Integrating grey sequencing with the genetic algorithm–immune algorithm to optimise touch panel cover glass polishing process parameter design
研究将灰色排序与遗传算法-免疫算法结合，优化触摸屏盖板玻璃抛光工艺参数，使玻璃厚度均匀性提升，工艺能力Cpk达1.75，优于响应面法和田口实验设计。
The touch panel cover glass is one of the important parts and components that determine touch panel quality. The quality requirement of touch panel cover glass emphasises the stability of glass thickness. As this factor directly influences the induction effect and touch of the touch panel, the parameter conditions for the cover glass polishing process have significant impact. This study integrated grey sequencing with the Genetic algorithm–Immune algorithm to optimise the parameter design for the touch panel cover glass polishing process. The experimental measurement value was the thickness value of the processed glass, and the uniformity of glass thickness after processing was discussed. The optimum processing combination influencing the process conditions is as follows: the ambient temperature is 22 (°C), the processing pressure is 0.04 (Mpa), the processing time is 30 (min), the machine speed is 70 (rpm), the polishing solution concentration is 1.4 (g/cm3), the central particle size of polishing powder is 1.4 (um) and the process capability Cpk is 1.75, which is better than the process capability of Cpk 1.41 of the response surface methodology and the process capability of Cpk 1.37 of the Taguchi experimental design.