IDEAS home Printed from https://ideas.repec.org/a/spr/opmare/v16y2023i4d10.1007_s12063-023-00381-0.html
   My bibliography  Save this article

An efficiency-based aggregate production planning model for multi-line manufacturing systems

Author

Listed:
  • S. Ali Naji Nasrabadi Yazd

    (Ferdowsi University of Mashhad)

  • Amirhossein Salamirad

    (University of British Columbia)

  • Siamak Kheybari

    (University of Cambridge)

  • Alessio Ishizaka

    (NEOMA Business School)

Abstract

Aggregate production planning (APP) is a medium-term planning in the production system, which determines the optimal production plan in the planning horizon. To allocate the optimal production quantity to the production lines, we propose an efficiency-based APP to multi-line manufacturing systems. For that purpose, first, considering the line efficiency factors, we calculate the efficiency score of production lines with an extension of data envelopment analysis (namely DEA-AR). Pollution rate, defective product rate, production capacity, downtime, and electricity consumption are the criteria employed to calculate the efficiency of production lines. Then, using the result of DEA as a parameter, we develop a bi-objectives integer mathematical model that allocates the most production to efficient lines while minimizing total production costs considering loading constraints. To solve the proposed model, the ℇ-constraint method is employed. We evaluate the performance of the multi-line APP using a set of data collected from a plastic production factory. Results indicate that in using the proposed model, both efficiency and production costs are appropriately satisfied in the efficiency-based APP. The proposed framework is generic and provides the managers of different manufacturing organizations with a powerful tool to deal with medium-term planning by taking the line efficiency into account.

Suggested Citation

  • S. Ali Naji Nasrabadi Yazd & Amirhossein Salamirad & Siamak Kheybari & Alessio Ishizaka, 2023. "An efficiency-based aggregate production planning model for multi-line manufacturing systems," Operations Management Research, Springer, vol. 16(4), pages 2008-2024, December.
    • Handle: RePEc:spr:opmare:v:16:y:2023:i:4:d:10.1007_s12063-023-00381-0
    DOI: 10.1007/s12063-023-00381-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12063-023-00381-0
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s12063-023-00381-0?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. Ríos-Solís, Yasmín Á & Ibarra-Rojas, Omar J. & Cabo, Marta & Possani, Edgar, 2020. "A heuristic based on mathematical programming for a lot-sizing and scheduling problem in mold-injection production," European Journal of Operational Research, Elsevier, vol. 284(3), pages 861-873.
    2. Mohammad Reza Bazargan-Lari & Sharareh Taghipour & Arash Zaretalab & Mani Sharifi, 2022. "Production scheduling optimization for parallel machines subject to physical distancing due to COVID-19 pandemic," Operations Management Research, Springer, vol. 15(1), pages 503-527, June.
    3. Kong, Wei-Hsin & Fu, Tsu-Tan, 2012. "Assessing the performance of business colleges in Taiwan using data envelopment analysis and student based value-added performance indicators," Omega, Elsevier, vol. 40(5), pages 541-549.
    4. Ouchi, Fumika, 2004. "A literature review on the use of expert opinion in probabilistic risk analysis," Policy Research Working Paper Series 3201, The World Bank.
    5. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    6. Russell G. Thompson & F. D. Singleton & Robert M. Thrall & Barton A. Smith, 1986. "Comparative Site Evaluations for Locating a High-Energy Physics Lab in Texas," Interfaces, INFORMS, vol. 16(6), pages 35-49, December.
    7. Taylor, William M. & Thompson, Russell G. & Thrall, Robert M. & Dharmapala, P. S., 1997. "DEA/AR efficiency and profitability of Mexican banks a total income model," European Journal of Operational Research, Elsevier, vol. 98(2), pages 346-363, April.
    8. Ray, SC & Seiford, LM & Zhu, J, 1998. "Market Entity Behavior of Chinese State-owned Enterprises," Omega, Elsevier, vol. 26(2), pages 263-278, April.
    9. Thompson, Russell G. & Brinkmann, Emile J. & Dharmapala, P. S. & Gonzalez-Lima, M. D. & Thrall, Robert M., 1997. "DEA/AR profit ratios and sensitivity of 100 large U.S. banks," European Journal of Operational Research, Elsevier, vol. 98(2), pages 213-229, April.
    10. Lulu Xin & Shuai Lang & Arunodaya Raj Mishra, 2022. "RETRACTED ARTICLE: Evaluate the challenges of sustainable supply chain 4.0 implementation under the circular economy concept using new decision making approach," Operations Management Research, Springer, vol. 15(3), pages 773-792, December.
    11. Hashimoto, Akihiro, 1997. "A ranked voting system using a DEA/AR exclusion model: A note," European Journal of Operational Research, Elsevier, vol. 97(3), pages 600-604, March.
    12. Tadić, Snežana & Krstić, Mladen & Brnjac, Nikolina, 2019. "Selection of efficient types of inland intermodal terminals," Journal of Transport Geography, Elsevier, vol. 78(C), pages 170-180.
    13. Raa, Birger & Dullaert, Wout & Aghezzaf, El-Houssaine, 2013. "A matheuristic for aggregate production–distribution planning with mould sharing," International Journal of Production Economics, Elsevier, vol. 145(1), pages 29-37.
    14. Mohammad Reza Bazargan-Lari & Sharareh Taghipour & Arash Zaretalab & Mani Sharifi, 2022. "Correction to: Production scheduling optimization for parallel machines subject to physical distancing due to COVID-19 pandemic," Operations Management Research, Springer, vol. 15(3), pages 1510-1510, December.
    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. Camanho, A. S. & Dyson, R. G., 2005. "Cost efficiency measurement with price uncertainty: a DEA application to bank branch assessments," European Journal of Operational Research, Elsevier, vol. 161(2), pages 432-446, March.
    2. Adler, Nicole & Friedman, Lea & Sinuany-Stern, Zilla, 2002. "Review of ranking methods in the data envelopment analysis context," European Journal of Operational Research, Elsevier, vol. 140(2), pages 249-265, July.
    3. Huang, Beijia & Zhang, Long & Ma, Linmao & Bai, Wuliyasu & Ren, Jingzheng, 2021. "Multi-criteria decision analysis of China’s energy security from 2008 to 2017 based on Fuzzy BWM-DEA-AR model and Malmquist Productivity Index," Energy, Elsevier, vol. 228(C).
    4. Lei Fang & Hecheng Li, 2013. "Lower bound of cost efficiency measure in DEA with incomplete price information," Journal of Productivity Analysis, Springer, vol. 40(2), pages 219-226, October.
    5. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    6. Obata, Tsuneshi & Ishii, Hiroaki, 2003. "A method for discriminating efficient candidates with ranked voting data," European Journal of Operational Research, Elsevier, vol. 151(1), pages 233-237, November.
    7. Lai, Po‐Lin & Potter, Andrew & Beynon, Malcolm & Beresford, Anthony, 2015. "Evaluating the efficiency performance of airports using an integrated AHP/DEA-AR technique," Transport Policy, Elsevier, vol. 42(C), pages 75-85.
    8. Madjid Tavana & Mehdi Soltanifar & Francisco J. Santos-Arteaga, 2023. "Analytical hierarchy process: revolution and evolution," Annals of Operations Research, Springer, vol. 326(2), pages 879-907, July.
    9. Khalili, M. & Camanho, A.S. & Portela, M.C.A.S. & Alirezaee, M.R., 2010. "The measurement of relative efficiency using data envelopment analysis with assurance regions that link inputs and outputs," European Journal of Operational Research, Elsevier, vol. 203(3), pages 761-770, June.
    10. Foroughi, A.A. & Tamiz, M., 2005. "An effective total ranking model for a ranked voting system," Omega, Elsevier, vol. 33(6), pages 491-496, December.
    11. Tadić, Snežana & Krstić, Mladen & Brnjac, Nikolina, 2019. "Selection of efficient types of inland intermodal terminals," Journal of Transport Geography, Elsevier, vol. 78(C), pages 170-180.
    12. Podinovski, V. V., 2004. "Suitability and redundancy of non-homogeneous weight restrictions for measuring the relative efficiency in DEA," European Journal of Operational Research, Elsevier, vol. 154(2), pages 380-395, April.
    13. Shih-Pin Chen & Chung-Wei Chang, 2021. "Measuring the efficiency of university departments: an empirical study using data envelopment analysis and cluster analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(6), pages 5263-5284, June.
    14. Asmild, Mette & Paradi, Joseph C. & Reese, David N. & Tam, Fai, 2007. "Measuring overall efficiency and effectiveness using DEA," European Journal of Operational Research, Elsevier, vol. 178(1), pages 305-321, April.
    15. Dimitrov, Stanko & Sutton, Warren, 2013. "Generalized symmetric weight assignment technique: Incorporating managerial preferences in data envelopment analysis using a penalty function," Omega, Elsevier, vol. 41(1), pages 48-54.
    16. Pishchulov, Grigory & Trautrims, Alexander & Chesney, Thomas & Gold, Stefan & Schwab, Leila, 2019. "The Voting Analytic Hierarchy Process revisited: A revised method with application to sustainable supplier selection," International Journal of Production Economics, Elsevier, vol. 211(C), pages 166-179.
    17. A Mukherjee & P Nath & M Pal, 2003. "Resource, service quality and performance triad: a framework for measuring efficiency of banking services," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(7), pages 723-735, July.
    18. Alexandr Gedranovich & Mykhaylo Salnykov, 2012. "Productivity analysis of Belarusian higher education system," BEROC Working Paper Series 16, Belarusian Economic Research and Outreach Center (BEROC).
    19. Conde, Eduardo, 2002. "Mean utility in the assurance region model," European Journal of Operational Research, Elsevier, vol. 140(1), pages 93-103, July.
    20. Karasakal, Esra & Aker, Pınar, 2017. "A multicriteria sorting approach based on data envelopment analysis for R&D project selection problem," Omega, Elsevier, vol. 73(C), pages 79-92.

    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:spr:opmare:v:16:y:2023:i:4:d:10.1007_s12063-023-00381-0. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.