TY - GEN
T1 - Health estimation method of manufacturing systems based on multidimensional state prediction
AU - Gu, Changchao
AU - He, Yihai
AU - Han, Xiao
AU - Chen, Zhaoxiang
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/9/8
Y1 - 2017/9/8
N2 - Systematic and accurate health estimation for the running manufacturing system is the prerequisite to implement production scheduling and predictive maintenance. This enables remedial actions to be taken in advance and reschedule of production if necessary. However, existing studies pay more attention to the failure diagnosis of equipment, while ignoring the output and input characteristics of the manufacturing system. Therefore, this paper presents a novel method for health estimation of manufacturing systems from three dimensions of equipment performance, product quality and task execution Firstly, the equipment performance state is represented based on the theory of polymorphism. Secondly, the quality state is defined to describe the qualified degree of the output products according to the response model. Thirdly, a task execution state modeling method is proposed, and the correlation between sub-Task execution states is considered based on Copula function. Then, an integrated model is built to prognosis the change trend of manufacturing system health by integrating the above three states. Finally, a case study conducted to illustrate the effectiveness of the proposed method.
AB - Systematic and accurate health estimation for the running manufacturing system is the prerequisite to implement production scheduling and predictive maintenance. This enables remedial actions to be taken in advance and reschedule of production if necessary. However, existing studies pay more attention to the failure diagnosis of equipment, while ignoring the output and input characteristics of the manufacturing system. Therefore, this paper presents a novel method for health estimation of manufacturing systems from three dimensions of equipment performance, product quality and task execution Firstly, the equipment performance state is represented based on the theory of polymorphism. Secondly, the quality state is defined to describe the qualified degree of the output products according to the response model. Thirdly, a task execution state modeling method is proposed, and the correlation between sub-Task execution states is considered based on Copula function. Then, an integrated model is built to prognosis the change trend of manufacturing system health by integrating the above three states. Finally, a case study conducted to illustrate the effectiveness of the proposed method.
KW - equipment performance
KW - health estimation
KW - manufacturing system
KW - product quality
KW - state prediction
KW - sub-Task execution
UR - https://www.scopus.com/pages/publications/85032306004
U2 - 10.1109/ICRSE.2017.8030726
DO - 10.1109/ICRSE.2017.8030726
M3 - 会议稿件
AN - SCOPUS:85032306004
T3 - 2017 2nd International Conference on Reliability Systems Engineering, ICRSE 2017
BT - 2017 2nd International Conference on Reliability Systems Engineering, ICRSE 2017
A2 - Fan, Dongming
A2 - Yang, Jun
A2 - Wang, Ziyao
A2 - Zhao, Tingdi
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2nd International Conference on Reliability Systems Engineering, ICRSE 2017
Y2 - 10 July 2017 through 12 July 2017
ER -