IDEAS home Printed from https://ideas.repec.org/a/spr/joinma/v28y2017i1d10.1007_s10845-014-0962-z.html
   My bibliography  Save this article

Patching process optimization in an agent-controlled timber mill

Author

Listed:
  • Matthias Wolfgang Hofmair

    (Vienna University of Technology)

  • Martin Melik-Merkumians

    (Vienna University of Technology)

  • Martin Böck

    (Vienna University of Technology)

  • Munir Merdan

    (Vienna University of Technology)

  • Georg Schitter

    (Vienna University of Technology)

  • Andreas Kugi

    (Vienna University of Technology)

Abstract

Repair and patching of wood defects is a costly process of inline production in timber industry. A large variety of plain as well as laminated wooden products demands for offline human interaction and skilled handcrafting in order to achieve the desired quality of the final products. The EU FP7 project Hol-I-Wood PR demonstrates the transformation of a traditional wood patching line for shuttering panels into a fully automated, flexible patching plant. The focus of this paper is set on the optimization of the different production steps of a patching robot, which comprises optimal patch placement, path planning and trajectory generation. Based on this, the processing time of each workpiece can be accurately estimated. These computations serve as an input for advanced panel scheduling, which assigns panels to one of several identical parallel patching lines in a throughput-optimal manner. In order to ensure high modularity of the components and scalability for various wood mills, an agent-based approach was chosen for the implementation of the automation system.

Suggested Citation

  • Matthias Wolfgang Hofmair & Martin Melik-Merkumians & Martin Böck & Munir Merdan & Georg Schitter & Andreas Kugi, 2017. "Patching process optimization in an agent-controlled timber mill," Journal of Intelligent Manufacturing, Springer, vol. 28(1), pages 69-84, January.
    • Handle: RePEc:spr:joinma:v:28:y:2017:i:1:d:10.1007_s10845-014-0962-z
    DOI: 10.1007/s10845-014-0962-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10845-014-0962-z
    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/s10845-014-0962-z?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. Luca Maria Gambardella & Marco Dorigo, 2000. "An Ant Colony System Hybridized with a New Local Search for the Sequential Ordering Problem," INFORMS Journal on Computing, INFORMS, vol. 12(3), pages 237-255, August.
    2. Helsgaun, Keld, 2000. "An effective implementation of the Lin-Kernighan traveling salesman heuristic," European Journal of Operational Research, Elsevier, vol. 126(1), pages 106-130, October.
    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. Nikolakopoulos, Athanassios & Sarimveis, Haralambos, 2007. "A threshold accepting heuristic with intense local search for the solution of special instances of the traveling salesman problem," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1911-1929, March.
    2. Anurag Agarwal, 2009. "Theoretical insights into the augmented-neural-network approach for combinatorial optimization," Annals of Operations Research, Springer, vol. 168(1), pages 101-117, April.
    3. A. Scholz & G. Wäscher, 2017. "Order Batching and Picker Routing in manual order picking systems: the benefits of integrated routing," 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(2), pages 491-520, June.
    4. Deeam Najmadeen Hama Rashid & Tarik A. Rashid & Seyedali Mirjalili, 2021. "ANA: Ant Nesting Algorithm for Optimizing Real-World Problems," Mathematics, MDPI, vol. 9(23), pages 1-30, December.
    5. Lang, Jan Christian & Shen, Zuo-Jun Max, 2011. "Fix-and-optimize heuristics for capacitated lot-sizing with sequence-dependent setups and substitutions," European Journal of Operational Research, Elsevier, vol. 214(3), pages 595-605, November.
    6. Löhndorf, Nils & Riel, Manuel & Minner, Stefan, 2014. "Simulation optimization for the stochastic economic lot scheduling problem with sequence-dependent setup times," International Journal of Production Economics, Elsevier, vol. 157(C), pages 170-176.
    7. van Gils, Teun & Ramaekers, Katrien & Braekers, Kris & Depaire, Benoît & Caris, An, 2018. "Increasing order picking efficiency by integrating storage, batching, zone picking, and routing policy decisions," International Journal of Production Economics, Elsevier, vol. 197(C), pages 243-261.
    8. Ghosh, Diptesh, 2016. "Exploring Lin Kernighan neighborhoods for the indexing problem," IIMA Working Papers WP2016-02-13, Indian Institute of Management Ahmedabad, Research and Publication Department.
    9. Fleming, Christopher L. & Griffis, Stanley E. & Bell, John E., 2013. "The effects of triangle inequality on the vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 224(1), pages 1-7.
    10. Drexl, M. & Schneider, M., 2014. "A Survey of the Standard Location-Routing Problem," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 65940, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    11. Silva, Allyson & Coelho, Leandro C. & Darvish, Maryam & Renaud, Jacques, 2020. "Integrating storage location and order picking problems in warehouse planning," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 140(C).
    12. B. I. Goldengorin & D. S. Malyshev & P. M. Pardalos & V. A. Zamaraev, 2015. "A tolerance-based heuristic approach for the weighted independent set problem," Journal of Combinatorial Optimization, Springer, vol. 29(2), pages 433-450, February.
    13. Krešimir Mihić & Kevin Ryan & Alan Wood, 2018. "Randomized Decomposition Solver with the Quadratic Assignment Problem as a Case Study," INFORMS Journal on Computing, INFORMS, vol. 30(2), pages 295-308, May.
    14. Vig, Vikrant & Palekar, Udatta S., 2008. "On estimating the distribution of optimal traveling salesman tour lengths using heuristics," European Journal of Operational Research, Elsevier, vol. 186(1), pages 111-119, April.
    15. Jiang, Zhongzhou & Liu, Jing & Wang, Shuai, 2016. "Traveling salesman problems with PageRank Distance on complex networks reveal community structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 463(C), pages 293-302.
    16. Jean-Charles Créput & Amir Hajjam & Abderrafiaa Koukam & Olivier Kuhn, 2012. "Self-organizing maps in population based metaheuristic to the dynamic vehicle routing problem," Journal of Combinatorial Optimization, Springer, vol. 24(4), pages 437-458, November.
    17. Zongxu Mu & Jérémie Dubois-Lacoste & Holger H. Hoos & Thomas Stützle, 2018. "On the empirical scaling of running time for finding optimal solutions to the TSP," Journal of Heuristics, Springer, vol. 24(6), pages 879-898, December.
    18. Lin, Shih-Wei & Ying, Kuo-Ching, 2016. "Optimization of makespan for no-wait flowshop scheduling problems using efficient matheuristics," Omega, Elsevier, vol. 64(C), pages 115-125.
    19. Henke, Tino & Speranza, M. Grazia & Wäscher, Gerhard, 2015. "The multi-compartment vehicle routing problem with flexible compartment sizes," European Journal of Operational Research, Elsevier, vol. 246(3), pages 730-743.
    20. Jing Yu & Lining Xing & Xu Tan, 0. "The new treatment mode research of hepatitis B based on ant colony algorithm," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-20.

    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:28:y:2017:i:1:d:10.1007_s10845-014-0962-z. 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.