An artificial neural network based simulation metamodeling approach for dual resource constrained assembly line

Yildiz G., Eski O.

ARTIFICIAL NEURAL NETWORKS - ICANN 2006, PT 2, cilt.4132, ss.1002-1011, 2006 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 4132
  • Basım Tarihi: 2006
  • Dergi Adı: ARTIFICIAL NEURAL NETWORKS - ICANN 2006, PT 2
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, EMBASE, MathSciNet, Philosopher's Index, zbMATH
  • Sayfa Sayıları: ss.1002-1011
  • Dokuz Eylül Üniversitesi Adresli: Evet

Özet

The main objective of this study is to find the optimum values of design and operational parameters related to worker flexibility in a Dual Resource Constrained (DRC) assembly line considering the performance measures of Hourly Production Rate (HPR), Throughput Time (TT) and Number of Worker Transfers (NWT). We used Artificial Neural Networks (ANN) as a simulation metamodel to estimate DRC assembly line performances for all possible alternatives. All alternatives were evaluated with respect to a utility function which consists of weighted sum of normalized performance measures.