Enhancing Automated Defect Detection in Collagen Based Manufacturing by Employing a Smart Machine Vision Technique

摘要

Machine vision is now being extensively used for defect detection in the manufacturing process of collagen-based products such as sausage skins. At present the industry standard is to use a Lab View software environment to manage and detect any defects in the collagen skins. Available data corroborates that this method allows for false positives to appear in the results which is responsible for reducing the overall system performance and resulting wastage of resources. Hence novel criteria were added to enhance the current techniques. The proposed improvements aim to achieve a higher accuracy and flexibility in detecting both true and false positives by utilizing a function that probes for the color deviation and fluctuation in the collagen skins. After implementation of the method in a well-known Australian company, investigational results demonstrate an average 26 % increase in the ability to detect false positives with a corresponding substantial reduction in operating cost.