An Artificial Neural Network Based Simulation Metamodeling Approach for Dual Resource Constrained Assembly Line
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.
KeywordsArtificial Neural Network Artificial Neural Network Model Assembly Line Work Flexibility Throughput Time
Unable to display preview. Download preview PDF.
- 8.Kilmer, R., Smith, A., Shuman, L.: An Emergency Department Simulation and a Neural Network Metamodel. Journal of the Society for Health Systems 5(3), 63–79 (1997)Google Scholar
- 10.Pierreval, H.: Training a Neural Network by Simulation for Dispatching Problems. In: Proceedings of the Third Rensselaer International Conference on Computer Integrated Engineering, pp. 332–336 (1992)Google Scholar
- 15.Yıldız, G.: An Application of Typical When/Where Rule Pairs in Dual Resource Constrained (DRC) Assembly Line with Closed-Loop Conveyor. In: Proceedings of 35th International Conference of Computers and Industrial Engineering, pp. 2185–2190 (2005)Google Scholar