TY - GEN
T1 - Predictive maintenance of water purification unit for smart factories
AU - Chang, Tsung Yuan
AU - Cho, Wei-Ting
AU - Tseng, Shau Yin
AU - Ouyang, Yeni
AU - Lai, Chin Feng
PY - 2020
Y1 - 2020
N2 - In recent years, the applications of the smart factory are very popular. Predictive maintenance is one of the issues. Some research achieved the goal of predictive maintenance with Artificial Intelligence (AI). Here we focus on the local scrubber (LSR) system, a water purification and recycling system. This paper proposed a machine learning model to solve predictive maintenance problem. The device learns the pattern of input data through the RNN model and classify the different state of device. We can know the current situation of the device and judge whether it is about to be replaced. As far as we know, this is the first predictive task maintenance in the LSR system and has an accuracy of 84% in the datasets of different years. The smart factory will come true while the LSR system can be reduce cost, manpower, time and money with predictive maintenance.
AB - In recent years, the applications of the smart factory are very popular. Predictive maintenance is one of the issues. Some research achieved the goal of predictive maintenance with Artificial Intelligence (AI). Here we focus on the local scrubber (LSR) system, a water purification and recycling system. This paper proposed a machine learning model to solve predictive maintenance problem. The device learns the pattern of input data through the RNN model and classify the different state of device. We can know the current situation of the device and judge whether it is about to be replaced. As far as we know, this is the first predictive task maintenance in the LSR system and has an accuracy of 84% in the datasets of different years. The smart factory will come true while the LSR system can be reduce cost, manpower, time and money with predictive maintenance.
UR - http://www.scopus.com/inward/record.url?scp=85087279675&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85087279675&partnerID=8YFLogxK
U2 - 10.1007/978-981-15-6113-9_8
DO - 10.1007/978-981-15-6113-9_8
M3 - Conference contribution
AN - SCOPUS:85087279675
SN - 9789811561122
T3 - Communications in Computer and Information Science
SP - 62
EP - 70
BT - Cognitive Cities - 2nd International Conference, IC3 2019, Revised Selected Papers
A2 - Shen, Jian
A2 - Chang, Yao-Chung
A2 - Su, Yu-Sheng
A2 - Ogata, Hiroaki
PB - Springer
T2 - 2nd International Cognitive Cities Conference, IC3 2019
Y2 - 3 September 2019 through 6 September 2019
ER -