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首页> 外文期刊>International Journal of Production Research >Integrating grey sequencing with the genetic algorithm-immune algorithm to optimise touch panel cover glass polishing process parameter design
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Integrating grey sequencing with the genetic algorithm-immune algorithm to optimise touch panel cover glass polishing process parameter design

机译：将灰色排序与遗传算法-免疫算法相结合，以优化触摸屏盖板玻璃的抛光工艺参数设计

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摘要

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 (degrees 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/cm(3)), the central particle size of polishing powder is 1.4 (um) and the process capability C-pk is 1.75, which is better than the process capability of C-pk 1.41 of the response surface methodology and the process capability of C-pk 1.37 of the Taguchi experimental design.
机译：触摸屏盖板玻璃是决定触摸屏质量的重要部件之一。触摸屏盖板玻璃的质量要求强调了玻璃厚度的稳定性。由于该因素直接影响触摸屏的感应效果和触摸效果，因此盖板玻璃抛光工艺的参数条件具有重大影响。本研究将灰色排序与遗传算法-免疫算法相结合，以优化触摸屏盖板玻璃抛光工艺的参数设计。实验测量值是加工玻璃的厚度值，并讨论了加工后玻璃厚度的均匀性。影响加工条件的最佳加工组合如下：环境温度为22（摄氏度），加工压力为0.04（Mpa），加工时间为30（分钟），机器速度为70（rpm），抛光液的浓度为1.4（g / cm（3）），抛光粉的中心粒径为1.4（um），加工能力C-pk为1.75，优于C-pk 1.41的加工能力。田口实验设计的响应面方法学和C-pk 1.37的处理能力。

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