Kriging and expected improvement combined to an industrial context - Prediction of new geometries increasing the efficiency of fans
Journal de la société française de statistique, Volume 162 (2021) no. 1, pp. 22-45.

This study has been done in cooperation with the automotive supplier Valeo. In automotive industry, client needs evolve quickly in a competitiveness context, particularly, regarding the fan involved in the engine cooling module. The practitioners are asked to propose “optimal” new fans in short times. Unfortunately, each evaluation of the underlying computer code may be expensive whence the need of approximated models and specific, parsimonious, and efficient global optimization strategies. In this paper, we propose to use the Kriging interpolation combined with the expected improvement algorithm to provide new fan designs with high performances in terms of efficiency. As far as we know, such a use of Kriging interpolation together with the expected improvement methodology is unique in an industrial context and provide really promising results.

Cette étude résulte d’une collaboration avec Valeo, partenaire industriel. Dans l’industrie automobile, les besoins du marché évoluent très rapidement dans un contexte où la concurrence est forte et tout particulièrement concernant les systèmes de ventilation qui jouent un rôle clef dans le système de refroidissement du moteur. Les ingénieurs doivent dans ce contexte proposer des géométries de pales “optimales” dans des délais très courts. Malheureusement, les codes numériques sont coûteux à évaluer et des méthodes d’approximations et des techniques d’optimisation spécifiques doivent être developpées. Nous proposons de combiner l’interpolation par krigeage et l’algorithme d’optimisation d’amélioration attendue pour déterminer des géométries de pales ayant de bonnes performances en termes de rendement. Une telle application industrielle basée sur le krigeage et l’amélioration attendue semble inédite et fournit d’excellents résultats.

Classification: 35L05, 35L70
Keywords: Kriging, expected improvement, optimization
Mot clés : Krigeage, amélioration attendue, optimisation
Lagnoux, Agnès 1; Nguyen, Thi Mong Ngoc 2; Demory, Bruno 3; Henner, Manuel 3

1 Institut de Mathématiques de Toulouse; UMR5219. Université de Toulouse; CNRS. UT2J, F-31058 Toulouse, France.
2 Faculty of Mathematics & Computer Science, University of Science, VNU-HCMC, Ho Chi Minh City, Viet Nam. Vietnam National University, Ho Chi Minh City, Viet Nam.
3 Valeo. 8, rue Louis Lormand CS 80517 La Verrière, France.
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     title = {Kriging and expected improvement combined to an industrial context - {Prediction} of new geometries increasing the efficiency of fans},
     journal = {Journal de la soci\'et\'e fran\c{c}aise de statistique},
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Lagnoux, Agnès; Nguyen, Thi Mong Ngoc; Demory, Bruno; Henner, Manuel. Kriging and expected improvement combined to an industrial context - Prediction of new geometries increasing the efficiency of fans. Journal de la société française de statistique, Volume 162 (2021) no. 1, pp. 22-45. http://www.numdam.org/item/JSFS_2021__162_1_22_0/

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