TY - GEN
T1 - Production quality early warning method for firearms components based on cloud edge collaboration
AU - Sun, Jiawei
AU - Hao, Jia
AU - Zhang, Xiaoning
N1 - Publisher Copyright:
© 2023 ACM.
PY - 2023/10/27
Y1 - 2023/10/27
N2 - Digital transformation in manufacturing has become a trend with the continuous development of cloud computing and edge computing. The production process of firearms components is highly challenging and quality problems in the production process may directly affect the safety of people's lives and property. Thus, this paper proposes a production-quality early warning method for firearms components based on cloud-edge collaboration. Real-time early warning and rapid processing for abnormal conditions in the production process are realized based on cloud data analysis and edge intelligent prediction, thereby improving production efficiency and quality. The cloud edge collaboration framework is developed for cloud training of the long short-term memory models and real-time sample edge acquisition, enhancing the adaptability of quality early warning algorithms under specific conditions and the real-time quality of early warning for firearms components.
AB - Digital transformation in manufacturing has become a trend with the continuous development of cloud computing and edge computing. The production process of firearms components is highly challenging and quality problems in the production process may directly affect the safety of people's lives and property. Thus, this paper proposes a production-quality early warning method for firearms components based on cloud-edge collaboration. Real-time early warning and rapid processing for abnormal conditions in the production process are realized based on cloud data analysis and edge intelligent prediction, thereby improving production efficiency and quality. The cloud edge collaboration framework is developed for cloud training of the long short-term memory models and real-time sample edge acquisition, enhancing the adaptability of quality early warning algorithms under specific conditions and the real-time quality of early warning for firearms components.
KW - Big data perception
KW - Cloud edge collaboration
KW - Long short-term memory
KW - Production quality early warning
UR - http://www.scopus.com/inward/record.url?scp=85191319829&partnerID=8YFLogxK
U2 - 10.1145/3650215.3650275
DO - 10.1145/3650215.3650275
M3 - Conference contribution
AN - SCOPUS:85191319829
T3 - ACM International Conference Proceeding Series
SP - 339
EP - 343
BT - Proceedings of the 2023 4th International Conference on Machine Learning and Computer Application, ICMLCA 2023
PB - Association for Computing Machinery
T2 - 4th International Conference on Machine Learning and Computer Application, ICMLCA 2023
Y2 - 27 October 2023 through 29 October 2023
ER -