Computationally efficient approach for the integration of design and manufacturing in CE

Ozturk N., Ozturk F.

CONCURRENT ENGINEERING-RESEARCH AND APPLICATIONS, cilt.8, sa.2, ss.144-156, 2000 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 8 Sayı: 2
  • Basım Tarihi: 2000
  • Doi Numarası: 10.1106/1wve-1ce9-my9d-tlpv
  • Dergi Adı: CONCURRENT ENGINEERING-RESEARCH AND APPLICATIONS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.144-156
  • Anahtar Kelimeler: feature recognition, neural networks, concurrent engineering, PATTERN-RECOGNITION TECHNIQUES, NEURAL-NETWORK, BOUNDARY REPRESENTATIONS, DISCRIMINANT-ANALYSIS, AUTOMATIC EXTRACTION, MACHINING FEATURES, FIXTURE DESIGN, SYSTEMS, MODEL, DECOMPOSITION
  • Bursa Uludağ Üniversitesi Adresli: Evet

Özet

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.