TY - GEN
T1 - Research on Fuzzy Rule-Based Reasoning System for CC Quality Assurance
AU - Lei, Zhufeng
AU - Su, Wenbin
AU - Liu, Yu
AU - Gao, Qi
AU - Yang, Ladao
AU - Hu, Qiao
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - High-quality slab Continuous Casting (CC) production technology is one of the most competitive core technologies in the steel industry. How to inherit and apply the experience of CC expert has become an urgent problem in the quality assurance of CC. First, analyze the demand of the entire CC quality assurance system, carry out the system-based overall design and functional module decomposition design, design the system's workflow. Next, according to the characteristics of different types of knowledge in the field of CC, the representation form of design knowledge, construct the knowledge base of CC field, design the rule reasoning control process in detail according to the functional requirements of the rule inference system, and manage the knowledge base of CC field. Then it designed with maintenance. Finally, the human-computer interaction interface of the system is designed to complete the development of the system, and the detailed function test and analysis of the system's implementation effect are carried out. The system application results show that the system can well represent different types of CC quality assurance knowledge and apply it to systematic reasoning, which can solve the common quality fluctuation problems in CC production process and meet the application requirements. It improves the level of intelligent production of CC, and has certain promotion and reference value for the field of intelligent manufacturing.
AB - High-quality slab Continuous Casting (CC) production technology is one of the most competitive core technologies in the steel industry. How to inherit and apply the experience of CC expert has become an urgent problem in the quality assurance of CC. First, analyze the demand of the entire CC quality assurance system, carry out the system-based overall design and functional module decomposition design, design the system's workflow. Next, according to the characteristics of different types of knowledge in the field of CC, the representation form of design knowledge, construct the knowledge base of CC field, design the rule reasoning control process in detail according to the functional requirements of the rule inference system, and manage the knowledge base of CC field. Then it designed with maintenance. Finally, the human-computer interaction interface of the system is designed to complete the development of the system, and the detailed function test and analysis of the system's implementation effect are carried out. The system application results show that the system can well represent different types of CC quality assurance knowledge and apply it to systematic reasoning, which can solve the common quality fluctuation problems in CC production process and meet the application requirements. It improves the level of intelligent production of CC, and has certain promotion and reference value for the field of intelligent manufacturing.
KW - CC quality
KW - Expert experience
KW - Fuzzy Rule-Based Reasoning
KW - Process parameter adjustment
UR - https://www.scopus.com/pages/publications/85064129830
U2 - 10.1109/ROBIO.2018.8665221
DO - 10.1109/ROBIO.2018.8665221
M3 - 会议稿件
AN - SCOPUS:85064129830
T3 - 2018 IEEE International Conference on Robotics and Biomimetics, ROBIO 2018
SP - 1900
EP - 1908
BT - 2018 IEEE International Conference on Robotics and Biomimetics, ROBIO 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE International Conference on Robotics and Biomimetics, ROBIO 2018
Y2 - 12 December 2018 through 15 December 2018
ER -