Stencil Printing Optimization using a Hybrid of Support Vector Regression and Mixed-integer Linear Programming

A Review of Data Mining with Big Data towards Its Applications in the Electronics Industry

“…The distribution of the selected articles in different years and different stages are illustrated in Figure 3. It can be seen that 17% (17 articles) were related to the stage of product and manufacturing process design [26][27][28][29][30][31][32][33][34][35][36][37][38][39][40][41][42], and more than 75% (80 articles) applied DM and Big Data to production management and control in the stage of production , but less than 8% (8 articles) of applications focused on the stage of sale, service, and recycling [123][124][125][126][127][128][129][130]. The fluctuation in quantity of the selected articles in different years presents no obvious tendency, however, it indicates that the topic has attracted ongoing attention and research during the past decades, and the application areas have been extended and many new approaches have been developed.…”

“…(2) The optimization of the manufacturing process parameter is the main task of process planning, such as the parameter optimization of stencil printing process (SPP) [26,27,36], reflow soldering [29,31,32], fluid dispensing for microchip encapsulation [33], wave soldering [35,41], and hot solder dip [39] for component surface mounts on PCBs. These models always combined ANN, SVR, and regression for the quality prediction with GA for parameters optimization [26,[31][32][33].…”

“…(3) KD-oriented ANN is the widely used DMT. The pervasive function is prediction and has been widely employed for parameter optimization and determination of its effect [26,27,[32][33][34][35][36] followed by clustering and association. Clustering was mainly employed to identify similarity products, process plans, and parameters and no supervision classification was conducted to support more efficient and reasonable manufacturing [39][40][41].…”

Data Mining for Material Feeding Optimization of Printed Circuit Board Template Production

“…Tsai et al developed three hybrid approaches including ANN-genetic algorithm (GA), fuzzy logic-Taguchi, and regression analysisresponse surface methodology (RSM) to predict the volume and centroid offset two responses and optimize parameters for the micro ball grid array (BGA) packages during the stencil printing process (SPP) for components assembly on PCB, and the confirmation experiments show that the proposed fuzzy logic-based Taguchi method outperforms the other two methods in terms of the signal-to-noise ratios and process capability index [12,13]. Some other approaches, like support vector regression (SVR) and mixed-integer linear programming, have also been developed for the parameter optimization of SPP [14]. Haneda et al [15] employed variable cluster analysis and -means approach to help engineers determine appropriate drilling condition and parameter for PCB manufacturing.…”

“…However, the quality related research for PCB manufacturing mainly focuses on one operation of the manufacturing process for the purpose of yield improvement [12][13][14][15], and there are few studies on material feeding optimization especially for PCB production using DM mechanism to the best of our knowledge. Meanwhile, the change structure of the studied problem and corresponding change of relevant features have seldom been considered during the mining procedure.…”