TY - JOUR AU - Rossella, Berni AU - Piattoli, Lorenzo AU - Anderson-Cook, Christine Michaela AU - Lu, Lu PY - 2022/07/28 Y2 - 2024/03/29 TI - Split-plot designs and multi-response process optimization: a comparison between two approaches JF - Statistica Applicata - Italian Journal of Applied Statistics JA - sa-ijas VL - 34 IS - 1 SE - Latest articles DO - 10.26398/IJAS.0034-004 UR - https://www.sa-ijas.org/ojs/index.php/sa-ijas/article/view/148 SP - 97-118 AB - <p>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.</p> ER -