Please use this identifier to cite or link to this item:
|Title:||Artificial intelligence methodologies for agile refining: An overview|
Supply chain management
|Citation:||Srinivasan, R. (2007-07). Artificial intelligence methodologies for agile refining: An overview. Knowledge and Information Systems 12 (2) : 129-145. ScholarBank@NUS Repository. https://doi.org/10.1007/s10115-006-0057-z|
|Abstract:||Agile manufacturing is the capability to prosper in a competitive environment of continuous and unpredictable changes by reacting quickly and effectively to the changing markets and other exogenous factors. Agility of petroleum refineries is determined by two factors - ability to control the process and ability to efficiently manage the supply chain. In this paper, we outline some challenges faced by refineries that seek to be lean, nimble, and proactive. These problems, which arise in supply chain management and operations management are seldom amenable to traditional, monolithic solutions. As discussed here using several examples, methodologies drawn from artificial intelligence - software agents, pattern recognition, expert systems - have a role to play in this path toward agility. © Springer-Verlag London Limited 2007.|
|Source Title:||Knowledge and Information Systems|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Sep 17, 2018
WEB OF SCIENCETM
checked on Aug 29, 2018
checked on Sep 14, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.