Methodology Evaluation of Order Forecast in Small Manufacturing Industry-Take Taichung C Co. as an Example

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Title:	Methodology Evaluation of Order Forecast in Small Manufacturing Industry-Take Taichung C Co. as an Example
Authors:	Evan Lin
Contributors:	Department of Information Science and Applications
Keywords:	Forecast, Artificial Neural Network, Fuzzy Neural Network, order of goods.
Date:	2009
Issue Date:	2009-11-17 11:54:28 (UTC+0)
Publisher:	Asia University
Abstract:	The relation between an enterprise and its customers is orders of goods. No benefit will be gotten if there is no order. In addition, forecast of the number of orders is very important for an enterprise, because the number of orders affects production utility. A sudden large number of orders causes the paucity of materials, parts, and human powers. On the other hand, lack of orders causes the waste of enterprise?s resources. Using case data of a real company, in study applies four approaches, including Moving Average, Exponential Smoothing, Artificial Neural Network, and Fuzzy Neural Network, to forecast the company?s orders of goods. The results indicate that Fuzzy Neural Network approach has the best forecast results.
Appears in Collections:	[Department of Applied Informatics and Multimedia] Theses & dissertations

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