Geometric Complexity Analysis in an Integrative Technology Evaluation Model (Item) for Selective Laser Melting (Slm)#

Merkt, Simon; Hinke, Christian; Schleifenbaum, H.; Voswinckel, Holger

doi:10.7166/23-2-333

Cited by 11 publications

(5 citation statements)

References 10 publications

(13 reference statements)

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“…The complexity of geometry part will affect the result by taking longer time since it involve with removal of support from internal supported section like a hole and tube. Higher geometry complexity also means there may be multiple layers of supports within the geometry, which can be challenging to remove and require additional tools, such as pliers or tweezers, to reach the supports [21]. Removability of support during post-processing stage is crucial factor to be considered in designing support structure from beginning especially when dealing with support structure at internal section of part.…”

Section: Support Removal Timementioning

confidence: 99%

Effect of support structure design toward residual stress of part build using selective laser melting

Sulaiman,

Yusof

2023

Materialwissenschaft Werkst

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Selective laser melting process required post‐processing of support structure and it is compulsory to use it at overhanging part. There is certain condition where support structure cannot be remove using wire cut machine because of limited access to part and need to be remove manually. This is where the removability of support structure plays important role because support structure needed to be design so that it can be easily remove using manual way. In addition, when comparing contour type of support structure with the most commonly use block type of support structure it shows that contour type is easier to be remove. Furthermore, no research has been done on optimizing the contour type of support structure. A research experiment is conducted in this work to optimize the parameter of contour support structure which is contour offset, teeth height, teeth top length and teeth base length. The result indicates amount of residual stress and the time required for support removal are significantly influenced by contour offset, while all parameters are significant for support volume. The optimum parameter to get low residual stress is contour offset is 0.6 mm, teeth height is 1.4 mm, teeth top length is 0.75 mm and teeth base length is 1.55 mm.

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Section: Support Removal Timementioning

confidence: 99%

Effect of support structure design toward residual stress of part build using selective laser melting

Sulaiman,

Yusof

2023

Materialwissenschaft Werkst

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“…In addition, research studies have claimed that "complexity is free" when it comes to AM [21], with evidence supporting that claim. Part complexity in Traditional Manufacturing (TM) often leads to higher production cost and time [22].…”

Section: Introductionmentioning

confidence: 99%

“…The four methods define complexity based on the number of facets and part volume divided by: the number of facets, bounding box volume, and surface area of the model. Merkt et al [21] investigated the three complexity measures Brajlih et al proposed to be added to an integrative technology evaluation model (ITEM). The model is supposed to identify whether Selective Laser Melting (SLM) is the most efficient process based on the three complexity factors.…”

Section: Introductionmentioning

confidence: 99%

Investigation of the impact of power consumption, surface roughness, and part complexity in stereolithography and fused filament fabrication

Ali

Fidan

Tantawi

2023

Int J Adv Manuf Technol

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Today, Additive Manufacturing (AM) is being utilized in a plethora of fields and applications. This study investigates two of the most commonly used AM technologies, Fused Filament Fabrication (FFF) and Stereolithography (SLA) under the different part complexities and their effects to finished part quality. The process parameters investigated are infill density (ID), infill pattern (IP), and layer height (LH). The output variables observed are power consumption (PC), surface roughness (SR), and mass. Statistical analysis of experimental data indicates that LH is the most influential parameter for all output variables except mass. A validation study is later performed using three specimens with more diversely complex geometries. The model complexity is then evaluated and analyzed using three different ratios. Normalizing PC with respect to volume indicates a lower PC per unit volume for FFF. Experimental data also indicates SLA has a better surface finish and uses less power. This paper reports the state-of-the-art FFF and SLA process knowledge blocks created through this research study.

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“…The layer-based strategy in AM allows for the creation of complex shapes without the use of hard tooling. The cost per part in conventional manufacturing has been found to increase as the complexity of the design increases, whereas the cost per part in AM has been reported to remain nearly constant as the complexity increases (Merkt et al , 2011). AM offers a new opportunity for organizations with established product lines and those launching new products to review their manufacturing strategies (Brennan et al , 2021).…”

Section: Introductionmentioning

confidence: 99%

A view similarity-based shape complexity metric to guide part selection for additive manufacturing

Jayapal

Kumaraguru

Varadarajan

2022

RPJ

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Purpose This paper aims to propose a view similarity-based shape complexity metric to guide part selection for additive manufacturing (AM) and advance the goals of design for AM. The metric helps to improve the selection process by objectively screening a large number of parts and identifying the parts most suited for AM and enabling experts to prioritize parts from a smaller set based on relevant subjective/contextual factors. Design/methodology/approach The methodology involves calculating a part’s shape complexity based on the concept of view similarity, that is, the similarity of different views of the outer shape and internal cross-sectional geometry. The combined shape complexity metric (weighted sum of the external shape and internal structure complexity) has been used to rank various three dimensional (3D) models. The metric has been tested for its sensitivity to various input parameters and thresholds are suggested for effective results. The proposed metric’s applicability for part selection has also been investigated and compared with the existing metric-based part selection. Findings The proposed shape complexity metric can distinguish the parts of different shapes, sizes and parts with minor design variations. The method is also efficient regarding the amount of data and computation required to facilitate the part selection. The proposed method can detect differences in the mass properties of a 3D model without evaluating the modified parameters. The proposed metric is effective in initial screening of a large number of parts in new product development and for redesign using AM. Research limitations/implications The proposed metric is sensitive to input parameters, such as the number of viewpoints, design orientation, image resolution and different lattice structures. To address this issue, this study suggests thresholds for each input parameter for optimum results. Originality/value This paper evaluates shape complexity using view similarity to rank parts for prototyping or redesigning with AM.

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Geometric Complexity Analysis in an Integrative Technology Evaluation Model (Item) for Selective Laser Melting (Slm)#

Cited by 11 publications

References 10 publications

Effect of support structure design toward residual stress of part build using selective laser melting

Effect of support structure design toward residual stress of part build using selective laser melting

Investigation of the impact of power consumption, surface roughness, and part complexity in stereolithography and fused filament fabrication

A view similarity-based shape complexity metric to guide part selection for additive manufacturing

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