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

  • Authors:

  • Fulya Altiparmak;Berna Dengiz;Akif A. Bulgak

  • Affiliations:

  • Department of Industrial Engineering, Gazi University, Celal Bayar Blvd., 06570 Maltepe, Ankara, Turkey;Department of Industrial Engineering, Baskent University, Baglica Campus, 06530 Ankara, Turkey;Department of Mechanical and Industrial Engineering, Concordia University, 1455 de Maisonneuve Blvd. West, Montreal, Que., Canada H3G 1M8

  • Venue:
  • Applied Soft Computing
  • Year:
  • 2007

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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.