摘要
发动机工厂在过程质量控制中践行数字工厂理念,通过采用数字化、智能化方法实现高效的质量管理。通过python等编程工具开发上位机软件实现数据获取的时效性,自主开发深度学习的视觉防错应用提升识别率,通过与现场实时通信获取各工序防错点状态实现生产线防错的系统化闭环管理;开发机床的数据采集系统,并在关键加工质量过程通过增加传感器方式实现机加工过程实时监控。生产线通过上述数字化、智能化技术应用有效提升了过程质量,实现了售后关键指标提升,保障了发动机工厂的制造质量。
Engine plant adopts digital quality concept during the in-process quality control and realizes the efficient quality management by digital and intelligent method.By using python and other programming tools,the development of the software is performed to meet the timing requirement of data acquisition,and the deep learning vision system to make error proofing is independently developed to increase the recognition rate,and capture each operation’s error proofing sensor status through the real-time communication with the site,so as to achieve the closed loop management of the production line for error prevention.And the machine’s data acquisition system is developed,the special sensor is added in the key processing quality process to monitor all the machine processes.The production line has effectively improved the process quality through the application of the above-mentioned digital and intelligent technologies,achieved the improvement of key after-sales indicators,and guaranteed the manufacturing quality of the engine factory.
作者
黄春笋
庹鹏
Huang Chun-sun;Tuo Peng(SAIC GM Wuling Automobile Co.,Ltd.Chongqing 401135,China)
出处
《科学与信息化》
2022年第14期84-87,共4页
Technology and Information
关键词
质量追溯系统
数据实时性
深度学习的视觉开发
防错系统应用
实时监控
quality traceability system
real-time data
visual development of deep learning
application of error-proofing system
real-time monitoring
