Sketch-Based Modeling in Mechanical Engineering Design: Current Status and Opportunities

Camba, Jorge D.; Company, Pedro; Naya, Ferran

doi:10.1016/j.cad.2022.103283

Cited by 12 publications

(6 citation statements)

References 113 publications

(70 reference statements)

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“…The "Usable area of the glasses [was] very limited" (P3), referring to the limited field of view of the HoloLens. This sentiment was echoed by other participants (P5, 6,8,17).…”

Section: Desktop Rather Desktop Neutral Rather Param Parammentioning

confidence: 81%

“…Several works rely on path design [45] or sketching as a way to define curves [7,8] or express design intent [17,46], which is also a relevant parameter type in pARam. This was also considered from an evaluation perspective by surveying the state of the art of how sketch-based systems are evaluated and highlighting the absence of standardized methods to do so [71].…”

Section: Design In and For Extended Realitymentioning

confidence: 99%

“…3a. This allows users to control separate dimensions of a design, reduced to a linear mapping 17 . The effects of the changes are reflected immediately in the positioned design.…”

Section: Slidersmentioning

confidence: 99%

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pARam: Leveraging Parametric Design in Extended Reality to Support the Personalization of Artifacts for Personal Fabrication

Stemasov,

Demharter,

Rädler

et al. 2024

Proceedings of the CHI Conference on Human Factors in Computing Systems

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Extended Reality (XR) allows in-situ previewing of designs to be manufactured through Personal Fabrication (PF). These in-situ interactions exhibit advantages for PF, like incorporating the environment into the design process. However, design-for-fabrication in XR often happens through either highly complex 3D-modeling or is reduced to rudimentary adaptations of crowd-sourced models. We present pARam, a tool combining parametric designs (PDs) and XR, enabling in-situ configuration of artifacts for PF. In contrast to modeling-or search-focused approaches, pARam supports customization through embodied and practical inputs (e.g., gestures, recommendations) and evaluation (e.g., lighting estimation) without demanding complex 3D-modeling skills. We implemented pARam for HoloLens 2 and evaluated it (𝑛 = 20), comparing XR and desktop conditions. Users succeeded in choosing context-related parameters and took their environment into account for their configuration using pARam. We reflect on the prospects and challenges of PDs in XR to streamline complex design methods for PF while retaining suitable expressivity. CCS CONCEPTS• Human-centered computing → Human computer interaction (HCI); Mixed / augmented reality; Interaction design.

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“…The "Usable area of the glasses [was] very limited" (P3), referring to the limited field of view of the HoloLens. This sentiment was echoed by other participants (P5, 6,8,17).…”

Section: Desktop Rather Desktop Neutral Rather Param Parammentioning

confidence: 81%

Section: Design In and For Extended Realitymentioning

confidence: 99%

See 1 more Smart Citation

pARam: Leveraging Parametric Design in Extended Reality to Support the Personalization of Artifacts for Personal Fabrication

Stemasov,

Demharter,

Rädler

et al. 2024

Proceedings of the CHI Conference on Human Factors in Computing Systems

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“…Readers interested in this topic can find a recent state of the art by Camba, Company and Naya [2], where balancing geometric rules with perceptual principles is repeatedly advocated for. A recent work by Hähnlein et al [3] builds on the so-called "design principles" (previously explored by other authors like Agrawala et al [4]), which the authors define as "insights about sketching and design practices" (based on recommendations of expert designers on how to sketch). We consider them quite promising as a third type of information that may complement and enrich geometric and perceptual information.…”

Section: Related Workmentioning

confidence: 99%

A New Approach to Detect Hand-Drawn Dashed Lines in Engineering Sketches

Plumed,

Contero,

Naya

et al. 2024

Applied Sciences

Self Cite

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Sketched drawings sometimes include non-solid lines drawn as sets of consecutive strokes. They represent dashed lines, which are useful for various purposes. Recognizing such dashed lines while parsing drawings is reasonably straightforward if they are outlined with a ruler and compass but becomes challenging when they are hand-drawn. The problem is manageable if the strokes are drawn consecutively so we can leverage the entire sequence. However, it becomes more challenging if they are drawn unordered, and/or we do not have access to the sequence (like in batch vectorization). In this paper, we describe a new approach to identify groups of strokes as depicting single hand-drawn dashed lines. The approach does not use sequence information and is tolerant with irregularities and imprecisions of the strokes. Our goal is to identify hidden lines of sketched engineering line-drawings, which would enable the interpretation of line-drawings with hidden edges, which currently cannot be efficiently vectorized. We speculate that other fields like hand-drawn graph interpretation may also benefit from our approach.

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“…The hand-drawn schematic diagrams of civil engineering structures consist of the following unique characteristics. First, the sketches typically consist of large variation of drawing styles [1,4,11,16,30]. Some objects, such as the supports and loading conditions, are orientation dependent and have large variation in their aspect ratios.…”

Section: Introductionmentioning

confidence: 99%

Image‐based structural analysis for education purposes: A proof‐of‐concept study

Loong

Juan

Chang

2023

Comp Applic In Engineering

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In civil engineering education, hand‐drawn sketches of structural systems are commonly used for response analysis. Based on these sketches, students may determine the response of the structures either by hand calculations or via some specialized software through the construction of finite‐element models. The former method is prone to errors, while the latter method could be time‐consuming for inexperienced students. It would be convenient if the information within the hand‐drawn sketches could be automatically converted into computer‐recognizable objects for further structural analysis. To address this issue, a novel method entitled Image‐based Structural Analysis (ISA) is proposed as a proof of concept to determine the response of a linear‐elastic structure directly from the image of a hand‐drawn sketch. A selective search algorithm and a deep convolutional neural network are adopted to detect relevant objects in the images. Based on the bounding boxes and the classes of the objects, a finite element model is constructed for further structural response analysis. This study demonstrates the proposed ISA method via several hand‐drawn beams under loadings. Results show that the proposed method, which consists of a combination of artificial intelligence and semantic rules, can produce, and analyze structural models from hand‐drawn sketches.

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Sketch-Based Modeling in Mechanical Engineering Design: Current Status and Opportunities

Cited by 12 publications

References 113 publications

pARam: Leveraging Parametric Design in Extended Reality to Support the Personalization of Artifacts for Personal Fabrication

pARam: Leveraging Parametric Design in Extended Reality to Support the Personalization of Artifacts for Personal Fabrication

A New Approach to Detect Hand-Drawn Dashed Lines in Engineering Sketches

Image‐based structural analysis for education purposes: A proof‐of‐concept study

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