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.
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Rajagopalan Srinivasan received the B.Tech. degree from Indian Institute of Technology, Madras, India, in 1993 and the Ph.D. from Purdue University, West Lafayette, IN, USA, in 1998. He worked as a Research Associate at Honeywell Technology Center, Minneapolis, MN, USA, before moving to the National University of Singapore (NUS). He is currently an Associate Professor in the Department of Chemical and Biomolecular Engineering at NUS and concurrently a Senior Scientist at the Institute of Chemical and Engineering Sciences. His research interests include process supervision, supply chain management, and applied artificial intelligence.
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Srinivasan, R. Artificial intelligence methodologies for agile refining: an overview. Knowl Inf Syst 12, 129–145 (2007). https://doi.org/10.1007/s10115-006-0057-z
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DOI: https://doi.org/10.1007/s10115-006-0057-z