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Sequencing of interacting prismatic machining features for process planning
KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems. National Research Council of Canada. (Sustainable Manufacturing)ORCID iD: 0000-0001-8679-8049
2007 (English)In: Computers in industry (Print), ISSN 0166-3615, E-ISSN 1872-6194, Vol. 58, no 4, p. 295-303Article in journal (Refereed) Published
Abstract [en]

oday, feature-based process planning has been popular in academia and industry with its ability to rigorously integrate design and manufacturing. To date, research on feature sequencing is mainly focused on using expert systems or knowledge-based systems, geometric based approaches, unsupervised-leaming or artificial neural network, and genetic algorithms. The approach presented in this paper, however, is a hybrid one using both knowledge-based rules and geometric reasoning rules. In addition to feature sequencing rules formulation, our research contributions consist of: (1) determining machining precedence constraints by a set of defined knowledge-based rules, (2) grouping machining features into setups based on tool approaching directions, and (3) sequencing features within each setup through geometric reasoning. The sequence of materials (features) to be removed depends on two types of interactions: adjacent interaction and volumetric interaction. A set of rules for geometric reasoning is therefore developed to generate feature sequence. The developed approach has been implemented as the Sequence Generator module in a Distributed Process Planning system and is validated through a case study.

Place, publisher, year, edition, pages
Elsevier, 2007. Vol. 58, no 4, p. 295-303
Keywords [en]
process planning, machining features, feature interaction, feature sequencing, geometric reasoning
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:kth:diva-205710DOI: 10.1016/j.compind.2006.07.003ISI: 000245793700001Scopus ID: 2-s2.0-33947229517OAI: oai:DiVA.org:kth-205710DiVA, id: diva2:1090216
Note

QC 20170628

Available from: 2017-04-23 Created: 2017-04-23 Last updated: 2018-01-13Bibliographically approved

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Wang, Lihui

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CiteExportLink to record
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  • apa
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  • nn-NB
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Output format
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