遗传算法在凹版印刷质量优化中的应用研究  

Application of Genetic Algorithms in Quality Optimization of Gravure Printing

作　　者：刘民望 LIU Minwang(Shaanxi Beiren Printing Machinery Co.Ltd.,Weinan 714000,China)

机构地区：[1]陕西北人印刷机械有限责任公司,渭南714000

出　　处：《北京印刷学院学报》2024年第12期8-16,共9页Journal of Beijing Institute of Graphic Communication

摘　　要：随着印刷行业对高质量产品需求的不断增长,传统的印刷过程优化方法已无法满足快速变化的市场需求。凹版印刷作为广泛使用的一种印刷技术,其质量控制至关重要。本研究采用遗传算法(GA),一种有效的全局搜索和优化技术,针对凹版印刷过程中的质量优化问题进行探究。通过设计适应度函数来评价印刷质量,并利用遗传算法的迭代进化过程寻找最优参数组合,以达到提升印刷品质的目的。实验结果表明,该算法能显著提高凹版印刷的色彩一致性、分辨率和对比度等关键质量指标,同时减少了对专业人员经验的依赖。此外,算法生成的大量数据可用于进一步的数据分析和机器学习,为预测和预防潜在的生产问题提供支持。本研究不仅证明了遗传算法在凹版印刷质量优化中的有效性,而且展示了其在现代工业生产中的潜在应用前景。With the continuous growth in demand for high-quality products in the printing industry,traditional methods of printing process optimization are no longer able to meet rapidly changing market demands.Gravure printing,as a widely used printing technology,requires crucial quality control.This study employs genetic algorithms(GA),an effective global search and optimization technique,to explore quality optimization issues in the gravure printing process.By designing fitness functions to evaluate printing quality,and utilizing the iterative evolutionary process of genetic algorithms to find the optimal parameter combinations,the aim is to enhance printing quality.Experimental results show that the algorithm significantly improves key quality indicators such as color consistency,resolution,and contrast in gravure printing,while reducing reliance on professional experience.Additionally,the extensive data generated by the algorithm can be used for further data analysis and machine learning,providing support for predicting and preventing potential production issues.This study not only proves the effectiveness of genetic algorithms in optimizing gravure printing quality but also demonstrates their potential application prospects in modern industrial production.

关 键 词：遗传算法 凹版印刷 质量优化 适应度函数 工业应用 

分 类 号：TM923[电气工程—电力电子与电力传动]