BELNA, Maëllis; NDIAYE, Amadou; TAILLANDIER, Franck; AGABRIEL, Louis; MARIE, Anne-Laure; GÉSAN-GUIZIOU, Geneviève

doi:10.1016/j.fbp.2020.09.002

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http://creativecommons.org/licenses/by-nc-nd/

BELNA, Maëllis
Science et Technologie du Lait et de l'Oeuf [STLO]
Institut de Mécanique et d'Ingénierie [I2M]
Société Boccard

NDIAYE, Amadou
Institut de Mécanique et d'Ingénierie [I2M]

TAILLANDIER, Franck
Risques, Ecosystèmes, Vulnérabilité, Environnement, Résilience [RECOVER]

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Food and Bioproducts Processing. 2020-09-14, vol. 124, p. 244-257

Elsevier

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Optimizing 0.1 m microfiltration (MF) of skim milk requires formulating optimization of afood processing problem with conflicting objectives that consider product composition, pro-cess variables and operating conditions. Formulating the MF optimization problem requiresknowledge from experts about food processing, dairy product production and equipmentmanufacturing. This study formulated the MF optimization problem in an innovative man-ner: as a multiobjective optimization problem that considered the entire MF process. Elevenexperts were interviewed to identify the knowledge domains necessary, which required 36interviews over a total of 14 h. Formulation was achieved from the MF process to the com-positions of the permeate and retentate fractions. Five conflicting optimization objectives,influenced by 36 variables, were set up to formulate the problem. Five of the variables weredecision variables used to control the MF, and the other 31 were intermediate calculationvariables. This approach opens new perspectives for optimization of food processes thatintegrate expert knowledge< Leer menos

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Knowledge acquisition

Expert knowledge

Knowledge representation

Causal maps

Protein fractionation

Dairy sectora

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Formulating multiobjective optimization of 0.1 μm microfiltration of skim milk

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