The Model of Raw and Packaging Materials Cost Estimation Using Neural Networks
Jasna Gamulin
Last modified: 2010-07-13
Abstract
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Raw and packaging materials cost estimation for the next year is a regular procedure in purchasing departments and is a part of company's annual plan. For the medium size company producing approximately 50 products the number of items that should be purchased amounts from 500 to 1000. That is the reason why the process of cost estimation in the „classical“, iterative way is so time consuming and demanding. In this paper a model has been developed in order to predict raw and packaging materials cost based on data on realized quantities and prices of raw and packaging materials during the six years in a medium-sized company producing food and dietetic products. The model is using the technique of neural networks (Neural Networks - NN). The result achieved using the model is compared to prices actually realized in a given period and also to the prices estimated in a classical way. The comparison of the prices showed encouraging results making the prospective of using the proposed model when quick cost estimation is needed, quite feasible.