A Production Planning Model using Fuzzy Neural Network: A Case Study of an Automobile Industry
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10.5120/5032-7183 |
Rashmi Sharma and Ashok K Sinha. Article: A Production Planning Model using Fuzzy Neural Network: A Case Study of an Automobile Industry. International Journal of Computer Applications 40(4):19-22, February 2012. Full text available. BibTeX
@article{key:article,
author = {Rashmi Sharma and Ashok K. Sinha},
title = {Article: A Production Planning Model using Fuzzy Neural Network: A Case Study of an Automobile Industry},
journal = {International Journal of Computer Applications},
year = {2012},
volume = {40},
number = {4},
pages = {19-22},
month = {February},
note = {Full text available}
}
Abstract
The production forecast based on order received is adversely affected by deterrent factors in supply chain management (SCM). Although several mathematical models have been attempted by researchers, the accuracy of such forecast still need to be improved. In the present paper the various deterrent factors influencing the supply chain have been considered adequately to forecast the production plan on the order received. The model is based on the machine learning using fuzzy neural network architecture and validated with real data on automobile production. The result is compared with that obtained by conventional multiple regression model and the former is found to be quite satisfactory, the error being as low as 2.9847 e-006
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