Production adjusting method based on predicted distribution of production and inventory using dynamic Bayesian network

Yeong Hwa Park, Ji Sun Shin, Ki Yun Woo, Fumihiro Shoji, HeeHyol Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In general, the production quantities and the delivered goods are changed randomly, and then the total stock is also changed randomly. This paper deals with the production and inventory control of an automobile production part line using the Dynamic Bayesian Network. Bayesian Network indicates the quantitative relations between the individual variables by the conditional probability. The probabilistic distribution of the total stock is calculated through the propagation of the probability on the network. Moreover, an adjusting rule of the production quantities to maintain the probability of the lower bound value and the upper bound value of the total stock to certain values is shown.

Original languageEnglish
Title of host publicationProceedings of the 14th International Symposium on Artificial Life and Robotics, AROB 14th'09
Pages63-68
Number of pages6
Publication statusPublished - 2009
Event14th International Symposium on Artificial Life and Robotics, AROB 14th'09 - Oita
Duration: 2008 Feb 52009 Feb 7

Other

Other14th International Symposium on Artificial Life and Robotics, AROB 14th'09
CityOita
Period08/2/509/2/7

Fingerprint

Bayesian networks
Inventory control
Production control
Automobiles

Keywords

  • Delivery data
  • Dynamic Bayesian network
  • Predicted distribution
  • Production adjusting method

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction

Cite this

Park, Y. H., Shin, J. S., Woo, K. Y., Shoji, F., & Lee, H. (2009). Production adjusting method based on predicted distribution of production and inventory using dynamic Bayesian network. In Proceedings of the 14th International Symposium on Artificial Life and Robotics, AROB 14th'09 (pp. 63-68)

Production adjusting method based on predicted distribution of production and inventory using dynamic Bayesian network. / Park, Yeong Hwa; Shin, Ji Sun; Woo, Ki Yun; Shoji, Fumihiro; Lee, HeeHyol.

Proceedings of the 14th International Symposium on Artificial Life and Robotics, AROB 14th'09. 2009. p. 63-68.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Park, YH, Shin, JS, Woo, KY, Shoji, F & Lee, H 2009, Production adjusting method based on predicted distribution of production and inventory using dynamic Bayesian network. in Proceedings of the 14th International Symposium on Artificial Life and Robotics, AROB 14th'09. pp. 63-68, 14th International Symposium on Artificial Life and Robotics, AROB 14th'09, Oita, 08/2/5.
Park YH, Shin JS, Woo KY, Shoji F, Lee H. Production adjusting method based on predicted distribution of production and inventory using dynamic Bayesian network. In Proceedings of the 14th International Symposium on Artificial Life and Robotics, AROB 14th'09. 2009. p. 63-68
Park, Yeong Hwa ; Shin, Ji Sun ; Woo, Ki Yun ; Shoji, Fumihiro ; Lee, HeeHyol. / Production adjusting method based on predicted distribution of production and inventory using dynamic Bayesian network. Proceedings of the 14th International Symposium on Artificial Life and Robotics, AROB 14th'09. 2009. pp. 63-68
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