‐drop approach, which extracts one facet for slicing from the Stereolithography (STL) file at a time. The facets that intersect with the cutting plane are read in, sliced and then disposed of from the memory one by one for subsequent construction of slice contours. Only the slice data and the associated topological information of the current layer are temporarily stored in the memory. This approach greatly reduces the amount of computer memory required and it involves much less computationally intensive searching operations. Thus, STL models of virtually unlimited file size can be sliced to facilitate the LM processes. The algorithm is also relatively fault‐tolerant in that common defects of STL models may be tolerated and the resultant inconsistent contours are effectively repaired.

Additive manufacturing (AM) enables the fabrication of complex geometries beyond the capability of traditional manufacturing methods. Complex lattice structures have enabled engineering innovation; however, the use of traditional computer-aided design (CAD) methods for the generation of lattice structures is inefficient, time-consuming and can present challenges to process integration. In an effort to improve the implementation of lattice structures into engineering applications, this paper aims to develop a programmatic lattice generator (PLG).

The PLG method is computationally efficient; has direct control over the quality of the stereolithographic (STL) file produced; enables the generation of more complex lattice than traditional methods; is fully programmatic, allowing batch generation and interfacing with process integration and design optimization tools; capable of generating a lattice STL file from a generic input file of node and connectivity data; and can export a beam model for numerical analysis.

This method has been successfully implemented in the generation of uniform, radial and space filling lattices. Case studies were developed which showed a reduction in processing time greater than 60 per cent for a 3,375 cell lattice over traditional CAD software.

The PLG method is a novel design for additive manufacture (DFAM) tool with unique advantages, including full control over the number of facets that represent a lattice strut, allowing optimization of STL data to minimize file size, while maintaining suitable resolution for the implemented AM process; programmatic DFAM capability that overcomes the learning curve of traditional CAD when producing complex lattice structures, therefore is independent of designer proficiency and compatible with process integration; and the capability to output both STL files and associated data for numerical analysis, a unique DFAM capability not previously reported.