阅读说明：本技术 用于动态地优化工业生产过程的方法和装置 (Method and device for dynamically optimizing an industrial process ) 是由 J-G·菲舍尔 M·皮尔克 于 2019-01-14 设计创作，主要内容包括：用于动态地优化工业生产过程的方法和装置一种过程优化器装置(1),用于动态地优化包括物理生产模块(3)的生产工厂(2)的工业生产过程,所述过程优化器(1)包括看门狗部件(1A),其适于监视所述生产工厂(2)的生产模块(3)以检测所述生产工厂(2)内的配置改变；模型比较器部件(1B),其适于评估包括与所述生产工厂(2)的物理生产模块(3)相关的数字孪生数据模型(DM)的所述生产工厂(2)的生产工厂数据模型(PPDM)以自动地标识与被所述看门狗部件(1A)检测到的配置改变影响的所述生产工厂(2)的物理生产模块(3)相关的数字孪生数据模型(DM)的偏离模型元素；以及过程重新排序器部件(1C),其适于根据由所述模型比较器部件(1B)标识的偏离模型元素来执行所述生产工厂(2)的所述至少一个生产过程的动态过程优化。(Method and apparatus for dynamically optimizing an industrial production process a process optimizer apparatus (1) for dynamically optimizing an industrial production process of a production plant (2) comprising physical production modules (3), said process optimizer (1) comprising a watchdog component (1A) adapted to monitor production modules (3) of said production plant (2) to detect configuration changes within said production plant (2); a model comparator component (1B) adapted to evaluate a Production Plant Data Model (PPDM) of the production plant (2) comprising a digital twin Data Model (DM) related to a physical production module (3) of the production plant (2) to automatically identify deviating model elements of the digital twin Data Model (DM) related to the physical production module (3) of the production plant (2) affected by the configuration change detected by the watchdog component (1A); and a process re-sequencer component (1C) adapted to perform a dynamic process optimization of the at least one production process of the production plant (2) in dependence of the deviating model elements identified by the model comparator component (1B).)

1. A process optimizer device (1) for dynamically optimizing an industrial process of a production plant (2) comprising physical production modules (3), the process optimizer (1) comprising:

(a) a watchdog component (1A) adapted to monitor production modules (3) of the production plant (2) to detect configuration changes within the production plant (2);

(b) a model comparator component (1B) adapted to evaluate a Production Plant Data Model (PPDM) of the production plant (2) comprising a digital twin Data Model (DM) related to a physical production module (3) of the production plant (2) to automatically identify deviating model elements of the digital twin Data Model (DM) related to the physical production module (3) of the production plant (2) affected by the configuration change detected by the watchdog component (1A); and

(c) a process re-sequencer component (1C) adapted to perform a dynamic process optimization of said at least one production process of said production plant (2) in accordance with deviating model elements identified by said model comparator component (1B).

2. The process optimizer device according to claim 1, wherein the watchdog component (1A) of the process optimizer device (1) is connected to a communication infrastructure of the production plant (2) to detect configuration changes within the production plant (2), the configuration changes comprising hardware configuration changes and/or software configuration changes related to physical production modules (3) of the production plant (2).

3. The process optimizer device according to claim 1 or 2, wherein the watchdog component (1A) is fed with plant data of the production plant (2) via a data interface.

4. The process optimizer device according to any of the preceding claims 1 to 3, wherein the Production Plant Data Model (PPDM) comprises a digital twin Data Model (DM) of a physical production module (3) of the production plant (2) stored in a local memory (4) of the process optimizer device (1) or in a remote database (4) connected to the process optimizer device (1).

5. A process optimizer arrangement according to any of the preceding claims, wherein the Production Plant Data Model (PPDM) comprises a list of attribute values indicating the capabilities of the respective production module (3) as a twin Data Model (DM) for a physical production module (3) of the production plant (2).

6. The process optimizer apparatus of claim 5 wherein the model comparator component (1B) is implemented to perform a rule-based attribute-to-attribute comparison in a stored list of attribute values of a Production Plant Data Model (PPDM) for production modules (3) affected by a configuration change detected by the watchdog component (1A) to automatically identify deviating model elements, in particular value changes in the list of attribute values.

7. The process optimizer apparatus according to any of the preceding claims 1 to 4, wherein the Production Plant Data Model (PPDM) comprises a semantic data model representing an ontology comprising a digital twin Data Model (DM) characterizing the capabilities of the physical production modules (3) and the dependencies between the physical production modules (3) of the production plant (2).

8. The process optimizer device according to any one of the preceding claims 1 to 7, wherein the process re-sequencer component (1C) is adapted to determine whether the deviating model element identified by the model comparator component (1B) has an influence or meaning on the production process sequence of production Process Steps (PS) performed by the production modules (3) of the production plant (2) and to provide, if an influence has been identified, a dynamic re-sequencing of the production process sequence performed by the production modules (3) of the production plant (2) based on a predefined set of relationships specifying dependencies between the production Process Steps (PS) of the production process and the physical production modules (3).

9. The process optimizer device according to any of the preceding claims 1 to 8, wherein the production Process Steps (PS) of the production process sequence are stored in an ERP database (5).

10. The process optimizer device according to any one of the preceding claims 1 to 9, wherein the process optimizer device (1) is adapted to perform an automatic optimization of an industrial process of the production plant (2) during a runtime of the production plant (2) and/or during a simulation session in which the industrial process of the production plant (2) is simulated based on real-time data received by the watchdog component (1A) of a process optimizer device (1) monitoring a production module (3) of the production plant (2).

11. The process optimizer device according to any one of the preceding claims 1 to 10, wherein the production modules (3) of the production plant (2) comprise transport production modules, in particular robotic arms and/or conveyor belts, which are adapted to transport workpieces between predefined locations to perform associated production process steps.

12. The process optimizer device according to any of the preceding claims 1 to 11, wherein the digital twin Data Model (DM) of a physical production module (3) is automatically updated when the corresponding physical production module (3) is upgraded.

13. The process optimizer device according to any of the preceding claims 1 to 12, wherein the process optimizer device (1) is implemented on a local server of the production plant (2) or on a remote server connected to a communication infrastructure of the production plant (2).

14. A production plant (2) comprising:

a plurality of production modules (3) adapted to perform production process steps of a production process, an

The process optimizer device (1) according to any of the preceding claims 1 to 13.

15. A method for dynamically optimizing an industrial process of a production plant (2) comprising physical production modules (3),

the method comprises the following steps:

(a) monitoring (S1) production modules (3) of the production plant (2) to detect configuration changes within the production plant (2);

(b) evaluating (S2) a Production Plant Data Model (PPDM) of the production plant (2) comprising a digital twin Data Model (DM) related to a physical production module (3) of the production plant (2) to automatically identify deviating model elements of the digital twin Data Model (DM) related to a physical production module (3) of the production plant (2) affected by the detected configuration change; and

(c) performing (S3) a dynamic process optimization of at least one production process of the production plant (2) in accordance with the identified deviating model elements.