Monitoring pasta production line using automated imaging technique

AbstractIn food mass production visual inspection does not match the high standards exhibited in food technology, not to mention the economic costs and drawback from the human factor involved which mainly burdens quality assurance. In focus, quality control, on a daily basis, is just performed on selected samples which are thought to indicate the whole production trend. Therefore an automated solution should be used, which offers an inline monitoring protocol joined with more statistical measurement evaluation. Pasta is considered one of the typical food around the world, production quality of pasta have always been of concern to producers. Pasta, in order to meet the criteria and expectations of consumers, must avoid the production defects like crumbling during packaging, in-homogeneousness, unevenness in size, cracks due to extra dehydration, additionally must not be glutinous on the surface (stick together). Process analytical technology is a time saver, precise and economic solution which the industry can rely on. In this work a pasta production line monitoring is developed conceding to PAT basis (process analytical technology); using an industrial camera controlled by microcontroller, and a developed combinatorial algorithm using image processing techniques. Glutinous is easily detected by intelligent edge detection algorithm and pasta in-homogeneousness defect is evaluated by automated surface roughness evaluation