3D超薄曲面玻璃热弯工艺优化及分析

Performance Analysis of Hot Bending Process for Ultra-thin Glass of Mobile Phone

曲面屏手机因其使用舒适性好、屏幕面积利用率高,在智能手机市场的需求正在稳步增长。高精度超薄玻璃热弯工艺是曲面屏手机的生产线上非常重要的工序之一,然而玻璃热弯过程由于能耗高、合格率低,不符合环保理念。鉴于此,对超薄玻璃热弯工艺性能进行了全面分析。介绍了超薄玻璃热弯工艺,对玻璃热弯装置结构进行了描述,并阐述了玻璃热弯工艺原理及工艺参数。基于一系列玻璃热弯实验,揭示了热弯工艺参数对能量消耗和合格率的影响。基于实验数据,采用BP神经网络的遗传-量子粒子群复合算法进行建模,确定最优工艺参数,并验证其可靠性。研究结果有助于高精度超薄玻璃热弯工艺的高效运作,提高产品合格率和生产效率,同时实现绿色可持续制造。

Curved screen mobile phones are steadily increasing in demand in the smartphone market due to their good comfort and high screen area utilization.The high-precision ultra-thin glass hot bending process is one of the very important processes on the production line of curved screen mobile phones.However,due to the high energy consumption and low pass rate,the glass hot bending process does not meet the environmental protection concept.In view of the problems,a comprehensive analysis of the performance of ultra-thin glass hot bending process was made.The ultra-thin glass hot bending process was introduced,including the description of the glass hot bending device,the principle of the glass hot bending process and process parameters.Based on a series of glass hot bending experiments,the influence of hot bending process parameters on energy consumption and pass rate was revealed.Based on the experimental data,the genetic-quantum particle swarm composite algorithm of BP neural network was used to model and determine the optimal process parameters,and its reliability was verified.Therefore,the research contributes to the efficient operation of the high-precision ultra-thin glass hot bending process,improves the pass rate and productivity and achieves green and sustainable manufacturing.