Split-plot designs and multi-response process optimization: a comparison between two approaches

Authors

  • Berni Rossella
  • Mr
  • Dr
  • Lu Lu

DOI:

https://doi.org/10.26398/IJAS.0034-004

Keywords:

Designo of experiment, Pareto Front approach, Process Optimization

Abstract

Nowadays split-plot designs play a crucial role in the technological field, both for their flexibility when applying a robust design approach and in relation to the modelling step, by considering Mixed Response Surface models and/or the class of Generalized Linear Mixed Models-GLMMs. In this paper, a split-plot design is studied in a process optimization scenario involving several response variables, e.g., a multi-response situation, in which a comparison between two optimization methods is performed. More precisely, by considering a real case study related to the improvement of a measurement process of a Numerical-Control machine (N/C machine) to measure dental implants, the optimization is carried out with the Pareto front approach and then compared with other analytical methods also used to optimize. The final discussion considers the advantages and disadvantages (of application) for both methods.

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Published

2022-07-28

How to Cite

Rossella, B., Piattoli, L., Anderson-Cook, C. M., & Lu, L. (2022). Split-plot designs and multi-response process optimization: a comparison between two approaches. Statistica Applicata - Italian Journal of Applied Statistics, 34(1), 97–118. https://doi.org/10.26398/IJAS.0034-004

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