Image Based Quality Control of Free-form Profiles in Automatic Cutting Processes

In manufacturing, Machine Vision Systems are increasingly being used for their ability to collect information pertaining to the quality of a product in real time. When physical profiles are collected from images captured by Machine Vision Systems, the number and locations of the observed points can change from one item to another. The research is focused on non-parametric control charts for statistical monitoring of free-form profiles with different number and locations of observed points. The proposed method consists in extracting the shape of the monitored profile from images and in comparing it to a baseline model taken as reference. A new discrepancy metric, which consists in computing the deviation area of the monitored profile from the baseline model, is proposed. Two control charting procedures, based on univariate and a multivariate statistics are illustrated and validated through computer simulations. The automatic cutting process in leather part manufacturing (e.g. furniture, automotive interior, apparel) is the reference context.