TY - GEN
T1 - An application on building information model to procurement strategy of copper raw material with big data analytics
AU - Li, Sheng Tun
AU - Chiu, Kuei Chen
AU - Chiu, Tsung He
N1 - Funding Information:
This work was supported in part by the Ministry of Science and Technology, Taiwan, under Contracts MOST-107-2410-H-006-046 and MOST-108-2410-H-006-106-MY3. And thanks to the Center for Innovative FinTech Business Models, National Cheng Kung University, the Department of Industrial and Information Management, College of Management, National Cheng Kung University, Tainan, Taiwan, and the Department of Executive Master of Business Administration (EMBA), College of Management, National Cheng Kung University, Tainan, Taiwan for supporting this study accomplish.
Publisher Copyright:
© 2020 IEEE.
PY - 2020/12/14
Y1 - 2020/12/14
N2 - This research uses big data analysis to find the key factors of copper futures price fluctuations, successfully predicts copper price fluctuations, and applies them to the purchase strategy of copper raw materials for plant construction to help reduce plant construction costs. Since copper is an indispensable raw material in all building structures and pipeline configuration, the control of prices will help manufacturers from all walks of life to control the fluctuations in the price of copper raw materials and reduce the cost of building plants in the early stage of plant construction. Manufacturers "win at the starting point."
AB - This research uses big data analysis to find the key factors of copper futures price fluctuations, successfully predicts copper price fluctuations, and applies them to the purchase strategy of copper raw materials for plant construction to help reduce plant construction costs. Since copper is an indispensable raw material in all building structures and pipeline configuration, the control of prices will help manufacturers from all walks of life to control the fluctuations in the price of copper raw materials and reduce the cost of building plants in the early stage of plant construction. Manufacturers "win at the starting point."
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U2 - 10.1109/IEEM45057.2020.9309743
DO - 10.1109/IEEM45057.2020.9309743
M3 - Conference contribution
AN - SCOPUS:85099767364
T3 - IEEE International Conference on Industrial Engineering and Engineering Management
SP - 696
EP - 700
BT - 2020 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2020
PB - IEEE Computer Society
T2 - 2020 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2020
Y2 - 14 December 2020 through 17 December 2020
ER -