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S., Tichkiewitch. A Process planning system with feature based neural network search strategy for aluminum extrusion die manufacturing. (). King Mongkut's University of Technology North Bangkok. Central Library. : , 2009.
A Process planning system with feature based neural network search strategy for aluminum extrusion die manufacturing
Name: S. Butdee
Organization :
King Mongkuts University of Technology North Bangkok. Faculty of Engineering. Department of Production Engineering. IMSRC
Email :
stb@kmutnb.ac.th
Name: C. Noomtong
Organization :
King Mongkuts University of Technology North Bangkok. Faculty of Engineering. Department of Production Engineering. IMSRC
Name: S., Tichkiewitch
Organization :
Grenoble Institute of Technology. G-SCOP Laboratory
keyword:
Feature-based neural network
LCSH:
Process planning
Abstract:
Aluminum extrusion die manufacturing is a critical task for productive improvement and increasing potential of competition in aluminum extrusion industry. It causes to meet the efficiency not only consistent quality but also time and production cost reduction. Die manufacturing consists first of die design and process planning in order to make a die for extruding the customers requirement products. The efficiency of die design and process planning are based on the knowledge and experience of die design and die manufacturer experts. This knowledge has been formulated into a computer system called the knowledge-based system. It can be reused to support a new die design and process planning. Such knowledge can be extracted directly from die geometry which is composed of die features. These features are stored in die feature library to be prepared for producing a new die manufacturing. Die geometry is defined according to the characteristics of the profile so we can reuse die features from the previous similar profile design cases. This paper presents the CaseXpert Process Planning System for die manufacturing based on feature based neural network technique. Die manufacturing cases in the case library would be retrieved with searching and learning method by neural network for reusing or revising it to build a die design and process planning when a new case is similar with the previous die manufacturing cases. The results of the system are dies design and machining process. The system has been successfully tested, it has been proved that the system can reduce planning time and respond high consistent plans.
King Mongkut's University of Technology North Bangkok. Central Library
Address:
Bangkok
Email:
library@kmutnb.ac.th
Created:
2009
Modified:
2011-03-21
Issued:
2011-03-15
บทความ/Article
application/pdf
BibliograpyCitation :
Asian International Journal of Science and Technology in Production and Manufacturing Engineering. Vol. 2, No.1 (Jan.- Mar. 2009), p. 137-157
eng
©copyrights King Mongkut's University of Technology North Bangkok
RightsAccess:
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0.039582 วินาที
S. Butdee
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C. Noomtong
| Title | Contributor | Type |
|---|---|---|
| A Process planning system with feature based neural network search strategy for aluminum extrusion die manufacturing
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ S. Butdee;C. Noomtong;S., Tichkiewitch | บทความ/Article |
S., Tichkiewitch
| Title | Contributor | Type |
|---|---|---|
| A Process planning system with feature based neural network search strategy for aluminum extrusion die manufacturing
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ S. Butdee;C. Noomtong;S., Tichkiewitch | บทความ/Article |