AOI based Neurofuzzy System to Evaluate Solder Joint Quality

Surface Mount Technology is extensively used in the production of Printed Circuit Boards due to the high level of density in the electronic device integration. In such production process several defects could occur on the final electronic components, compromising their correct working. In this paper a neurofuzzy solution to process information deriving from an automatic optical system is proposed. The designed solution provides a Quality Index of a solder joint, by reproducing the modus operandi of an expert and making it automatic. Moreover, the considered solution presents some attractive advantages: a complex acquisition system is not needed, reducing the equipment costs and shifting the assessment of a solder joint on the fuzzy parts. Finally, the typical low computational costs of the fuzzy systems could satisfy urgent time constrains in the in-line detection of some industrial productive processes.