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8 March 1999 Industrial web inspection for manufacturing process understanding and control
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Abstract
Many industrial manufacturing processes are not well understood and are treated as `black art' with few experts able to control the process and ensure product quality. However, modern manufacturing companies are finding it increasingly difficult to compete in the global marketplace without better process understanding and control. Automated inspection systems for general manufacturing have become more feasible through technical advances, primarily in sensor and computing technology. However, these systems have been used almost exclusively for the detection and subsequent removal of well defined, discrete defects from the product; thus guaranteeing high quality for the customer. This paper describes a larger opportunity to affect operations by employing web inspection techniques to dynamically analyze manufacturing conditions rather than just detecting the presence of defective material. One can then keep the process under better control, thereby eliminating defects, ensuring product quality, and optimizing manufacturing time on the production line. Specific image and data processing techniques will be illustrated including product uniformity metrics, automatic determination of thresholds for blob analysis, and localization of repeating defects within production data. The benefit of these techniques will be demonstrated through `real-world' examples of web-based manufactured products.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Wenyuan Xu and Steven P. Floeder "Industrial web inspection for manufacturing process understanding and control", Proc. SPIE 3652, Machine Vision Applications in Industrial Inspection VII, (8 March 1999); https://doi.org/10.1117/12.341143
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