2001
DOI: 10.1016/s0924-0136(01)00971-2
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A decision support system for sheet metal blanking process parameters selection

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Cited by 16 publications
(7 citation statements)
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“…The capability of the system was illustrated with the help of single stage deep drawing, three step deep drawing, and deep drawing with embossing. A user friendly, menu driven decision support system (DSS) was also developed by Faura et al for sheet metal blanking operation (Faura et al, 2001). The DSS consists of relational database having technicaleconomic information and collection of processing algorithms created to apply the knowhow to the model.…”
Section: Process Designmentioning
confidence: 99%
See 1 more Smart Citation
“…The capability of the system was illustrated with the help of single stage deep drawing, three step deep drawing, and deep drawing with embossing. A user friendly, menu driven decision support system (DSS) was also developed by Faura et al for sheet metal blanking operation (Faura et al, 2001). The DSS consists of relational database having technicaleconomic information and collection of processing algorithms created to apply the knowhow to the model.…”
Section: Process Designmentioning
confidence: 99%
“…The technical knowledge is based on many experiments relating empirically the blanking clearance with edge draw-in, the penetration depth of cracks, and burr height. By providing dialog boxes to facilitate data input and display of output results, it is possible to predict the impact of blanking parameters on the cost and quality (Faura et al, 2001). Other than the ES described above, there are expert systems that are helpful for web based manufacturing.…”
Section: Process Designmentioning
confidence: 99%
“…Research in process planning has focused mostly on industrial processes that involve metal removal [9], although there are researchers working on studies on process planning and CAPP systems in other industrial fields, such as shaping sheet metal [13].…”
Section: Capp Systemsmentioning
confidence: 99%
“…Hambli, çalışmasında kesme boşluğu ve zımba kaplamasının çapak boyuna etkilerini incelemiş ve Yapay Sinir Ağları (Neural Network) yöntemiyle tahminler geliştirmiştir [12][13]. Faura ve arkadaşları üretim parametrelerine göre değişen bir karar verme sistemi geliştirerek kesme parametrelerinin maliyete etkisini araştırmışlardır [14]. Bu çalışmada, kesme boşluğu ve sac malzeme kalınlığına göre, kesme düzlüğü derinliği, kopma boyu, çapak yüksekliği ve kesme kuvvetlerinin değişimi deneysel olarak incelenmiştir.…”
Section: Gi̇ri̇ş (Introduction)unclassified