Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 7-Day Trial for You or Your Team.

Learn More →

Manufacturing intelligence and innovation for digital manufacturing and operational excellence

Manufacturing intelligence and innovation for digital manufacturing and operational excellence J Intell Manuf (2014) 25:845–847 DOI 10.1007/s10845-014-0896-5 Manufacturing intelligence and innovation for digital manufacturing and operational excellence Chen-Fu Chien · Mitsuo Gen · Yongjiang Shi · Chia-Yu Hsu Published online: 21 March 2014 © Springer Science+Business Media New York 2014 Global manufacturing networks and supply chains are facing algorithms to construct intelligent algorithms and solutions ongoing dynamic changes in the evolutionary business that can be embedded in various information systems for ecosystems. The introduction of new process technologies enterprise resources planning (ERP), advanced production and the advances in manufacturing intelligence capabilities system (APS), advanced process control and advanced equip- are having profound effects on the strategies, decisions, man- ment control (APC/AEC), manufacturing execution system agement, and operations involved in manufacturing (Chien (MES), engineering data analysis (EDA), and supply chain et al. 2007; Leachman et al. 2007). While big data is accu- management (SCM) to enhance decision quality and man- mulated due to the fully automation manufacturing facilities agement effectiveness (Chien et al. 2012; Chien et al. 2013b; and logistics systems for business integration, various solu- Wu et al. 2012a; Wu et al. 2012b). By seamless integration tions and techniques are developed to extract useful infor- of intelligence and decision http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Intelligent Manufacturing Springer Journals

Manufacturing intelligence and innovation for digital manufacturing and operational excellence

Download PDF
3 pages

Loading next page...
 
/lp/springer-journals/manufacturing-intelligence-and-innovation-for-digital-manufacturing-KCYuUjnxdK

References (16)

Publisher
Springer Journals
Copyright
Copyright © 2014 by Springer Science+Business Media New York
Subject
Economics / Management Science; Production/Logistics/Supply Chain; Manufacturing, Machines, Tools; Control, Robotics, Mechatronics
ISSN
0956-5515
eISSN
1572-8145
DOI
10.1007/s10845-014-0896-5
Publisher site
See Article on Publisher Site

Abstract

J Intell Manuf (2014) 25:845–847 DOI 10.1007/s10845-014-0896-5 Manufacturing intelligence and innovation for digital manufacturing and operational excellence Chen-Fu Chien · Mitsuo Gen · Yongjiang Shi · Chia-Yu Hsu Published online: 21 March 2014 © Springer Science+Business Media New York 2014 Global manufacturing networks and supply chains are facing algorithms to construct intelligent algorithms and solutions ongoing dynamic changes in the evolutionary business that can be embedded in various information systems for ecosystems. The introduction of new process technologies enterprise resources planning (ERP), advanced production and the advances in manufacturing intelligence capabilities system (APS), advanced process control and advanced equip- are having profound effects on the strategies, decisions, man- ment control (APC/AEC), manufacturing execution system agement, and operations involved in manufacturing (Chien (MES), engineering data analysis (EDA), and supply chain et al. 2007; Leachman et al. 2007). While big data is accu- management (SCM) to enhance decision quality and man- mulated due to the fully automation manufacturing facilities agement effectiveness (Chien et al. 2012; Chien et al. 2013b; and logistics systems for business integration, various solu- Wu et al. 2012a; Wu et al. 2012b). By seamless integration tions and techniques are developed to extract useful infor- of intelligence and decision

Journal

Journal of Intelligent Manufacturing – Springer Journals

Published: Mar 21, 2014

There are no references for this article.