Content area

Abstract

This paper contributes to advancing the quality of 3D procedural models by proposing practices based on the principle of “how to avoid doing it wrong” derived from analyzing negative knowledge in CAD modeling. The described framework adopts the three levels of quality identified in the literature—usability, reusability, and design intent richness—while focusing specifically on deriving best practices to prevent failures based on negative knowledge related to reusability. The framework is built on the premise that quality issues hindering reusability can be categorized into three interrelated but largely independent types, each affecting the sketches, datums, or features within a procedural model’s tree structure. In this work, the study of sketches is addressed. The negative impact of typical failures, identified through representative case studies that illustrate both design and redesign errors, is analyzed to extract best practices that ensure CAD model reusability. While this study results in a practical guide for avoiding sketch-related errors that compromise the reusability of CAD models, the main contribution lies in demonstrating a framework that transforms negative knowledge into effective best practices.

Details

1009240
Business indexing term
Title
From Negative Knowledge to Best Practices for Enhancing Reusability of Sketches in Procedural 3D CAD Models
Publication title
Designs; Basel
Volume
9
Issue
6
First page
132
Number of pages
26
Publication year
2025
Publication date
2025
Publisher
MDPI AG
Place of publication
Basel
Country of publication
Switzerland
Publication subject
e-ISSN
24119660
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
Publication history
 
 
Online publication date
2025-11-25
Milestone dates
2025-10-27 (Received); 2025-11-21 (Accepted)
Publication history
 
 
   First posting date
25 Nov 2025
ProQuest document ID
3286271302
Document URL
https://www.proquest.com/scholarly-journals/negative-knowledge-best-practices-enhancing/docview/3286271302/se-2?accountid=208611
Copyright
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2025-12-24
Database
ProQuest One Academic