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39733

FEATURE RECOGNITION TECHNIQUE FOR TURNING OPERATION

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Last updated: 04 Jan 2025

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Abstract

ABSTRACT
The paper presents a new feature recognition technique which is considered the first
module of an implemented computer aided process planning system [CAPP] for turning
parts. The developed feature recognition technique involves the reconstruction of the
part design features (lines, arcs), which are extracted from the CAD file in the form of
manufacturing features (16 external features, and 10 internal features). It includes also
retrieval of important data related to the created features (dimensions, tolerances and
roughness) to be an efficient tool in process planning. Output data are displayed to the
user as design features, and manufacturing features with all required data technique for
manufacturing. A case study is given to demonstrate, and verify the proposed
algorithm.

DOI

10.21608/amme.2008.39733

Keywords

Feature Recognition, CAPP, CIM

Authors

First Name

EL-HAKIM

Last Name

A.

MiddleName

M.

Affiliation

Professor, Dpt. of Mechanical Engineering, Ain-Shams University, Cairo, Egypt.

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First Name

AFIFI

Last Name

A.

MiddleName

A.

Affiliation

Assist. Prof., Dpt. of Mechanical Engineering, Modern Academy , Cairo, Egypt.

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First Name

EL-MESALLAMY

Last Name

S.

MiddleName

A.

Affiliation

Egyptian Armed Forces.

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Volume

13

Article Issue

13th International Conference on Applied Mechanics and Mechanical Engineering.

Related Issue

6264

Issue Date

2008-05-01

Receive Date

2019-07-08

Publish Date

2008-05-01

Page Start

121

Page End

134

Print ISSN

2636-4352

Online ISSN

2636-4360

Link

https://amme.journals.ekb.eg/article_39733.html

Detail API

https://amme.journals.ekb.eg/service?article_code=39733

Order

117

Type

Original Article

Type Code

831

Publication Type

Journal

Publication Title

The International Conference on Applied Mechanics and Mechanical Engineering

Publication Link

https://amme.journals.ekb.eg/

MainTitle

FEATURE RECOGNITION TECHNIQUE FOR TURNING OPERATION

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Article

Created At

22 Jan 2023