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Integrated planning of transportation and recycling for multiple plants based on process simulation

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  • Fröhling, Magnus
  • Schwaderer, Frank
  • Bartusch, Hauke
  • Rentz, Otto

Abstract

By-products accrue in all stages of industrial production networks. Legal requirements, shortening of primary resources and their increasing prices make their recycling more and more important. For the re-integration into the economic cycle the scope of common supply chain management is enlarged and so-called closed-loop supply chains with adapted and new planning tasks are developed. In process industries this requires a detailed modelling of the recycling processes. This is of special relevance for operational planning tasks in which an optimal usage of a given production system is envisaged. This contribution presents an integrated planning approach for a real-world case study from the zinc industry to achieve such an adequate process modelling. We consider the planning problem of a company that operates four metallurgical recycling plants and has to allocate residues from different sources to these recycling sites. The allocation determines the raw material mix used in the plants. This blending has an effect on the transportation costs and the costs and revenues of the individual technical processes in the recycling plants. Therefore in this problem transportation and recycling planning for multiple sites have to be regarded in an integrated way. The necessary detailed process modelling is achieved by the use of a flowsheet process simulation system to model each recycling plant individually. The models are used to derive linear input-output functions by multiple linear regression analyses. These are used in an integrated planning model to calculate the decision-relevant input and output flows that are dependent upon the allocation of the residues to the recycling sites. The model is embedded in a decision support system for the operational use. An example application and sensitivity analyses demonstrate and validate the approach and its potentials. The approach is transferable to other recycling processes as well as to other processes in process industries.

Suggested Citation

  • Fröhling, Magnus & Schwaderer, Frank & Bartusch, Hauke & Rentz, Otto, 2010. "Integrated planning of transportation and recycling for multiple plants based on process simulation," European Journal of Operational Research, Elsevier, vol. 207(2), pages 958-970, December.
    • Handle: RePEc:eee:ejores:v:207:y:2010:i:2:p:958-970
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    Cited by:

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    4. Bhattacharya, Sourabh & Govindan, Kannan & Ghosh Dastidar, Surajit & Sharma, Preeti, 2024. "Applications of artificial intelligence in closed-loop supply chains: Systematic literature review and future research agenda," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 184(C).
    5. Gaurav Singh & Rodolfo García-Flores & Andreas Ernst & Palitha Welgama & Meimei Zhang & Kerry Munday, 2014. "Medium-Term Rail Scheduling for an Iron Ore Mining Company," Interfaces, INFORMS, vol. 44(2), pages 222-240, April.
    6. Porzio, Giacomo Filippo & Fornai, Barbara & Amato, Alessandro & Matarese, Nicola & Vannucci, Marco & Chiappelli, Lisa & Colla, Valentina, 2013. "Reducing the energy consumption and CO2 emissions of energy intensive industries through decision support systems – An example of application to the steel industry," Applied Energy, Elsevier, vol. 112(C), pages 818-833.
    7. Ching-Chin Chern & Hsin-Mei Wang & Kwei-Long Huang, 2017. "A heuristic master planning algorithm for recycling supply chain management," Journal of Intelligent Manufacturing, Springer, vol. 28(4), pages 985-1003, April.
    8. De Meyer, Annelies & Cattrysse, Dirk & Van Orshoven, Jos, 2015. "A generic mathematical model to optimise strategic and tactical decisions in biomass-based supply chains (OPTIMASS)," European Journal of Operational Research, Elsevier, vol. 245(1), pages 247-264.
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