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Optimal split-plot order-of-addition designs.

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Title: Optimal split-plot order-of-addition designs.
Authors: Lin, Chang-Yun1 (AUTHOR) chlin6@nchu.edu.tw, Yang, Po2 (AUTHOR)
Source: Quality Engineering. 2026, Vol. 38 Issue 3, p481-495. 15p.
Subjects: Experimental design, Optimization algorithms, Statistical power analysis, Pharmaceutical chemistry, Factorial experiment designs
Abstract: This study presents a comprehensive framework for designing and evaluating split-plot order-of-addition (SP-OofA) experiments. The proposed method aims to develop D-optimal SP-OofA designs to maximize the efficiency of estimating both whole-plot and subplot effects. We introduce a systematic algorithm that incorporates a point-exchange method to iteratively refine the design, ultimately identifying the D-optimal design. Through an example in pharmaceutical formulation, the D-optimal SP-OofA design achieved an improvement of nearly 50% in D-efficiency compared to the original design. A simulation study further demonstrates the superiority of D-optimal SP-OofA designs in terms of statistical power and design efficiency. This research contributes to the methodology of OofA experiments with split-plot structures, providing a practical solution for high-efficiency experimental design in fields, such as pharmaceuticals, material science, and manufacturing. [ABSTRACT FROM AUTHOR]
Copyright of Quality Engineering is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
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AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Optimal split-plot order-of-addition designs.
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  Data: <searchLink fieldCode="AR" term="%22Lin%2C+Chang-Yun%22">Lin, Chang-Yun</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> chlin6@nchu.edu.tw</i><br /><searchLink fieldCode="AR" term="%22Yang%2C+Po%22">Yang, Po</searchLink><relatesTo>2</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Quality+Engineering%22">Quality Engineering</searchLink>. 2026, Vol. 38 Issue 3, p481-495. 15p.
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  Data: <searchLink fieldCode="DE" term="%22Experimental+design%22">Experimental design</searchLink><br /><searchLink fieldCode="DE" term="%22Optimization+algorithms%22">Optimization algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+power+analysis%22">Statistical power analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Pharmaceutical+chemistry%22">Pharmaceutical chemistry</searchLink><br /><searchLink fieldCode="DE" term="%22Factorial+experiment+designs%22">Factorial experiment designs</searchLink>
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  Label: Abstract
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  Data: This study presents a comprehensive framework for designing and evaluating split-plot order-of-addition (SP-OofA) experiments. The proposed method aims to develop D-optimal SP-OofA designs to maximize the efficiency of estimating both whole-plot and subplot effects. We introduce a systematic algorithm that incorporates a point-exchange method to iteratively refine the design, ultimately identifying the D-optimal design. Through an example in pharmaceutical formulation, the D-optimal SP-OofA design achieved an improvement of nearly 50% in D-efficiency compared to the original design. A simulation study further demonstrates the superiority of D-optimal SP-OofA designs in terms of statistical power and design efficiency. This research contributes to the methodology of OofA experiments with split-plot structures, providing a practical solution for high-efficiency experimental design in fields, such as pharmaceuticals, material science, and manufacturing. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Group: Ab
  Data: <i>Copyright of Quality Engineering is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – Type: doi
        Value: 10.1080/08982112.2026.2625210
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      – Code: eng
        Text: English
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      Pagination:
        PageCount: 15
        StartPage: 481
    Subjects:
      – SubjectFull: Experimental design
        Type: general
      – SubjectFull: Optimization algorithms
        Type: general
      – SubjectFull: Statistical power analysis
        Type: general
      – SubjectFull: Pharmaceutical chemistry
        Type: general
      – SubjectFull: Factorial experiment designs
        Type: general
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      – TitleFull: Optimal split-plot order-of-addition designs.
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            NameFull: Lin, Chang-Yun
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            NameFull: Yang, Po
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              M: 07
              Text: 2026
              Type: published
              Y: 2026
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