A constraint redundancy elimination strategy to improve design reuse in parametric modeling

González-Lluch, Carmen; Plumed, Raquel; Pérez-López, David; Contero, Manuel; Camba, Jorge D.

doi:10.1016/j.compind.2021.103460

Cited by 6 publications

(3 citation statements)

References 32 publications

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“…It should be noted here that, as revealed by a recent study by Gonzalez-Lluch et al [37], a userspecified GCS often contains redundant constraints which can hinder design reusability. It is thus necessary to eliminate such redundancies before handling SAI (B), using tools like the one presented in [37]. For this reason, this work will not focus on the third type.…”

Section: Shape-associativity Inconsistency (Sai) Bmentioning

confidence: 86%

“…Geometric constraint solving is a well-established field, and many effective algorithms have been made available [26,36]. It should be noted here that, as revealed by a recent study by Gonzalez-Lluch et al [37], a userspecified GCS often contains redundant constraints which can hinder design reusability. It is thus necessary to eliminate such redundancies before handling SAI (B), using tools like the one presented in [37].…”

Section: Shape-associativity Inconsistency (Sai) Bmentioning

confidence: 96%

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Variational Direct Modeling: A framework towards integration of parametric modeling and direct modeling in CAD

Zou,

Feng,

Gao

2023

Preprint

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Feature-based parametric modeling is the de facto standard in CAD. Boundary representation-based direct modeling is another CAD paradigm developed recently. They have complementary advantages and limitations, thereby offering huge potential for improvement towards an integrated CAD modeling scheme. Most existing integration methods are developed by industry and typically treat direct edits as pseudo-features, where little can be said about seamless integration. This paper presents an alternative method for seamless parametric/direct integration, which allows parametric and direct edits to work in a unified way. The fundamental issues and challenges of parametric/direct integration are first explained. A framework is then proposed to handle those information inconsistencies, based on a detection-then-resolution strategy. Algorithms that can systematically detect and resolve all possible types of information inconsistencies are also given to implement the framework. With them, model validity can be maintained during the whole model editing process, and then the discrepancy between direct edits and parametric edits can be resolved. The effectiveness of the proposed approach has been shown with a series of case studies and comparisons, based on a preliminary prototype.

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Section: Shape-associativity Inconsistency (Sai) Bmentioning

confidence: 86%

Section: Shape-associativity Inconsistency (Sai) Bmentioning

confidence: 96%

Variational Direct Modeling: A framework towards integration of parametric modeling and direct modeling in CAD

Zou,

Feng,

Gao

2023

Preprint

View full text Add to dashboard Cite

show abstract

“…10 Typically, this process yields CAD models that closely approximate real-world objects, thereby reducing the occurrence of engineering errors and enhancing solution visualization. 11 The subsequent sections provide a concise overview of three widely adopted modeling approaches currently in use.…”

Section: Cad Modeling Approaches and Dss Explorationmentioning

confidence: 99%

A comparative analysis of CAD modeling approaches for design solution space exploration

Li,

Ye,

Zhang

et al. 2024

Advances in Mechanical Engineering

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Design solution space (DSS) exploration is a pivotal process for comprehending design challenges and identifying diverse solution alternatives based on varying requirements. Computer-aided design (CAD) approaches, such as parametric design, knowledge-based design, and generative design, have proven successful in DSS exploration. However, a comparative study evaluating their performance is lacking in the technical literature. This paper addresses this gap by conducting a comparative analysis of these approaches regarding their performance in exploring DSS. The research begins by providing an overview of parametric design, knowledge-based design, and generative design, establishing the foundation for the study. Six evaluation criteria are identified based on the DSS exploration process. A qualitative analysis is then conducted, considering these criteria, to objectively assess the performance of each modeling approach. The results highlight the strengths and weaknesses of each approach, revealing that DSS exploration success is directly tied to the quantity of implemented knowledge. The results also emphasize the complementarity of those approaches, as their strengths and weaknesses are based on different problem-solving logics, demonstrating the synergy that can be achieved through strategic combinations of them. Additionally, the paper discusses open issues related to DSS exploration, contributing valuable insights for future developments in this field.

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Adaptive sampling for corrugated plate digitization using a laser displacement sensor

Wu,

Qi,

Chen

et al. 2024

Sci. China Technol. Sci.

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A constraint redundancy elimination strategy to improve design reuse in parametric modeling

Cited by 6 publications

References 32 publications

Variational Direct Modeling: A framework towards integration of parametric modeling and direct modeling in CAD

Variational Direct Modeling: A framework towards integration of parametric modeling and direct modeling in CAD

A comparative analysis of CAD modeling approaches for design solution space exploration

Adaptive sampling for corrugated plate digitization using a laser displacement sensor

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