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A Feature-Based Approach to Automating High-Level Process Planning

<p>High-level process planning plays an important role in determining candidate process domains at the configuration design stage. Changing the processes domainslater increases the product development cycle and the product development cost. Therefore, determining the most appropriate manufacturing processes at thebeginning stages of the design process becomes critical. However, high-level process planning systems have traditionally lacked integration of design synthesis anddesign evaluation. The main objective of this research has been to develop a FEature-Based Design And Process Planning (FEBDAPP) system that helps designers decide whether ornot the design is worth pursuing by providing manufacturing advice to designers during the design process. In order to achieve the main objective, the following taskshave been accomplished: (1) developed a hybrid system incorporating design by feature and feature recognition approaches capable of reducing the complexity offeature recognition algorithms without sacrificing flexibility in creating a part design, (2) developed a comprehensive set of feature mapping algorithms capable oftransforming a primary part representation into a secondary part representation that is required as input to downstream applications, and (3) developed aCAD-based interface capable of integrating a current CAD system with a high-level process planning system.This research contributes significantly to the availability of early design tools that enhance and at the same time shorten the design process cycle. The implementationof feature technology in this research will support the development of applications such as tooling cost estimation and manufacturability analysis. Finally, theFEBDAPP system is intended to be an effective concurrent engineering tool that bridges the gap between design and manufacturing.<P>

Identiferoai:union.ndltd.org:NCSU/oai:NCSU:etd-20010711-140320
Date12 July 2001
CreatorsFebransyah, Ade
ContributorsDr. Ezat T. Sanii, Dr. Denis R. Cormier, Dr. Michael G. Kay, Dr. Fen Wu
PublisherNCSU
Source SetsNorth Carolina State University
LanguageEnglish
Detected LanguageEnglish
Typetext
Formatapplication/pdf
Sourcehttp://www.lib.ncsu.edu/theses/available/etd-20010711-140320
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