Automated Refinement of Automated Visual Inspection Algorithms

One of the challenges faced by the users of automated visual inspection (AVI) systems is how to efficiently upgrade the legacy systems to inspect the new components introduced into the assembly lines. If the AVI systems are not flexible enough to accommodate new components, they will be rendered obsolete even by small changes in the product being inspected. The overall objective of the research presented in this paper is to produce the methodological basis that will result in the development of highly reconfigurable AVI systems. In this paper, we focus on part of this overall development, the adaptation of preexisting inspection algorithms to inspect similar components introduced into the assembly line. While this paper bases its development and discussion on the inspection of surface mounted devices (SMDs), the proposed methodology is general enough to be applicable to a broad range of inspection problems. In this paper, we present a methodology that would allow the automation of the refinement of AVI algorithms. In particular, the proposed method identifies a set of components, or cluster of components, for which a particular set of inspection features or algorithms, renders a certain level of inspection reliability. This is particularly useful for adapting preexisting systems to inspect new components, especially when the characteristics of the new components are similar to those of components already inspected by the inspection system. We applied this methodology to a case of study of the inspection of SMDs.