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Title: | Computationally efficient approach for the integration of design and manufacturing in CE |
Authors: | Uludağ Üniversitesi/Mühendislik Fakültesi/Endüstri Mühendisliği Bölümü. Uludağ Üniversitesi/Mühendislik Fakültesi/Makine Mühendisliği Bölümü. Öztürk, Nursel Öztürk, Ferruh AAG-9923-2021 AAG-9336-2021 7005688805 56271685800 |
Keywords: | Computer science Operations research & management science Engineering Feature recognition Neural networks Concurrent engineering Pattern-recognition techniques Neural-network Boundary representations Discriminant-analysis Automatic extraction Model Machining features Fixture design Systems Decomposition Automation Competition Computer aided design Computer aided manufacturing Computer integrated manufacturing Feature extraction Neural networks Productivity Automation systems |
Issue Date: | 2000 |
Publisher: | Sage Publications |
Citation: | Öztürk, F. ve Öztürk, N. (2000). "Computationally efficient approach for the integration of design and manufacturing in CE". Concurrent Engineering-Research and Applications, 8(2), 144-156. |
Abstract: | Today, companies are faced with fierce competition which is characterized by the necessity to bring the higher quality products and lower priced products to the market in shorter times than their competitors. The key to the success of organizations is the effective integration of design and applications following design such as machining, process planning, analysis, assembly, inspection etc. It was seen that effectiveness of the traditional CIM systems is not satisfactory to ensure competitiveness and high productivity. Recently, the concept of CE has been proposed to overcome the problems exist in integration. However, it has been recognized by both academic and industrial environments that efficient application of CE is still not achieved. In this research, STEP based feature recognition using neural networks is presented to develop feature based model and to enhance the integration of production activities in CE. |
URI: | https://doi.org/10.1106/1WVE-1CE9-MY9D-TLPV http://hdl.handle.net/11452/22239 |
ISSN: | 1063-293X |
Appears in Collections: | Scopus Web of Science |
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