Recognition of Machined Features from Solid Database of Prismatic Components
The automation of process planning requires features to he recognized directly from a computer aided design (CAD) system. This paper presents a new technique for recognition of machined features using point classification technique with a logic-based approach. Boundary r~presentation of solid model...
| Main Authors: | , |
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| Format: | Article |
| Language: | English English |
| Published: |
Universiti Putra Malaysia Press
1997
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| Online Access: | http://psasir.upm.edu.my/id/eprint/3373/ http://psasir.upm.edu.my/id/eprint/3373/1/Recognition_of_Machined_Features_from_Solid_Database_of.pdf |
| _version_ | 1848839512823693312 |
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| author | Ismail, Napsiah Abu Bakar, Nooh |
| author_facet | Ismail, Napsiah Abu Bakar, Nooh |
| author_sort | Ismail, Napsiah |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | The automation of process planning requires features to he recognized directly from a computer aided design (CAD) system. This paper presents a new
technique for recognition of machined features using point classification technique with a logic-based approach. Boundary r~presentation of solid modelling is used to model a prismatic component. The system is developed
entirely in the AutoCAD environment, and the AutoLISP language was used to build the recognition system as it has direct access to the database. Test results
are presented to demonstrate the capabilities of the feature recognition algorithm. This paper concentrates on depression and protrusion type machined
features. |
| first_indexed | 2025-11-15T07:12:38Z |
| format | Article |
| id | upm-3373 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-15T07:12:38Z |
| publishDate | 1997 |
| publisher | Universiti Putra Malaysia Press |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-33732013-05-27T07:07:55Z http://psasir.upm.edu.my/id/eprint/3373/ Recognition of Machined Features from Solid Database of Prismatic Components Ismail, Napsiah Abu Bakar, Nooh The automation of process planning requires features to he recognized directly from a computer aided design (CAD) system. This paper presents a new technique for recognition of machined features using point classification technique with a logic-based approach. Boundary r~presentation of solid modelling is used to model a prismatic component. The system is developed entirely in the AutoCAD environment, and the AutoLISP language was used to build the recognition system as it has direct access to the database. Test results are presented to demonstrate the capabilities of the feature recognition algorithm. This paper concentrates on depression and protrusion type machined features. Universiti Putra Malaysia Press 1997 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/3373/1/Recognition_of_Machined_Features_from_Solid_Database_of.pdf Ismail, Napsiah and Abu Bakar, Nooh (1997) Recognition of Machined Features from Solid Database of Prismatic Components. Pertanika Journal of Science & Technology, 5 (2). pp. 231-240. ISSN 0128-7680 English |
| spellingShingle | Ismail, Napsiah Abu Bakar, Nooh Recognition of Machined Features from Solid Database of Prismatic Components |
| title | Recognition of Machined Features from Solid Database of
Prismatic Components |
| title_full | Recognition of Machined Features from Solid Database of
Prismatic Components |
| title_fullStr | Recognition of Machined Features from Solid Database of
Prismatic Components |
| title_full_unstemmed | Recognition of Machined Features from Solid Database of
Prismatic Components |
| title_short | Recognition of Machined Features from Solid Database of
Prismatic Components |
| title_sort | recognition of machined features from solid database of
prismatic components |
| url | http://psasir.upm.edu.my/id/eprint/3373/ http://psasir.upm.edu.my/id/eprint/3373/1/Recognition_of_Machined_Features_from_Solid_Database_of.pdf |