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Design of a neuro-fuzzy-regression expert system to estimate cost in a flexible jobshop automated manufacturing system

Fazlollahtabar, H ; Sharif University of Technology | 2013

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  1. Type of Document: Article
  2. DOI: 10.1007/s00170-012-4610-5
  3. Publisher: 2013
  4. Abstract:
  5. We propose a cost estimation model based on a fuzzy rule backpropagation network, configuring the rules to estimate the cost under uncertainty. A multiple linear regression analysis is applied to analyze the rules and identify the effective rules for cost estimation. Then, using a dynamic programming approach, we determine the optimal path of the manufacturing network. Finally, an application of this model is illustrated through a numerical example showing the effectiveness of the proposed model for solving the cost estimation problem under uncertainty
  6. Keywords:
  7. Automated manufacturing system ; Cost estimation ; Neural network ; Automated manufacturing systems ; Backpropagation network ; Cost estimation models ; Cost estimations ; Flexible job shops ; Manufacturing networks ; Multiple linear regression analysis ; Optimal paths ; Cost estimating ; Expert systems ; Fuzzy logic ; Linear regression ; Neural networks ; Production engineering ; Regression analysis ; Uncertainty analysis ; Cost benefit analysis
  8. Source: International Journal of Advanced Manufacturing Technology ; Volume 67, Issue 5-8 , 2013 , Pages 1809-1823 ; 02683768 (ISSN)
  9. URL: http://link.springer.com/article/10.1007%2Fs00170-012-4610-5