Electronic Component Parameter Recognition by a Nonparametric Approach with an Assignment Algorithm

This study presents an automatic system to identify essential design parameters from observed features when drawing plans for electronic circuit board footprints. The system helps to reduce the error rate of manual recognition and enhances identification accuracy, thereby improving the efficiency of producing high-quality footprints and contributing to the production of superior consumer electronics. A nonparametric approach is proposed to define a score matrix for evaluating the relationships between the observed qualitative/quantitative features and the essential design parameters in a robust manner. The best matching result for the observed features and essential design parameters is obtained using an assignment algorithm with the proposed score matrix. A user-friendly sufficient condition is introduced to ensure the correct assignment produced by the proposed method. In addition, a consistent estimator of this sufficient condition is developed to facilitate practical implementation. Numerical results from the simulation study highlight the importance of this condition, demonstrating that distinct observed features can provide complementary information for accurate recognition. In the empirical study, we apply the proposed method to 15 electronic component packages and achieve satisfactory correct assignment percentages in identifying essential design parameters.