IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v269y2018i1p227-243.html
   My bibliography  Save this article

Water-integrated scheduling of batch process plants: Modelling approach and application in technology selection

Author

Listed:
  • Pulluru, Sai Jishna
  • Akkerman, Renzo

Abstract

Efficient water management is becoming increasingly important in production systems, but companies often do not have any concrete strategies to implement. While there are numerous technological options for improving water efficiency in process plants, there is a lack of effective decision support to integrate water aspects in operational decision making. This paper is based on the premise that inclusion of water reuse and related technological decisions during scheduling of production operations is essential for reduction of industrial water consumption. We develop a water-integrated scheduling approach based on mathematical programming to capture the main characteristics of water flows in batch process plants. We model water quality with a practical and generic classification scheme to effectively include water reuse and treatment possibilities. The approach is able to quantify tradeoffs between production efficiency and water efficiency. We also illustrate the use of our approach in the evaluation of water reuse and regeneration technologies for typical process industry settings. Overall, our approach is able to integrate water reuse and regeneration in a relatively efficient manner, and can help reduce industrial water consumption in process industries.

Suggested Citation

  • Pulluru, Sai Jishna & Akkerman, Renzo, 2018. "Water-integrated scheduling of batch process plants: Modelling approach and application in technology selection," European Journal of Operational Research, Elsevier, vol. 269(1), pages 227-243.
  • Handle: RePEc:eee:ejores:v:269:y:2018:i:1:p:227-243
    DOI: 10.1016/j.ejor.2017.07.009
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221717306367
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ejor.2017.07.009?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Stefansson, Hlynur & Sigmarsdottir, Sigrun & Jensson, Pall & Shah, Nilay, 2011. "Discrete and continuous time representations and mathematical models for large production scheduling problems: A case study from the pharmaceutical industry," European Journal of Operational Research, Elsevier, vol. 215(2), pages 383-392, December.
    2. Christodoulos Floudas & Xiaoxia Lin, 2005. "Mixed Integer Linear Programming in Process Scheduling: Modeling, Algorithms, and Applications," Annals of Operations Research, Springer, vol. 139(1), pages 131-162, October.
    3. Julien, Benoit, 1994. "Water quality management with imprecise information," European Journal of Operational Research, Elsevier, vol. 76(1), pages 15-27, July.
    4. Sadiq, Rehan & Tesfamariam, Solomon, 2007. "Probability density functions based weights for ordered weighted averaging (OWA) operators: An example of water quality indices," European Journal of Operational Research, Elsevier, vol. 182(3), pages 1350-1368, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. M Tavana & M A Sodenkamp, 2010. "A fuzzy multi-criteria decision analysis model for advanced technology assessment at Kennedy Space Center," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(10), pages 1459-1470, October.
    2. Farahmand, H. & Doorman, G.L., 2012. "Balancing market integration in the Northern European continent," Applied Energy, Elsevier, vol. 96(C), pages 316-326.
    3. Moo-Sung Sohn & Jiwoong Choi & Hoseog Kang & In-Chan Choi, 2017. "Multiobjective Production Planning at LG Display," Interfaces, INFORMS, vol. 47(4), pages 279-291, August.
    4. Carlos Llopis-Albert & José M. Merigó & Huchang Liao & Yejun Xu & Juan Grima-Olmedo & Carlos Grima-Olmedo, 2018. "Water Policies and Conflict Resolution of Public Participation Decision-Making Processes Using Prioritized Ordered Weighted Averaging (OWA) Operators," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(2), pages 497-510, January.
    5. Daniel, S. E. & Diakoulaki, D. C. & Pappis, C. P., 1997. "Operations research and environmental planning," European Journal of Operational Research, Elsevier, vol. 102(2), pages 248-263, October.
    6. Grzegorz Bocewicz & Zbigniew Banaszak & Izabela Nielsen, 2019. "Multimodal processes prototyping subject to grid-like network and fuzzy operation time constraints," Annals of Operations Research, Springer, vol. 273(1), pages 561-585, February.
    7. Alix Vargas & Carmen Fuster & David Corne, 2020. "Towards Sustainable Collaborative Logistics Using Specialist Planning Algorithms and a Gain-Sharing Business Model: A UK Case Study," Sustainability, MDPI, vol. 12(16), pages 1-29, August.
    8. Kabir, Golam & Tesfamariam, Solomon & Francisque, Alex & Sadiq, Rehan, 2015. "Evaluating risk of water mains failure using a Bayesian belief network model," European Journal of Operational Research, Elsevier, vol. 240(1), pages 220-234.
    9. Gian Paramo & Arturo Bretas, 2023. "Proactive Frequency Stability Scheme: A Distributed Framework Based on Particle Filters and Synchrophasors," Energies, MDPI, vol. 16(11), pages 1-19, June.
    10. Mohammad Heydari & Kin Keung Lai, 2023. "Post-COVID-19 Pandemic Era and Sustainable Healthcare: Organization and Delivery of Health Economics Research (Principles and Clinical Practice)," Mathematics, MDPI, vol. 11(16), pages 1-30, August.
    11. Khayyam, Hamid & Naebe, Minoo & Bab-Hadiashar, Alireza & Jamshidi, Farshid & Li, Quanxiang & Atkiss, Stephen & Buckmaster, Derek & Fox, Bronwyn, 2015. "Stochastic optimization models for energy management in carbonization process of carbon fiber production," Applied Energy, Elsevier, vol. 158(C), pages 643-655.
    12. Ioannis Fragkos & Bert De Reyck, 2016. "Improving the Maritime Transshipment Operations of the Noble Group," Interfaces, INFORMS, vol. 46(3), pages 203-217, April.
    13. Chung, S.H. & Lau, H.C.W. & Choy, K.L. & Ho, G.T.S. & Tse, Y.K., 2010. "Application of genetic approach for advanced planning in multi-factory environment," International Journal of Production Economics, Elsevier, vol. 127(2), pages 300-308, October.
    14. Bohle, Carlos & Maturana, Sergio & Vera, Jorge, 2010. "A robust optimization approach to wine grape harvesting scheduling," European Journal of Operational Research, Elsevier, vol. 200(1), pages 245-252, January.
    15. Silvente, Javier & Aguirre, Adrián M. & Zamarripa, Miguel A. & Méndez, Carlos A. & Graells, Moisès & Espuña, Antonio, 2015. "Improved time representation model for the simultaneous energy supply and demand management in microgrids," Energy, Elsevier, vol. 87(C), pages 615-627.
    16. M. Saqlain & S. Ali & J. Y. Lee, 2023. "A Monte-Carlo tree search algorithm for the flexible job-shop scheduling in manufacturing systems," Flexible Services and Manufacturing Journal, Springer, vol. 35(2), pages 548-571, June.
    17. Solomon Tesfamariam & Rehan Sadiq & Homayoun Najjaran, 2010. "Decision Making Under Uncertainty—An Example for Seismic Risk Management," Risk Analysis, John Wiley & Sons, vol. 30(1), pages 78-94, January.
    18. Laing, Harry & O'Malley, Chris & Browne, Anthony & Rutherford, Tony & Baines, Tony & Moore, Andrew & Black, Ken & Willis, Mark J., 2022. "Optimisation of energy usage and carbon emissions monitoring using MILP for an advanced anaerobic digester plant," Energy, Elsevier, vol. 256(C).
    19. Olivér Ősz & Balázs Ferenczi & Máté Hegyháti, 2020. "Scheduling a forge with due dates and die deterioration," Annals of Operations Research, Springer, vol. 285(1), pages 353-367, February.
    20. Seyed Ahmad Hosseini, 2013. "A Model-Based Approach and Analysis for Multi-Period Networks," Journal of Optimization Theory and Applications, Springer, vol. 157(2), pages 486-512, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:269:y:2018:i:1:p:227-243. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.