TY - GEN
T1 - Applying BPN and EWMA SPC chart to cold chain temperature monitoring
AU - Chen, Kai Ying
AU - Shaw, Yi Cheng
AU - Chen, Mu-Chen
AU - Wu, Teh Chang
PY - 2009
Y1 - 2009
N2 - Recently, with the development of urbanization, the enhancement efficiency of contactless, real-time features and high data transmission rate in supply chain management are widely discussed. The cold chain is one part of the supply chain, and especially the temperature monitoring plays a vital role in cold chain system. In this paper, we apply EWMA control chart and artificial neural network technologies to monitor temperature data. The back-propagation neural network is used to predict temperature shifts and trend. EWMA control chart is adopted to monitor temperature variation. As there're something wrong happened, the control center of an enterprise can do some actions immediately to prevent further disaster. Finally, we construct a system with back-propagation neural network and statistical process control chart. A simulations and demonstrations environment using LEGO® bricks is also implemented.
AB - Recently, with the development of urbanization, the enhancement efficiency of contactless, real-time features and high data transmission rate in supply chain management are widely discussed. The cold chain is one part of the supply chain, and especially the temperature monitoring plays a vital role in cold chain system. In this paper, we apply EWMA control chart and artificial neural network technologies to monitor temperature data. The back-propagation neural network is used to predict temperature shifts and trend. EWMA control chart is adopted to monitor temperature variation. As there're something wrong happened, the control center of an enterprise can do some actions immediately to prevent further disaster. Finally, we construct a system with back-propagation neural network and statistical process control chart. A simulations and demonstrations environment using LEGO® bricks is also implemented.
KW - Back propagation network
KW - LEGO®NXT
KW - Radio frequency identification
KW - Statistical process control
KW - Temperature monitoring
UR - http://www.scopus.com/inward/record.url?scp=77953192172&partnerID=8YFLogxK
U2 - 10.1115/MSEC2009-84209
DO - 10.1115/MSEC2009-84209
M3 - Conference contribution
AN - SCOPUS:77953192172
SN - 9780791843611
T3 - Proceedings of the ASME International Manufacturing Science and Engineering Conference 2009, MSEC2009
SP - 247
EP - 256
BT - Proceedings of the ASME International Manufacturing Science and Engineering Conference 2009, MSEC2009
T2 - ASME International Manufacturing Science and Engineering Conference 2009, MSEC2009
Y2 - 4 October 2009 through 7 October 2009
ER -