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    DATA DRIVEN MULTI-CRITERIA OPTIMIZA TION OF CHEMICAL FORMULATIONS
    2.
    发明申请
    DATA DRIVEN MULTI-CRITERIA OPTIMIZA TION OF CHEMICAL FORMULATIONS 审中-公开

    公开(公告)号：WO2022136161A1

    公开(公告)日：2022-06-30

    申请号：PCT/EP2021/086462

    申请日：2021-12-17

    Applicant: BASF SE ,  FRAUNHOFER-GESELLSCHAFT ZUR FÖRDERUNG DER ANGEWANDTEN FORSCHUNG E. V.

    Inventor： HAJNAL, David ,  LEHNER, Stefan ,  RESKE, Julia ,  BORTZ, Michael ,  KUEFER, Karl-Heinz ,  SUESS, Philipp

    IPC: G06Q10/06 ,  G06Q50/04

    Abstract: The present invention relates generally to the field of chemical formulations in a chemical production facility, and more particularly to providing assistance for producing a chemical formulation in a chemical production facility. In detail, the present invention relates to a computer-implemented method for providing assistance for optimizing chemical formulations, comprising: (a) receiving input data, preferably via an input unit (10), of at least one set of experimental data comprising formulation data and/or process data, key physicochemical properties of the formulation and a target product profile, TPP, comprising a minimum product requirement, (b) performing multicriterial optimization based on a computational model based on experimental data via a processing unit (20) and (c) providing optimization signal, preferably via an output unit (30), wherein the optimization signal is configured to control and/or monitor, preferably via a control unit (40), the production process of the chemical formulation

    SEQUENTIAL OPTIMIZATION PROCEDURE FOR SYSTEMS WITH DEGENERATION
    3.
    发明申请
    SEQUENTIAL OPTIMIZATION PROCEDURE FOR SYSTEMS WITH DEGENERATION 审中-公开

    公开(公告)号：WO2022136162A1

    公开(公告)日：2022-06-30

    申请号：PCT/EP2021/086465

    申请日：2021-12-17

    Applicant: BASF SE ,  FRAUNHOFER-GESELLSCHAFT ZUR FÖRDERUNG DER ANGEWANDTEN FORSCHUNG E.V.

    Inventor： HAJNAL, David ,  BORTZ, Michael ,  SUESS, Philipp ,  KUEFER, Karl-Heinz

    IPC: G06F30/20 ,  G06F111/06

    Abstract: The present invention generally relates to a system optimization procedure. In order to improve a system optimization procedure for generating a recipe profile of a chemical mixture, a method is provided that comprises the steps of: a) providing (110), via an input channel, a system model for modelling the chemical mixture, which associates a set of design parameters with a plurality of objective parameters that represent design characteristics of the chemical mixture, wherein the set of design parameters comprises a chemical mixture recipe having two or more ingredients, and the plurality of objective parameters comprises two or more physicochemical properties of the chemical mixture; b) defining (120), via the input channel, a set of primary optimization objective parameters, wherein the set of primary optimization objective parameters comprises one or more essential physicochemical properties of the chemical mixture; c) performing (130), by a processor, a multi-objective optimizing process on the system model by exploring a plurality of design configurations by assigning specified values to the set of design parameters, such that the set of primary optimization objective parameters meets a specified system requirement and a design goal over a set of defined constrains, by which the range of at least one of the design parameters is limited; d) determining (140), by the processor, if the multi-objective optimizing process yields a degenerated multi-objective optimal design; e) if it is determined that the multi-objective optimizing process yields a degenerated multi-objective optimal design, performing (150), by the processor, a further multi-objective optimizing process on the system model using the set of primary optimization objective parameters and at least one secondary optimization objective parameter to provide a multi-objective optimal design, wherein the at least one secondary optimization objective parameter comprises one or more optional physicochemical properties of the chemical mixture; and f) providing (160), via an output channel, the multi-objective optimal design that comprises a recipe profile preferably usable for production of the chemical mixture.

    AUTOMATED MULTI-OBJECTIVE OPTIMIZATION OF MATERIALS
    4.
    发明申请
    AUTOMATED MULTI-OBJECTIVE OPTIMIZATION OF MATERIALS 审中-公开

    公开(公告)号：WO2023017165A1

    公开(公告)日：2023-02-16

    申请号：PCT/EP2022/072702

    申请日：2022-08-12

    Applicant: BASF SE

    Inventor： SCHULTZE, Hergen ,  HAJNAL, David ,  WEISS, Horst ,  JELICH, Holger Kai Peter ,  NIEMEIER, Lukas ,  DIAZ, Jorge Samuel

    IPC: G05B19/418 ,  G05B13/04

    Abstract: The present disclosure generally relates to a computer-implemented method (100) for generating operation conditions usable to control a manufacturing or development process, the method comprising the steps of: a) providing (110), via an input channel, a set of operation conditions, a set of associated measured objective properties that represent characteristics of a system, and a set of parameterized system models; b) performing (120), by a processor, a parameter identification process for each parameterized system model of the set of parameterized system models; c) determining (130), by the processor, if at least one parameterized system model of the set of parameterized system models yields a prediction quality above a predefined value, if it is determined that the at least one parameterized system model of the set of parameterized system models yields the prediction quality above the predefined value, identifying (140) the at least one parameterized system model with the highest prediction quality d) performing (150), by a processor, a multi-objective optimizing process on the identified at least one parameterized system model; e) providing (160), via an output channel, a control file usable for the manufacturing or the development process including operation conditions obtained by the multi-objective optimizing process on the identified system model; and if it is determined that the at least one parameterized system model of the set of parameterized system models yields the prediction quality below the predefined value, identifying (170) the at least one parameterized system model with the highest prediction quality; d1) determining (180), specifically calculating, an experimental design usable to control the manufacturing or the development process based on the prediction quality of the identified system model; e1) providing (190), via an output channel, the determined experimental design.

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