Tolerancing from STL data: A Legacy Challenge

Leirmo, Torbjørn Langedahl; Semeniuta, Oleksandr; Martinsen, Kristian

doi:10.1016/j.procir.2020.05.180

Cited by 6 publications

(5 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The meshing introduces specific inaccuracies due to rounding errors and the discretization of smooth curves, resulting in a characteristic tessellated surface. These errors inevitably lead to some uncertainty regarding the accurate size and position of features when extracting information from meshed solid data [31]. As Qiu et.…”

Section: Resultsmentioning

confidence: 99%

Automatic Detection of Axes for Turning Parts

Erler,

Başar,

Brosius

2024

Journal of Machine Engineering

View full text Add to dashboard Cite

This paper delves into a critical aspect of Computer-Aided Production Planning (CAPP): the automated detection of the main rotational axis in turning parts within Computer-Aided Designs (CAD). The identification of the principal turning axis in CAD models presents numerous opportunities in the field of CAPP. In this study, the authors employ advanced surface segmentation techniques to analyse the surface geometry, pinpointing rotational surfaces within the CAD model. Subsequently, significant features are extracted from these identified rotational surfaces, and the necessary data for rotational centers are gathered. By fine-tuning the weighting of the data gathered, the approach can be tailored to suit various planning strategies. This approach has the potential to significantly enhance both the efficiency and accuracy of the automated production planning process for turning parts in CAPP.

show abstract

Section: Resultsmentioning

confidence: 99%

Automatic Detection of Axes for Turning Parts

Erler,

Başar,

Brosius

2024

Journal of Machine Engineering

View full text Add to dashboard Cite

show abstract

“…Whilst the process is relatively straightforward for solid geometry, for porous geometries, the number of data points created increases exponentially in relation to feature size and porosity. This leads to significant challenges associated with pre-processing leading to alterations in the file format resolution, error fixing (bad edges, overlapping, intersecting triangles) and slicing parameter inconsistencies leading to print defects (Leirmo et al, 2020;Manmadhachary et al, 2016;Huotilainen et al, 2014).…”

Section: Additive Manufacturing Copper-tungsten-silvermentioning

confidence: 99%

“…Whilst the process is relatively straightforward for solid geometry, for porous geometries, the number of data points increases exponentially in line with the resolution of the porous architecture required. This leads to significant challenges associated with preprocessing, leading to alterations in the file format resolution, error fixing (bad edges, overlapping and intersecting triangles) and slicing parameter inconsistencies leading to print defects when using the conventional technique (Leirmo et al, 2020;Huotilainen et al, 2014;Cuesta et al, 2020). The excellent agreement between predicted and actual data also shows the accuracy and consistency of the parameter informed technique, which is also a challenge when working with high-resolution STL files with large data points.…”

Section: Regulation and Approvalmentioning

confidence: 99%

Additive manufacturing of anti-SARS-CoV-2 Copper-Tungsten-Silver alloy

Robinson

Arjunan

Baroutaji

et al. 2021

RPJ

View full text Add to dashboard Cite

Purpose The COVID-19 pandemic emphasises the need for antiviral materials that can reduce airborne and surface-based virus transmission. This study aims to propose the use of additive manufacturing (AM) and surrogate modelling for the rapid development and deployment of novel copper-tungsten-silver (Cu-W-Ag) microporous architecture that shows strong antiviral behaviour against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Design/methodology/approach The research combines selective laser melting (SLM), in-situ alloying and surrogate modelling to conceive the antiviral Cu-W-Ag architecture. The approach is shown to be suitable for redistributed manufacturing by representing the pore morphology through a surrogate model that parametrically manipulates the SLM process parameters: hatch distance (h_d), scan speed (S_s) and laser power (L_p). The method drastically simplifies the three-dimensional (3D) printing of microporous materials by requiring only global geometrical dimensions solving current bottlenecks associated with high computed aided design data transfer required for the AM of porous materials. Findings The surrogate model developed in this study achieved an optimum parametric combination that resulted in microporous Cu-W-Ag with average pore sizes of 80 µm. Subsequent antiviral evaluation of the optimum architecture showed 100% viral inactivation within 5 h against a biosafe enveloped ribonucleic acid viral model of SARS-CoV-2. Research limitations/implications The Cu-W-Ag architecture is suitable for redistributed manufacturing and can help reduce surface contamination of SARS-CoV-2. Nevertheless, further optimisation may improve the virus inactivation time. Practical implications The study was extended to demonstrate an open-source 3D printed Cu-W-Ag antiviral mask filter prototype. Social implications The evolving nature of the COVID-19 pandemic brings new and unpredictable challenges where redistributed manufacturing of 3D printed antiviral materials can achieve rapid solutions. Originality/value The papers present for the first time a methodology to digitally conceive and print-on-demand a novel Cu-W-Ag alloy that shows high antiviral behaviour against SARS-CoV-2.

show abstract

“…The artifact was inspected and reoriented to aligned with Cartesian orthogonal axes using Microsoft 3D Builder and converted to binary format. The interested reader is referred to [35] and [36] for details on STL files and the challenges they impose on AM and tolerancing. The artifact is available online, along with all supplementary data.…”

Section: Designing the Test Artifactmentioning

confidence: 99%

Investigating the Dimensional and Geometric Accuracy of Laser-Based Powder Bed Fusion of PA2200 (PA12): Experiment Design and Execution

Leirmo

Semeniuta

2021

Applied Sciences

Self Cite

View full text Add to dashboard Cite

Variation management in additive manufacturing (AM) is progressively more important as technologies are implemented in industrial manufacturing systems; hence massive research efforts are focused on the modeling and optimization of process parameters and the effect on final part quality. These efforts are, however, hampered by the very problem they are seeking to solve, as conclusions are weakened by poor validity, reliability, and repeatability. This paper details an elaborate experiment design and the subsequent execution with the aim of making the research data available without loss of validity. Test artifacts were designed and allocated to fixed positions and orientations in a grid pattern within the build chamber to facilitate rigid analysis between different builds and positions in the build chamber. A total of 507 specimens were produced over three builds by laser sintering PA12 before inspection with a coordinate measuring machine. This research demonstrates the inherent variations of laser-based powder bed fusion of polymers (LB-PBF/P) that must be considered in experiment designs to account for noise factors. In particular, the results indicate that the position in the xy-plane has a major influence on the geometric accuracy, while the position in the z-direction appears to be less influential.

show abstract

Tolerancing from STL data: A Legacy Challenge

Cited by 6 publications

References 28 publications

Automatic Detection of Axes for Turning Parts

Automatic Detection of Axes for Turning Parts

Additive manufacturing of anti-SARS-CoV-2 Copper-Tungsten-Silver alloy

Investigating the Dimensional and Geometric Accuracy of Laser-Based Powder Bed Fusion of PA2200 (PA12): Experiment Design and Execution

Contact Info

Product

Resources

About