Article ID: | iaor20112204 |
Volume: | 41 |
Issue: | 1 |
Start Page Number: | 79 |
End Page Number: | 92 |
Publication Date: | Jan 2011 |
Journal: | Interfaces |
Authors: | Meyer Marlize, Robinson Hylton, Fisher Michele, van der Merwe Anette, Streicher Gerrit, van Rensburg Johan Janse, van den Berg Hentie, Dreyer Esmi, Joubert Jaco, Bonthuys Gerkotze, Rossouw Ruan, Louw Willem, van Deventer Lorraine, Wykes Cecile, Cawood Ebert |
Keywords: | petroleum, simulation: applications, artificial intelligence: decision support |
Sasol, an integrated energy and chemicals company based in South Africa, leads the world in producing liquid fuels from natural gas and coal. Sasol faces many challenges, such as stricter fuel specifications, fluctuating oil and gas prices, and unique developing‐world issues. Historically, the petrochemical industry based business decisions on average production limits. Sasol critically needed a better method to understand and include the effect of variability and dynamics in its decisions. The company's modeling operations using stochastic simulation (MOSS) methodology is an application of operations research that has helped to radically improve decision making. Sasol used this methodology to build three discrete‐event simulation models spanning its unique coal‐to‐liquids value chain. The models have repeatedly proven their value by enhancing insights, enabling collaboration, ensuring efficient and effective production, and improving Sasol's bottom line. This work has applications in the wider chemical and fuels industries and represents a major step forward for operations research and chemical engineering.