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Buffer allocation and performance modeling in asynchronous assembly system operations: An artificial neural network metamodeling approach

Authors
Journal
Applied Soft Computing
1568-4946
Publisher
Elsevier
Publication Date
Volume
7
Issue
3
Identifiers
DOI: 10.1016/j.asoc.2006.06.002
Keywords
  • Artificial Neural Networks
  • Metamodel
  • Assembly Systems
  • Simulation
Disciplines
  • Computer Science
  • Design
  • Engineering

Abstract

Abstract This article investigates metamodeling opportunities in buffer allocation and performance modeling in asynchronous assembly systems (AAS). Practical challenges to properly design these complex systems are emphasized. A critical review of various approaches in modeling and evaluation of assembly systems reported in the recently published literature, with a special emphasis on the buffer allocation problems, is given. Various applications of artificial intelligence techniques on manufacturing systems problems, particularly those related to artificial neural networks, are also reviewed. Advantages and the drawbacks of the metamodeling approach are discussed. In this context, a metamodeling application on AAS buffer design/performance modeling problems in an attempt to extend the application domain of metamodeling approach to manufacturing/assembly systems is presented. An artificial neural network (ANN) metamodel is developed for a simulation model of an AAS. The ANN and regression metamodels for each AAS are compared with respect to their deviations from the simulation results. The analysis shows that the ANN metamodels can successfully be used to model of AASs. Consequently, one concludes that practising engineers involved in assembly system design can potentially benefit from the advantages of the metamodeling approach.

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