IDEAS home Printed from https://ideas.repec.org/a/taf/japsta/v44y2017i3p493-510.html
   My bibliography  Save this article

Split-plot designs for multistage experimentation

Author

Listed:
  • Murat Kulahci
  • John Tyssedal

Abstract

Most of today’s complex systems and processes involve several stages through which input or the raw material has to go before the final product is obtained. Also in many cases factors at different stages interact. Therefore, a holistic approach for experimentation that considers all stages at the same time will be more efficient. However, there have been only a few attempts in the literature to provide an adequate and easy-to-use approach for this problem. In this paper, we present a novel methodology for constructing two-level split-plot and multistage experiments. The methodology is based on the Kronecker product representation of orthogonal designs and can be used for any number of stages, for various numbers of subplots and for different number of subplots for each stage. The procedure is demonstrated on both regular and nonregular designs and provides the maximum number of factors that can be accommodated in each stage. Furthermore, split-plot designs for multistage experiments with good projective properties are also provided.

Suggested Citation

  • Murat Kulahci & John Tyssedal, 2017. "Split-plot designs for multistage experimentation," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(3), pages 493-510, February.
    • Handle: RePEc:taf:japsta:v:44:y:2017:i:3:p:493-510
    DOI: 10.1080/02664763.2016.1177497
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/02664763.2016.1177497
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/02664763.2016.1177497?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. S. E. Michaels, 1964. "The Usefulness of Experimental Designs," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 13(3), pages 221-228, November.
    2. Bradley Jones & Peter Goos, 2009. "D-optimal design of split-split-plot experiments," Biometrika, Biometrika Trust, vol. 96(1), pages 67-82.
    3. D. R. Bingham & E. D. Schoen & R. R. Sitter, 2004. "Designing fractional factorial split‐plot experiments with few whole‐plot factors," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 53(2), pages 325-339, April.
    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. ARNOUTS, Heidi & GOOS, Peter, 2013. "Staggered-level designs for response surface modeling," Working Papers 2013027, University of Antwerp, Faculty of Business and Economics.
    2. Palhazi Cuervo, Daniel & Goos, Peter & Sörensen, Kenneth, 2017. "An algorithmic framework for generating optimal two-stratum experimental designs," Computational Statistics & Data Analysis, Elsevier, vol. 115(C), pages 224-249.
    3. K. Chatterjee & C. Koukouvinos, 2021. "Construction of mixed-level supersaturated split-plot designs," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 84(7), pages 949-967, October.
    4. Smucker, Byran J. & Castillo, Enrique del & Rosenberger, James L., 2012. "Model-robust designs for split-plot experiments," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 4111-4121.
    5. ARNOUTS, Heidi & GOOS, Peter, 2009. "Design and analysis of industrial strip-plot experiments," Working Papers 2009007, University of Antwerp, Faculty of Business and Economics.
    6. Fundin, Anders & Bergquist, Bjarne & Eriksson, Henrik & Gremyr, Ida, 2018. "Challenges and propositions for research in quality management," International Journal of Production Economics, Elsevier, vol. 199(C), pages 125-137.
    7. Yang, Jianfeng & Zhang, Runchu & Liu, Minqian, 2007. "Construction of fractional factorial split-plot designs with weak minimum aberration," Statistics & Probability Letters, Elsevier, vol. 77(15), pages 1567-1573, September.
    8. Minyang Hu & Shengli Zhao, 2022. "Minimum Aberration Split-Plot Designs Focusing on the Whole Plot Factors," Mathematics, MDPI, vol. 10(5), pages 1-12, February.
    9. ARNOUTS, Heidi & GOOS, Peter, 2008. "Staggered designs for experiments with more than one hard-to-change factor," Working Papers 2008018, University of Antwerp, Faculty of Business and Economics.
    10. Loeza-Serrano, S. & Donev, A.N., 2014. "Construction of experimental designs for estimating variance components," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 1168-1177.
    11. Lin, Chang-Yun & Yang, Po, 2019. "Data-driven multistratum designs with the generalized Bayesian D-D criterion for highly uncertain models," Computational Statistics & Data Analysis, Elsevier, vol. 138(C), pages 222-238.
    12. Bradley Jones & Peter Goos, 2009. "D-optimal design of split-split-plot experiments," Biometrika, Biometrika Trust, vol. 96(1), pages 67-82.
    13. K. Chatterjee & C. Koukouvinos & K. Mylona, 2020. "Construction of supersaturated split-plot designs," Statistical Papers, Springer, vol. 61(5), pages 2203-2219, October.
    14. Steven G. Gilmour & Peter Goos, 2009. "Analysis of data from non‐orthogonal multistratum designs in industrial experiments," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 58(4), pages 467-484, September.
    15. Borrotti, Matteo & Sambo, Francesco & Mylona, Kalliopi, 2023. "Multi-objective optimisation of split-plot designs," Econometrics and Statistics, Elsevier, vol. 28(C), pages 163-172.
    16. Xiaodong Li & Xu He & Yuanzhen He & Hui Zhang & Zhong Zhang & Dennis K. J. Lin, 2017. "The Design and Analysis for the Icing Wind Tunnel Experiment of a New Deicing Coating," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(520), pages 1417-1429, October.
    17. SCHOEN, Eric D. & JONES, Bradley & GOOS, Peter, 2010. "Split-plot experiments with factor-dependent whole-plot sizes," Working Papers 2010001, University of Antwerp, Faculty of Business and Economics.

    More about this item

    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:taf:japsta:v:44:y:2017:i:3:p:493-510. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/CJAS20 .

    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.