Integration of parametric modelling in web-based knowledge-based engineering applications

Knowledge-based Engineering (KBE) is a methodology to efficiently handle complex and iterative processes as well as simple recurring tasks in CAD-based product design. Even though Knowledge-based Engineering’s roots go back as far as the late 20th century, potential of attractive research is still g...

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Veröffentlicht in:Advanced engineering informatics 2022-01, Vol.51, p.101492, Article 101492
Hauptverfasser: Ortner-Pichler, Alexander, Landschützer, Christian
Format: Artikel
Sprache:eng
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Zusammenfassung:Knowledge-based Engineering (KBE) is a methodology to efficiently handle complex and iterative processes as well as simple recurring tasks in CAD-based product design. Even though Knowledge-based Engineering’s roots go back as far as the late 20th century, potential of attractive research is still given. As geometry handling in native full Knowledge-based Engineering approaches can still be a challenging and time-consuming task, approaches for utilizing the parametric modeling capabilities of high-level CAD packages were developed. With the rise of web-based technologies, bringing these utilizing approaches to the Web, seems to be the next step in the technological development of Knowledge-based Engineering applications. Even though KBE has found its way to the Web already in many different sectors, planning of large systems based on existing machinery and subsystems, is still at least one open field left. This article connects to a newly developed KBE methodology, tailored for the use within intralogistic system planning, but widely usable in other systems and proposes a software architecture to utilize CAD’s capabilities regarding geometry creation and manipulation by the parametric modelling method in a web-based environment. The architecture is especially designed for implementations of the Knowledge-based Engineering method described within the research context in the field of intralogistics system planning.
ISSN:1474-0346
1873-5320
DOI:10.1016/j.aei.2021.101492