An Analysis of Redundancy in High Volume High Mix Quality Testing Systems in Electronics Production

摘要

Due to increasing demand regarding quality, quantity, and individualization of electronic products, requirements for automated quality testing systems in electronics production came to include the need for greater flexibility and speed. Sophisticated contemporary production lines of electronic assemblies can include automated solder paste, optical and X-ray inspection as well as in-circuit tests. With the ultimate goal of evaluating 100 % of solder joints of any given board, redundancy can occur regarding overlapping testing content. Whereas contemporary approaches to more efficient testing of electronic assemblies focus on the reduction of false calls using machine learning (ML), this paper analyzes the degree of redundancy between automated optical inspection (AOI) and X-ray inspection (AXI). We further explore possibilities for reducing the scope of testing to a necessary minimum, while still achieving full coverage of any given board. As communication of such analysis is of great importance in large-scale production facilities, a method of visualization is devised to utilize initial findings before a holistic approach can be implemented. Additionally, the transferability of PCB-level testing plans between product lines using machine-learning models is evaluated as a method of including implicit knowledge for new products.