TY - GEN
T1 - Real-time Production Performance Analysis Using Machine Degradation Signals
T2 - 14th IEEE International Conference on Automation Science and Engineering, CASE 2018
AU - Kang, Yunyi
AU - Yan, Hao
AU - Ju, Feng
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/12/4
Y1 - 2018/12/4
N2 - Ahstract- Machine degradation has significant impact on the production system performance. Its variation might lead to large deviation from the steady state performance of the whole system. In this work, we build up a model to estimate the long-term production performance of the two-machine-and-one-buffer production systems, given the real-time machine degradation signals. A phase-type distribution is generated to mimic the remaining life distribution of each machine given the degradation signal. Then a continuous Markovian model is formulated to predict longterm system throughput rate for a two-machine-and-one-buffer system. With the fluctuation of machine degradation signals, such a model can effectively estimate the expected system performance in real-time.
AB - Ahstract- Machine degradation has significant impact on the production system performance. Its variation might lead to large deviation from the steady state performance of the whole system. In this work, we build up a model to estimate the long-term production performance of the two-machine-and-one-buffer production systems, given the real-time machine degradation signals. A phase-type distribution is generated to mimic the remaining life distribution of each machine given the degradation signal. Then a continuous Markovian model is formulated to predict longterm system throughput rate for a two-machine-and-one-buffer system. With the fluctuation of machine degradation signals, such a model can effectively estimate the expected system performance in real-time.
UR - http://www.scopus.com/inward/record.url?scp=85059972959&partnerID=8YFLogxK
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U2 - 10.1109/COASE.2018.8560385
DO - 10.1109/COASE.2018.8560385
M3 - Conference contribution
AN - SCOPUS:85059972959
T3 - IEEE International Conference on Automation Science and Engineering
SP - 1501
EP - 1506
BT - 2018 IEEE 14th International Conference on Automation Science and Engineering, CASE 2018
PB - IEEE Computer Society
Y2 - 20 August 2018 through 24 August 2018
ER -