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Artificial Neural Network Forecasting

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Zero defect as a goal for the manufacturing sector especially when the factory engage in global market which the market is required a highest grade quality product. A defect will occur when it is fail to meet the intended design. Hence, defect prediction methods play an important role to forecast the number of product defect. For this study, Artificial Neural Network (ANN) used to forecast the product defect in furniture manufacturing in in order to develop a well suit ANN model for the product defect prediction and obtain an accurate prediction defect number for decision making. Colour defect as one of the product defect category. Therefore, data of colour defect was collected within eight (8) working hours for fourteen (14) days and the analysis process carried out by MATLAB R2015a application using the neural network toolbox. The neural network framework for the colour defect prediction was developed with the minimum error. The company is able to conduct prediction process with the framework and make a better decision based on the result in order to reach their goal.   
Title: Artificial Neural Network Forecasting
Description:
Zero defect as a goal for the manufacturing sector especially when the factory engage in global market which the market is required a highest grade quality product.
A defect will occur when it is fail to meet the intended design.
Hence, defect prediction methods play an important role to forecast the number of product defect.
For this study, Artificial Neural Network (ANN) used to forecast the product defect in furniture manufacturing in in order to develop a well suit ANN model for the product defect prediction and obtain an accurate prediction defect number for decision making.
Colour defect as one of the product defect category.
Therefore, data of colour defect was collected within eight (8) working hours for fourteen (14) days and the analysis process carried out by MATLAB R2015a application using the neural network toolbox.
The neural network framework for the colour defect prediction was developed with the minimum error.
The company is able to conduct prediction process with the framework and make a better decision based on the result in order to reach their goal.
   .

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