Artificial Neural Intelligent Visual Inspection for Process Improvement
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Abstract
In Industrial manufacturing, product inspection is an important step in the production process. Since product reliability is most important in mass production facilities. Visual inspection seeks to identify both functional and cosmetic defects. The visual inspection in most manufacturing process depends mainly on human operators whose performance is generally inadequate and Variable. Advances in technology have resulted in better, cheaper image analysis equipment, which enable the use of affordable automated visual inspection system. The major advantages of automatic operation are speed and diagnostic capabilities. A Neural Network is a powerful datamodeling tool that is able to capture and represent Complex input/output relationships. The objective of this paper is to enhance on modeling, integrating, and implementation of neural network technique in the bottle manufacturing industry for quality control.