IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v9y2021i9p1039-d548498.html
   My bibliography  Save this article

Packaging Process Optimization in Multihead Weighers with Double-Layered Upright and Diagonal Systems

Author

Listed:
  • Rafael García-Jiménez

    (Department of Exact Sciences, Universidad Simón Bolívar, Barranquilla 080020, Colombia)

  • J. Carlos García-Díaz

    (Department of Applied Statistics and Operations Research and Quality, Universitat Politècnica de València, 46022 Valencia, Spain)

  • Alexander D. Pulido-Rojano

    (Grupo de Consultoría e Innovación JJ&N S.A.S., Department of Industrial Engineering, Universidad Simón Bolívar, Barranquilla 080020, Colombia)

Abstract

In multihead weighers, packaging processes seek to find the best combination of passage hoppers whose product content provides a total package weight as close as possible to its (nominal) label weight. The weighing hoppers arranged in these machines dispense the product quantity that each package contains through computer algorithms designed and executed for this purpose. For its part, in the packaging process for double-layered multihead weighers, all hoppers are arranged in two levels. The first layer comprises a group of weighing hoppers, and the second comprises a set of booster hoppers placed uprightly or diagonally to each weighing hopper based on design of the machine. In both processes, the initial machine configuration is the same; however, the hopper selection algorithm works differently. This paper proposes a new packaging process optimization algorithm for double-layer upright and diagonal machines, wherein the hopper subset combined has previously been defined, and the packaging weight is expressed as actual values. As part of its validation, product filling strategies were implemented for weighing hoppers to assess the algorithm in different scenarios. Results from the process performance metrics prove that the new algorithm improves processes by reducing variability. In addition, results reveal that some machine configurations were also able to improve their operation.

Suggested Citation

  • Rafael García-Jiménez & J. Carlos García-Díaz & Alexander D. Pulido-Rojano, 2021. "Packaging Process Optimization in Multihead Weighers with Double-Layered Upright and Diagonal Systems," Mathematics, MDPI, vol. 9(9), pages 1-20, May.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:9:p:1039-:d:548498
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/9/9/1039/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/9/9/1039/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. J. Carlos García-Díaz & Alexander Pulido-Rojano & Vicent Giner-Bosch, 2017. "Bi-objective optimisation of a multihead weighing process," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 11(3), pages 403-423.
    2. del Castillo, Enrique & Beretta, Alessia & Semeraro, Quirico, 2017. "Optimal setup of a multihead weighing machine," European Journal of Operational Research, Elsevier, vol. 259(1), pages 384-393.
    3. Wishon, Christopher & Villalobos, J. Rene, 2016. "Robust efficiency measures for linear knapsack problem variants," European Journal of Operational Research, Elsevier, vol. 254(2), pages 398-409.
    4. J. Carlos García-Díaz & Alexander Pulido-Rojano, 2020. "Performance analysis and optimisation of new strategies for the setup of a multihead weighing process," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 14(1), pages 58-84.
    5. Alexander Pulido-Rojano & J. Carlos García-Díaz, 2020. "Optimisation algorithms for improvement of a multihead weighing process," International Journal of Productivity and Quality Management, Inderscience Enterprises Ltd, vol. 29(1), pages 109-125.
    6. Gao, Chao & Lu, Guanzhou & Yao, Xin & Li, Jinlong, 2017. "An iterative pseudo-gap enumeration approach for the Multidimensional Multiple-choice Knapsack Problem," European Journal of Operational Research, Elsevier, vol. 260(1), pages 1-11.
    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. Barbati, Maria & Greco, Salvatore & Kadziński, Miłosz & Słowiński, Roman, 2018. "Optimization of multiple satisfaction levels in portfolio decision analysis," Omega, Elsevier, vol. 78(C), pages 192-204.
    2. Jaeyoung Yang & Yong-Hyuk Kim & Yourim Yoon, 2022. "A Memetic Algorithm with a Novel Repair Heuristic for the Multiple-Choice Multidimensional Knapsack Problem," Mathematics, MDPI, vol. 10(4), pages 1-15, February.
    3. del Castillo, Enrique & Beretta, Alessia & Semeraro, Quirico, 2017. "Optimal setup of a multihead weighing machine," European Journal of Operational Research, Elsevier, vol. 259(1), pages 384-393.
    4. Lai, Xiangjing & Hao, Jin-Kao & Yue, Dong, 2019. "Two-stage solution-based tabu search for the multidemand multidimensional knapsack problem," European Journal of Operational Research, Elsevier, vol. 274(1), pages 35-48.
    5. Diallo, Claver & Venkatadri, Uday & Khatab, Abdelhakim & Liu, Zhuojun, 2018. "Optimal selective maintenance decisions for large serial k-out-of-n: G systems under imperfect maintenance," Reliability Engineering and System Safety, Elsevier, vol. 175(C), pages 234-245.
    6. Lamanna, Leonardo & Mansini, Renata & Zanotti, Roberto, 2022. "A two-phase kernel search variant for the multidimensional multiple-choice knapsack problem," European Journal of Operational Research, Elsevier, vol. 297(1), pages 53-65.
    7. Caserta, Marco & Voß, Stefan, 2019. "The robust multiple-choice multidimensional knapsack problem," Omega, Elsevier, vol. 86(C), pages 16-27.

    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:gam:jmathe:v:9:y:2021:i:9:p:1039-:d:548498. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.