IDEAS home Printed from https://ideas.repec.org/a/ibn/masjnl/v10y2016i8p230.html
   My bibliography  Save this article

A Combined Approach for Production Parameter Selection and On-site Energy Supply Management in Manufacturing Industry

Author

Listed:
  • Pouya Ghadimi
  • Seyed Mousavi
  • Wen Li
  • Sami Kara
  • Bernard Kornfeld

Abstract

Integrated management of manufacturing plant’s production and on-site energy supply systems has shown potential economic, environmental and resource efficiency advantages for the industry. However, existing approaches are solely based on pure mathematical models with a high degree of abstraction with limited applicability, which becomes impractical for industrial applications. In this paper a simulation methodology for production parameters selection and on-site energy supply management is presented. In this case, state-based models and operational strategies of manufacturing processes and on-site energy supply options are integrated to represent interdependency between production processes, technical building services and on-site energy supply system. As a result, the proposed methodology covers manufacturing system complexity without compromising the required accuracy. This is applied to a batch based manufacturing plant and the impact of particular production parameters on energy demand profile is evaluated. The results indicate the impact of production parameters on energy supply system. In addition, the proposed approach enables manufacturers to evaluate the implications of potential production approaches in order to select appropriate operational strategies for on-site energy supply systems.

Suggested Citation

  • Pouya Ghadimi & Seyed Mousavi & Wen Li & Sami Kara & Bernard Kornfeld, 2016. "A Combined Approach for Production Parameter Selection and On-site Energy Supply Management in Manufacturing Industry," Modern Applied Science, Canadian Center of Science and Education, vol. 10(8), pages 230-230, August.
    • Handle: RePEc:ibn:masjnl:v:10:y:2016:i:8:p:230
    as

    Download full text from publisher

    File URL: https://ccsenet.org/journal/index.php/mas/article/download/56485/32606
    Download Restriction: no
    File URL: https://ccsenet.org/journal/index.php/mas/article/view/56485
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Stadtler, Hartmut, 2005. "Supply chain management and advanced planning--basics, overview and challenges," European Journal of Operational Research, Elsevier, vol. 163(3), pages 575-588, June.
    2. Hartmut Stadtler, 2005. "Production Planning and Scheduling," Springer Books, in: Hartmut Stadtler & Christoph Kilger (ed.), Supply Chain Management and Advanced Planning, edition 0, chapter 10, pages 197-214, Springer.
    3. Mařík, Karel & Schindler, Zdenek & Stluka, Petr, 2008. "Decision support tools for advanced energy management," Energy, Elsevier, vol. 33(6), pages 858-873.
    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. Mustapha Ouhimmou & Sophie D'Amours & Robert Beauregard & Daoud Ait-Kadi & Satyaveer Singh Chauhan, 2009. "Optimization Helps Shermag Gain Competitive Edge," Interfaces, INFORMS, vol. 39(4), pages 329-345, August.
    2. Yong Zeng & Yanpeng Cai & Guohe Huang & Jing Dai, 2011. "A Review on Optimization Modeling of Energy Systems Planning and GHG Emission Mitigation under Uncertainty," Energies, MDPI, vol. 4(10), pages 1-33, October.
    3. Sivadasan, Suja & Smart, Janet & Huaccho Huatuco, Luisa & Calinescu, Anisoara, 2013. "Reducing schedule instability by identifying and omitting complexity-adding information flows at the supplier–customer interface," International Journal of Production Economics, Elsevier, vol. 145(1), pages 253-262.
    4. Mate Barany & Zsolt Tuza, 2015. "Circular coloring of graphs via linear programming and tabu search," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 23(4), pages 833-848, December.
    5. Ewing, Bradley T. & Thompson, Mark A., 2008. "Industrial production, volatility, and the supply chain," International Journal of Production Economics, Elsevier, vol. 115(2), pages 553-558, October.
    6. Malinowski, Ethan & Karwan, Mark H. & Pinto, José M. & Sun, Lei, 2018. "A mixed-integer programming strategy for liquid helium global supply chain planning," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 110(C), pages 168-188.
    7. Laura Laguna-Salvadó & Matthieu Lauras & Uche Okongwu & Tina Comes, 2019. "A multicriteria Master Planning DSS for a sustainable humanitarian supply chain," Annals of Operations Research, Springer, vol. 283(1), pages 1303-1343, December.
    8. Abirami Raja Santhi & Padmakumar Muthuswamy, 2022. "Pandemic, War, Natural Calamities, and Sustainability: Industry 4.0 Technologies to Overcome Traditional and Contemporary Supply Chain Challenges," Logistics, MDPI, vol. 6(4), pages 1-32, November.
    9. Ma, Weiwu & Fang, Song & Liu, Gang & Zhou, Ruoyu, 2017. "Modeling of district load forecasting for distributed energy system," Applied Energy, Elsevier, vol. 204(C), pages 181-205.
    10. Weckenborg, Christian & Schumacher, Patrick & Thies, Christian & Spengler, Thomas S., 2024. "Flexibility in manufacturing system design: A review of recent approaches from Operations Research," European Journal of Operational Research, Elsevier, vol. 315(2), pages 413-441.
    11. Shiyu Chen & Wei Wang & Enrico Zio, 2021. "A Simulation-Based Multi-Objective Optimization Framework for the Production Planning in Energy Supply Chains," Energies, MDPI, vol. 14(9), pages 1-27, May.
    12. Jaller, Miguel & Harvey, John T. & Saremi, Sogol & Ambrose, Hanjiro & Butt, Ali A., 2018. "Development of a Freight System Conceptualization and Impact Assessment (Fre‐SCANDIA) Framework," Institute of Transportation Studies, Working Paper Series qt05g8p7tn, Institute of Transportation Studies, UC Davis.
    13. Camélia Dadouchi & Bruno Agard, 2021. "Recommender systems as an agility enabler in supply chain management," Journal of Intelligent Manufacturing, Springer, vol. 32(5), pages 1229-1248, June.
    14. Sharif, Amir M. & Irani, Zahir, 2012. "Supply Chain Leadership," International Journal of Production Economics, Elsevier, vol. 140(1), pages 57-68.
    15. Justyna Smagowicz & Cezary Szwed & Dawid Dąbal & Pavel Scholz, 2022. "A Simulation Model of Power Demand Management by Manufacturing Enterprises under the Conditions of Energy Sector Transformation," Energies, MDPI, vol. 15(9), pages 1-27, April.
    16. Athanassios Nikolakopoulos & Ioannis Ganas, 2017. "Economic model predictive inventory routing and control," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 25(3), pages 587-609, September.
    17. Dominguez, Roberto & Cannella, Salvatore & Barbosa-Póvoa, Ana P. & Framinan, Jose M., 2018. "Information sharing in supply chains with heterogeneous retailers," Omega, Elsevier, vol. 79(C), pages 116-132.
    18. Ahumada, Omar & Villalobos, J. Rene, 2009. "Application of planning models in the agri-food supply chain: A review," European Journal of Operational Research, Elsevier, vol. 196(1), pages 1-20, July.
    19. Difs, Kristina & Bennstam, Marcus & Trygg, Louise & Nordenstam, Lena, 2010. "Energy conservation measures in buildings heated by district heating – A local energy system perspective," Energy, Elsevier, vol. 35(8), pages 3194-3203.
    20. Aziz Hmioui & Badr Bentalha & Alla Lhoussaine, 2022. "Efficiency of the green service supply chain management: which practices for which performances? [Efficacité du green service supply chain management : quelles pratiques pour quelles performances ?," Post-Print hal-03703828, HAL.

    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

    Statistics

    Access and download statistics

    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:ibn:masjnl:v:10:y:2016:i:8:p:230. 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: Canadian Center of Science and Education (email available below). General contact details of provider: https://edirc.repec.org/data/cepflch.html .

    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.