Automatic Visual Inspection Machine for Pharmaceutical Infusion Bags Implementing Cellular Neural Networks

Abstract

Automation procedures and machines in the pharmaceutical field are required to implement a series of methodologies, designed parting from international standards, in order to ensure the high quality of the products. Regarding infusion bags, the standards require to thoroughly assess the conformity of the product before being used in patients. The inspection procedures are usually operator-based and therefore subject to human factor errors. A novel inspection machine has been designed and developed with the use of a specifically designed cellular neural network (CNN) coupled with an off-the-shelf neural network trainable solution. The novel machine, thanks to the computational versatility of the CNN, is capable of reaching high standards of assessment drastically decreasing the risk of operator-based errors in the procedure.