| dc.description.abstract | This work has the objective to present a methodology to predict product sales using artificial neural networks, as a study case was treated the periodic sales volume of an industry which develops products to the telecommunication area. Nowadays, realize sales prediction in the companies is crucial to reduce the costs with human resources, materials and increase the liquidity, without loose the quality which the clients are familiarized, avoiding delays in the products deliveries. The problem which this dissertation tackles is important to several kinds of industries, once a precise sales prediction allow the industries to organize themselves in a better way. It allows the company to know anticipated the material to be acquired, align their productions lines, avoiding an abrupt change in the factory layouts and offers a better control of their stocks. The study realized and the solution proposed are based on Artificial Neural Networks, applied to predict product sales using the sales history and the insertion | en |
