Design and planning petroleum supply chain

SAAD, Sameh, ELSAGHIER, Elganidi H. and EZAGA, David (2017). Design and planning petroleum supply chain. In: GAO, James, EL SOURI, Mohammed and KEATES, Simeon, (eds.) Advances in Manufacturing Technology. XXXI : Proceedings of the 15th International Conference on Manufacturing Research, Incorporating the 32nd National Conference on Manufacturing Research, September 5–7, 2017, University of Greenwich, UK. Advances in Transdisciplinary Engineering (6). Amsterdam, IOS Press, 351-356.

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Official URL: http://ebooks.iospress.nl/volumearticle/47054
Link to published version:: https://doi.org/10.3233/978-1-61499-792-4-351
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    Abstract

    In recent years, the petroleum industry has grown increasingly complex as a result of tighter competition, stricter environmental regulations and lower profit margins. These factors and others forced petroleum companies for a greater need in strategic planning and optimisation in order to make decisions that satisfy conflicting multi-objective situation, goals of maximising expected profit while simultaneously minimising risk. The main purpose of this paper is the design and development of a simulation model for a petroleum supply chain to be used as a planning and decision making tool while considering factors such as oil flow rate, quality of crude oil, distillation time and separators failure rate. The simulation model is then designed and implemented to measure the performance of the petroleum supply chain proposed. ARENA software is used to build the proposed models and the results of experiments are analysed using SPSS software.

    Item Type: Book Section
    Additional Information: Paper originally presented at the 15th International Conference on Manufacturing Research, ICMR 2017, University of Greenwch, London. 5-7th September 2017. Book series Print ISSN: 2352-751X ; online ISSN: 2352-7528
    Research Institute, Centre or Group - Does NOT include content added after October 2018: Materials and Engineering Research Institute > Centre for Automation and Robotics Research > Mobile Machine and Vision Laboratory
    Identification Number: https://doi.org/10.3233/978-1-61499-792-4-351
    Page Range: 351-356
    Depositing User: Carmel House
    Date Deposited: 29 Jan 2018 13:06
    Last Modified: 29 Jan 2018 13:06
    URI: http://shura.shu.ac.uk/id/eprint/16725

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