Artificial Neural Network for Assembly Line Balancing

  • Pius Ucheagwu Department of Production Engineering, University of Benin,Benin
  • Johnmary Ugochukwu Okeke Department of Civil Engineering, University of Benin, Benin
  • Christian I. Okonta Department of Civil Engineering, University of Benin, Benin
  • Efosa Osamuyimwen Department of Physics, University of Benin, Benin
Keywords: Assembly, Line balancing, Artificial Neural Network.

Abstract

This study examines an assembly line balancing using artificial neural network. An organization that balances the unique workloads must respect the limits and restrictions that hinder the assembly. To optimize the very specific operations, balancing an assembly line may require different methods, including: genetic algorithm, heuristic approach, simulation techniques, the ant colony optimization (ACO), etc., but in this study, artificial neural networks was applied to solving problems of assembly line balancing.  This study also explores the characteristics of the assembly line and the classification of the assembly balancing problems, suggesting as an artificial neural network solve.

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Published
2019-11-10
How to Cite
Ucheagwu, P., Ugochukwu Okeke, J., I. Okonta, C., & Osamuyimwen, E. (2019). Artificial Neural Network for Assembly Line Balancing. American International Journal of Sciences and Engineering Research, 2(2), 69-78. https://doi.org/10.46545/aijser.v2i2.121
Section
Research Articles