TY - JOUR
T1 - Fault propagation analysis of computer numerically controlled machine tools
AU - Huang, Shoujin
AU - Lu, Ningyun
AU - Jiang, Bin
AU - Simani, Silvio
AU - Li, Ronghua
AU - Huang, Binda
AU - Cao, Jie
N1 - Publisher Copyright:
© 2023 The Society of Manufacturing Engineers
PY - 2023/10
Y1 - 2023/10
N2 - Computer numerically controlled machine tools are the key equipment of the intelligent manufacturing industry, unscheduled shutdowns can substantially cause equipment damage and production loss. Fault propagation analysis, as a prominent basis of reducing unscheduled downtime, can locate the harmful parts and reveal the fault propagation path. To improve reliability, this paper proposes a novel fault propagation analysis method that can accurately and timely evaluate fault propagation coefficients of components in interior computer numerically controlled machine tools. To depict the latent cause–effect relationships of components, a quantitative causal diagram is built with the aid of design information and topology. An inverse PageRank algorithm is proposed to assess the fault propagation risks of components. Unlike the traditional PageRank algorithm, the idea of inverse PageRank is that a node is crucial if it directs to other important nodes. Subsequently, the fault propagation coefficients of components in the quantitative causal diagram are derived and the fault propagation path is identified. The proposed method is validated on the computer numerically controlled machine tool, and the results are basically consistent with the typical cascading events and conform to expert judgment.
AB - Computer numerically controlled machine tools are the key equipment of the intelligent manufacturing industry, unscheduled shutdowns can substantially cause equipment damage and production loss. Fault propagation analysis, as a prominent basis of reducing unscheduled downtime, can locate the harmful parts and reveal the fault propagation path. To improve reliability, this paper proposes a novel fault propagation analysis method that can accurately and timely evaluate fault propagation coefficients of components in interior computer numerically controlled machine tools. To depict the latent cause–effect relationships of components, a quantitative causal diagram is built with the aid of design information and topology. An inverse PageRank algorithm is proposed to assess the fault propagation risks of components. Unlike the traditional PageRank algorithm, the idea of inverse PageRank is that a node is crucial if it directs to other important nodes. Subsequently, the fault propagation coefficients of components in the quantitative causal diagram are derived and the fault propagation path is identified. The proposed method is validated on the computer numerically controlled machine tool, and the results are basically consistent with the typical cascading events and conform to expert judgment.
KW - Computer numerically controlled machine tools
KW - Fault propagation
KW - Inverse PageRank
KW - Propagation coefficient
KW - Quantitative causal diagram
UR - http://www.scopus.com/inward/record.url?scp=85166267730&partnerID=8YFLogxK
U2 - 10.1016/j.jmsy.2023.07.006
DO - 10.1016/j.jmsy.2023.07.006
M3 - Article
AN - SCOPUS:85166267730
SN - 0278-6125
VL - 70
SP - 149
EP - 159
JO - Journal of Manufacturing Systems
JF - Journal of Manufacturing Systems
ER -