摘要
在陶瓷制造业中,全流程工艺优化是提升产品质量和生产效率的关键。为了缓解陶瓷生产过程工艺反馈延时高、陶瓷整线工艺流程长等问题,研究了融合人工智能技术,构建一个覆盖整个陶瓷生产过程的工艺优化模型。该模型通过深度关联分析工艺参数与产品质量,优化了从原料制备到成品分选的关键环节,并提供了逆向推导出更为精确的过程检查和技术要求的方法。为有效提高生产效率和产品质量,降低生产成本,推动行业的技术创新和产业升级提供了新思路,为陶瓷产业的技术升级和转型提供了切实可行的新路径。研究内容涵盖了原料制备、压制成型、深加工、烧成等关键环节的智能化技术应用,以及陶瓷产品缺陷的自动检测与分类工具的开发。此外,项目构建了工艺参数与产品质量的关联模型,为生产过程的持续改进提供科学依据,从而实现陶瓷整线生产的精确控制和管理。
In the ceramic manufacturing industry,optimizing the entire process is key to improving product quality and production efficiency.The integration of artificial intelligence technology is studied to build a process optimization model that covers the entire ceramic production process.The model optimizes every step from raw material preparation to finished product sorting through in-depth correlation analysis between process parameters and product quality,and provides a method for deriving more precise process inspection and technical requirements.New ideas are offered for effectively improving production efficiency and product quality,reducing production costs,and promoting technological innovation and industrial upgrading in the industry,providing a feasible new path for the technological upgrading and transformation of the ceramic industry.The research covers the application of intelligent technology in key stages such as raw material preparation,pressing and shaping,deep processing,and sintering,as well as the development of automatic detection and classification tools for ceramic product defects.In addition,the project builds a correlation model between process parameters and product quality to provide a scientific basis for the continuous improvement of the production process,thus achieving precise control and management of the entire ceramic production line.
作者
杨学先
李庆民
林源升
Yang Xuexian;Li Qingmin;Lin Yuansheng(Keda Industrial Group Co.,Ltd.,Foshan,Guangdong 528000,China)
出处
《机电工程技术》
2024年第12期181-186,共6页
Mechanical & Electrical Engineering Technology
关键词
人工智能
工艺优化
陶瓷生产
过程检查
质量管理
artificial intelligence
process optimization
ceramic production
process inspection
quality management
