# US 2025/0155853 A1 · Method and Device for Parameterizing a Production Process > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2025/0155853 A1 - Document ID: US20250155853A1 - Status: Published application - Kind: A1 - Application number: 18/833,345 - Filed: 2023-01-23 - Published: 2025-05-15 - Earliest claimed: 2022-01-28 - Assignees: Robert Bosch GmbH - Applicants: Robert Bosch GmbH - Inventors: Simon Baeuerle; Damir Shakirov; Andreas Steimer - Web page: https://patentgrep.com/patent/US20250155853A1 ## CPC - G05B 13/042: {in which a parameter or coefficient is automatically adjusted to optimise the performance} - G05B 19/41875: {characterised by quality surveillance of production} - G05B 13/027: {using neural networks only} - G05B 13/041: {in which a variable is automatically adjusted to optimise the performance} - G05B 2219/32194: Quality prediction - G05B: CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS (systems for controlling or regulating non-electric variables G05D; systems for regulating electric or magnetic variables G05F; control devices or systems insofar as characterised by mechanical features only G05G) ## Abstract A method is for providing a process parameter model for parameterizing one or more process steps of a production process for manufacturing a component includes providing a quality model for determining a quality. The quality model is configured to specify the quality of the resulting component directly or with the aid of a predefined quality function based on one or more predefined measurement variables and/or one or more predefined state variables, which each specify a property of a pre-product or intermediate product of the component being manufactured and/or a production device for performing a process step and/or at least one environmental condition, and based on one or more process parameters which control a corresponding one of the process steps. The method further includes training a data-based process parameter model to output one or more process parameters based on one or more measurement variables captured by a sensor. ## Claims ### Claim 1 A computer-implemented method for providing a process parameter model for parameterizing one or more process steps of a production process for manufacturing a component, the method comprising: providing a quality model for determining a quality, the quality model configured to specify the quality of the resulting component directly or with the aid of a predefined quality function based on one or more predefined measurement variables (M) and/or one or more predefined state variables, which each specify a property of a pre-product or intermediate product of the component being manufactured and/or a production device for performing a process step and/or at least one environmental condition, and based on one or more process parameters which control a corresponding one of the process steps; training a data-based process parameter model to output one or more process parameters based on one or more measurement variables captured by a sensor and/or one or more predefined state variables by optimizing the quality. ### Claim 2 (depends on 1) The method according to claim 1, wherein the process parameters comprise a constant control variable for a process step, a time course of a control variable for a process step, a control parameter of a control for a process step, and/or a target manipulated variable for control for a process step. ### Claim 3 (depends on 1) The method according to claim 1, wherein: the quality model comprises a physical model, a heuristic or data-based model and is configured to evaluate properties of the manufactured component and/or costs of the production process based on an initial situation, which is specified by the at least one measurement variable and/or the at least one state variable and the at least one process parameter, which characterizes the performance of the production process, to evaluate properties of the manufactured component and/or costs of the production process, and the quality is determined with the aid of the quality function with respect to the properties of the manufactured component and/or the costs of the production process. ### Claim 4 (depends on 1) The method according to claim 1, wherein: the quality model comprises a data-based model, training datasets are determined to train the quality model, the training datasets are determined by training data points, which are determined by varying values of the one or more measurement variables and/or one or more state variables and varying values of the process parameters within respectively predefined allowable value ranges, with respectively assigned qualities as labels, the qualities resulting in each case from at least one property of the manufactured component and/or costs of the production process with the aid of the quality function, and the quality model is trained with the training datasets. ### Claim 5 (depends on 1) The method according to claim 1, wherein: the quality model comprises a data-based model, training datasets are determined to train the quality model, the training datasets are determined by training data points, which are determined by varying values of the one or more measurement variables and/or one or more state variables and varying values of the process parameters within respectively predefined allowable value ranges, each assigned with at least one property of the manufactured component and/or costs of the production process as labels, from which the quality can be determined with the aid of the quality function, and the quality model is trained with the training datasets. ### Claim 6 (depends on 3) The method according to claim 3, wherein: the properties of the manufactured component have geometric dimensions along with dimensional tolerances, a surface quality of the manufactured component, an electrical property of the manufactured component and a robustness of the manufactured component, and the cost of the production process includes wear of a tool, a duration of the production process, comprises an energy expenditure of the production process and a material expenditure. ### Claim 7 (depends on 1) The method according to claim 1, wherein training data points are used by varying the one or more measurement variables and/or the one or more predefined state variables within their respective value ranges to train the data-based process parameter model based on a loss function which is determined by the quality resulting from the application of the quality model. ### Claim 8 (depends on 1) The method according to claim 1, wherein the process parameter model is used prior to production of a component in order to parameterize the one or more process steps, based on at least one measurement variable of a property captured by a sensor or state of one or more pre-products, a property or state of one or more production devices for the one or more process steps and/or one or more environmental conditions with the aid of the trained process parameter model. ### Claim 9 (depends on 1) A device for performing the method according to claim 1. ### Claim 10 (depends on 1) The method according to claim 1, wherein a computer program product comprises instructions which, when the computer program product is executed by at least one data processing device, cause the data processing device to perform the method. ### Claim 11 (depends on 1) A non-transitory machine-readable storage medium comprising instructions which, when executed by at least one data processing device, cause the data processing device to perform the method according to claim 1.