IDEAS home Printed from https://ideas.repec.org/a/spr/joinma/v33y2022i4d10.1007_s10845-021-01901-0.html
   My bibliography  Save this article

Heuristic based approach for short term production planning in highly automated customer oriented pallet production

Author

Listed:
  • Matthias Kaltenbrunner

    (BOKU, University of Natural Resources and Life Science)

  • Maria Anna Huka

    (BOKU, University of Natural Resources and Life Science)

  • Manfred Gronalt

    (BOKU, University of Natural Resources and Life Science)

Abstract

Wooden pallets are commonly used as load carriers in many industrial and logistic applications. This article investigates and formalizes the production planning for a highly automated but customized pallet production and provides a solution approach. For completing a specific pallet, the required boards must be cut and stacked in advance to meet the demand at the assembly line. The arising planning problem for producing the required boards consists of both a cutting stock and a constraining open stack problem. Further, both the changeover of raw material at the cutting process and the number of fully automated internal storages, for stacked boards, are restricted. The proposed solution heuristic aims at minimizing the cutting waste. Additionally, feasibility with regard to the buffers is tested using discrete event simulation. Different approaches to generate, select and sequence the cutting patterns are investigated.

Suggested Citation

  • Matthias Kaltenbrunner & Maria Anna Huka & Manfred Gronalt, 2022. "Heuristic based approach for short term production planning in highly automated customer oriented pallet production," Journal of Intelligent Manufacturing, Springer, vol. 33(4), pages 1087-1098, April.
    • Handle: RePEc:spr:joinma:v:33:y:2022:i:4:d:10.1007_s10845-021-01901-0
    DOI: 10.1007/s10845-021-01901-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10845-021-01901-0
    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/s10845-021-01901-0?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. Yanasse, Horacio Hideki & Senne, Edson Luiz França, 2010. "The minimization of open stacks problem: A review of some properties and their use in pre-processing operations," European Journal of Operational Research, Elsevier, vol. 203(3), pages 559-567, June.
    2. Gleb Belov & Guntram Scheithauer, 2007. "Setup and Open-Stacks Minimization in One-Dimensional Stock Cutting," INFORMS Journal on Computing, INFORMS, vol. 19(1), pages 27-35, February.
    3. Byung-In Kim & Youngmin Ki & Donghee Son & Byungjoo Bae & Jun-Seo Park, 2016. "An algorithm for a cutting problem in window frame production," International Journal of Production Research, Taylor & Francis Journals, vol. 54(14), pages 4327-4339, July.
    4. Harjunkoski, Iiro & Westerlund, Tapio & Porn, Ray & Skrifvars, Hans, 1998. "Different transformations for solving non-convex trim-loss problems by MINLP," European Journal of Operational Research, Elsevier, vol. 105(3), pages 594-603, March.
    5. Melega, Gislaine Mara & de Araujo, Silvio Alexandre & Jans, Raf, 2018. "Classification and literature review of integrated lot-sizing and cutting stock problems," European Journal of Operational Research, Elsevier, vol. 271(1), pages 1-19.
    6. Christopher S. Tang & Eric V. Denardo, 1988. "Models Arising from a Flexible Manufacturing Machine, Part II: Minimization of the Number of Switching Instants," Operations Research, INFORMS, vol. 36(5), pages 778-784, October.
    7. Chen, Chuen-Lung S. & Hart, Stephen M. & Tham, Wai Mui, 1996. "A simulated annealing heuristic for the one-dimensional cutting stock problem," European Journal of Operational Research, Elsevier, vol. 93(3), pages 522-535, September.
    8. Armbruster, Michael, 2002. "A solution procedure for a pattern sequencing problem as part of a one-dimensional cutting stock problem in the steel industry," European Journal of Operational Research, Elsevier, vol. 141(2), pages 328-340, September.
    9. Rafael de Magalhães Dias Frinhani & Marco Antonio Moreira de Carvalho & Nei Yoshihiro Soma, 2018. "A PageRank-based heuristic for the minimization of open stacks problem," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-24, August.
    10. Christopher S. Tang & Eric V. Denardo, 1988. "Models Arising from a Flexible Manufacturing Machine, Part I: Minimization of the Number of Tool Switches," Operations Research, INFORMS, vol. 36(5), pages 767-777, October.
    11. Arbib, Claudio & Marinelli, Fabrizio & Pezzella, Ferdinando, 2012. "An LP-based tabu search for batch scheduling in a cutting process with finite buffers," International Journal of Production Economics, Elsevier, vol. 136(2), pages 287-296.
    12. Soeiro Ferreira, J. & Antonio Neves, M. & Fonseca e Castro, P., 1990. "A two-phase roll cutting problem," European Journal of Operational Research, Elsevier, vol. 44(2), pages 185-196, January.
    13. Yanasse, Horacio Hideki & Pinto Lamosa, Maria Jose, 2007. "An integrated cutting stock and sequencing problem," European Journal of Operational Research, Elsevier, vol. 183(3), pages 1353-1370, December.
    14. Beraldi, P. & Bruni, M.E. & Conforti, D., 2009. "The stochastic trim-loss problem," European Journal of Operational Research, Elsevier, vol. 197(1), pages 42-49, August.
    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. Arbib, Claudio & Marinelli, Fabrizio & Pezzella, Ferdinando, 2012. "An LP-based tabu search for batch scheduling in a cutting process with finite buffers," International Journal of Production Economics, Elsevier, vol. 136(2), pages 287-296.
    2. Kallrath, Julia & Rebennack, Steffen & Kallrath, Josef & Kusche, Rüdiger, 2014. "Solving real-world cutting stock-problems in the paper industry: Mathematical approaches, experience and challenges," European Journal of Operational Research, Elsevier, vol. 238(1), pages 374-389.
    3. Gislaine Mara Melega & Silvio Alexandre de Araujo & Reinaldo Morabito, 2020. "Mathematical model and solution approaches for integrated lot-sizing, scheduling and cutting stock problems," Annals of Operations Research, Springer, vol. 295(2), pages 695-736, December.
    4. Melega, Gislaine Mara & de Araujo, Silvio Alexandre & Jans, Raf, 2018. "Classification and literature review of integrated lot-sizing and cutting stock problems," European Journal of Operational Research, Elsevier, vol. 271(1), pages 1-19.
    5. Yves Crama & Joris van de Klundert, 1999. "Worst‐case performance of approximation algorithms for tool management problems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 46(5), pages 445-462, August.
    6. Anselmo Ramalho Pitombeira-Neto & Bruno de Athayde Prata, 2020. "A matheuristic algorithm for the one-dimensional cutting stock and scheduling problem with heterogeneous orders," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(1), pages 178-192, April.
    7. Calmels, Dorothea, 2022. "An iterated local search procedure for the job sequencing and tool switching problem with non-identical parallel machines," European Journal of Operational Research, Elsevier, vol. 297(1), pages 66-85.
    8. Chakravarty, Amiya K. & Balakrishnan, Nagraj, 1997. "Job sequencing rules for minimizing the expected makespan in flexible machines," European Journal of Operational Research, Elsevier, vol. 96(2), pages 274-288, January.
    9. Matzliach, Barouch & Tzur, Michal, 2000. "Storage management of items in two levels of availability," European Journal of Operational Research, Elsevier, vol. 121(2), pages 363-379, March.
    10. M. Selim Akturk & Jay B. Ghosh & Evrim D. Gunes, 2003. "Scheduling with tool changes to minimize total completion time: A study of heuristics and their performance," Naval Research Logistics (NRL), John Wiley & Sons, vol. 50(1), pages 15-30, February.
    11. Soares, Leonardo Cabral R. & Carvalho, Marco Antonio M., 2020. "Biased random-key genetic algorithm for scheduling identical parallel machines with tooling constraints," European Journal of Operational Research, Elsevier, vol. 285(3), pages 955-964.
    12. Moshe Dror & Mohamed Haouari, 2000. "Generalized Steiner Problems and Other Variants," Journal of Combinatorial Optimization, Springer, vol. 4(4), pages 415-436, December.
    13. Konak, Abdullah & Kulturel-Konak, Sadan & Azizoglu, Meral, 2008. "Minimizing the number of tool switching instants in Flexible Manufacturing Systems," International Journal of Production Economics, Elsevier, vol. 116(2), pages 298-307, December.
    14. Atan, Tankut S. & Pandit, Ram, 1996. "Auxiliary tool allocation in flexible manufacturing systems," European Journal of Operational Research, Elsevier, vol. 89(3), pages 642-659, March.
    15. Cui, Yaodong & Yang, Liu & Zhao, Zhigang & Tang, Tianbing & Yin, Mengxiao, 2013. "Sequential grouping heuristic for the two-dimensional cutting stock problem with pattern reduction," International Journal of Production Economics, Elsevier, vol. 144(2), pages 432-439.
    16. Sodhi, Manbir S. & Lamond, Bernard F. & Gautier, Antoine & Noel, Martin, 2001. "Heuristics for determining economic processing rates in a flexible manufacturing system," European Journal of Operational Research, Elsevier, vol. 129(1), pages 105-115, February.
    17. Crama, Yves, 1997. "Combinatorial optimization models for production scheduling in automated manufacturing systems," European Journal of Operational Research, Elsevier, vol. 99(1), pages 136-153, May.
    18. Beraldi, P. & Bruni, M.E. & Conforti, D., 2009. "The stochastic trim-loss problem," European Journal of Operational Research, Elsevier, vol. 197(1), pages 42-49, August.
    19. Renato de Matta & Vernon Ning Hsu & Timothy J. Lowe, 1999. "Capacitated selection problem," Naval Research Logistics (NRL), John Wiley & Sons, vol. 46(1), pages 19-37, February.
    20. Ramiro Varela & Camino Vela & Jorge Puente & María Sierra & Inés González-Rodríguez, 2009. "An effective solution for a real cutting stock problem in manufacturing plastic rolls," Annals of Operations Research, Springer, vol. 166(1), pages 125-146, February.

    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:joinma:v:33:y:2022:i:4:d:10.1007_s10845-021-01901-0. 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.