Production Control System

Abstract

A production control system for a matrix cell production plant (1) having an arrangement of matrix cells (2), each of which is configured to execute production processes, having logistics means which are configured to execute logistics processes and having a superordinate control logic (4) which is configured to control the matrix cells (2) and the logistics means. Proprietary data models of the matrix cells (2) and logistics means are linked via at least one ontology unit, thereby providing a continuous data flow between the matrix cells (2) and the logistics means. In dependence on the data in the data stream, production processes are automatically definable and executable in the individual matrix cells (2). Logistics processes are automatically definable and executable in individual logistics means.

Claims

1. A production control system for a matrix cell production plant (1), having an arrangement of matrix cells (2), each of which is configured to execute production processes, having logistics means, which are configured to execute logistics processes, and having a superordinate control logic (4), which is configured to control the matrix cells (2) and the logistics means, characterized in that proprietary data models of the matrix cells (2) and logistics means are linked via at least one ontology unit, as a result of which a continuous data stream is obtained between the matrix cells and the logistics means, and in that, in dependence on data of the data stream, production processes are automatically definable and executable in individual matrix cells (2) and/or logistics processes are automatically definable and executable in individual logistics means.

2. The production control system according to claim 1, characterized in that the superordinate control logic (4) is configured to define production specifications, and in that, in dependence on these, production processes are automatically generated in the matrix cells (2) and/or logistics processes are automatically generated in the logistics means.

3. The production control system according to claim 2, characterized in that the superordinate control logic (4) is configured to monitor compliance with the production specifications.

4. The production control system according to claim 1, characterized in that the automatic generation of production processes in the matrix cells (2) and/or logistics processes in the logistics means is carried out in dependence on process and resource availabilities of matrix cells (2) and/or logistics means.

5. The production control system according to claim 4, characterized in that periods of process and resource availabilities are taken into account.

6. The production control system according to claim 1, characterized in that the automatic generation of production processes in the matrix cell (2) and/or logistics processes in the logistics means is carried out in dependence on production costs.

7. The production control system according to claim 1, characterized in that the logistic means are formed by autonomous driving vehicles (3).

8. The production control system according to claim 7, characterized in that a selection of matrix cells (2) to be approached is specifiable as a logistics process automatically generated in an autonomous driving vehicle (3).

9. The production control system according to claim 7, characterized in that a sequence of matrix cells (2) to be approached is specifiable as a logistics process automatically generated in an autonomous driving vehicle (3).

10. The production control system according to claim 1, characterized in that matrix cells (2) are configured for the production of parts.

11. The production control system according to claim 7, characterized in that the production of spare parts is provided as a production process automatically generated in a matrix cell (2).

12. The production control system according to claim 1, characterized in that automatically generatable production processes and/or logistics processes are definable by means of simulation methods.

13. The production control system according to claim 12, characterized in that the utilization rates of matrix cells (2) and logistics means are optimizable by means of the simulation methods.

14. The production control system according to claim 1, characterized in that the matrix cell production plant (1) is integrated into a cloud computer network.

15. A method for controlling a matrix cell production plant (1), having an arrangement of matrix cells (2), each of which is configured to execute production processes, having logistics means, which are configured to execute logistics processes, and having a superordinate control logic (4), which is configured to control the matrix cell (2) and the logistics means, characterized in that proprietary data models of the matrix cells (2) and logistics means are linked via at least one ontology unit, as a result of which a continuous data stream is obtained between the matrix cells (2) and the logistics means, and in that, in dependence on data of the data stream, production processes are automatically definable and executable in individual matrix cells (2) and/or logistics processes are automatically definable and executable in individual logistics means.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The invention is explained below on the basis of the drawings. The drawings show:

[0044] FIG. 1: A schematic representation of an embodiment example of the matrix cell production plant according to the invention.

[0045] FIG. 2: A block diagram of a production control system for the matrix cell production plant as shown in FIG. 1.

[0046] FIG. 3: An embodiment example for the automatic generation of logistic processes of logistic means configured as an autonomous driving vehicle.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0047] FIG. 1 schematically shows the structure of a matrix cell production plant 1, which may be installed in a factory, for example. In general, the matrix cell production plant 1 may also be distributed over several locations, where these may be used in particular for the production of motor vehicles.

[0048] The matrix cell production plant 1 features a multiple arrangement of individual matrix cells 2, which on the basis of their specific configuration are configured to execute different production processes. In this context, the term production process generally includes machining processes of parts, assembly processes, but also positioning or provisioning processes. Each matrix cell 2 has a computer unit that is not shown.

[0049] The matrix cell production plant 1 also has a number of logistic means that are configured to execute logistic processes. In the present case, the logistic means are formed by autonomous driving vehicles 3, preferably AGVs (automated guided vehicles). Every autonomous driving vehicle has a computer unit that is not shown.

[0050] With the autonomous driving vehicles 3 logistics processes can be executed in such a way that materials can be supplied to or collected from individual matrix cells 2.

[0051] For the sake of clarity, FIG. 1 shows only one autonomous driving vehicle 3.

[0052] For the central control of the matrix cells 2 and logistic means, a superordinate control logic 4 is provided, which is configured, for example, in the form of neural networks.

[0053] A computer system 5 on which a business management software is implemented is assigned to the superordinate control logic 4. The superordinate control logic 4 can read business data from the computer system 5 for control purposes.

[0054] All units of the matrix cell production plant 1, i.e. the superordinate control logic 4, the computer system 5, the matrix cells 2 as well as the autonomous driving vehicles 3 are coupled with each other via preferably contactless data interfaces, such that they can exchange data among each other.

[0055] FIG. 2 shows an example of a production control system for the matrix cell production plant 1 according to FIG. 1.

[0056] According to the invention, the production control system has an arrangement of ontology units by means of which proprietary data models of the manufacturer-specific matrix cells 2 and logistics means and also product facility-specific data and processes are semantically networked.

[0057] As FIG. 2 shows, a resource unit 6, a process unit 7 and a product unit 8, which are controlled by the superordinate control logic 4, are provided as ontology units. These ontology units form a virtual model of the processes carried out in the production facility.

[0058] In the individual ontology units ontology-forming object models are provided, which are linked with each other via suitable ontological links 9 and thus manage a semantic networking of proprietary data models existing in the resource unit 6, the process unit 7 and the product unit 8.

[0059] In the resource unit 6, ontologies are used to structure and digitally make available data that describe and define production processes. The data form production-specific proprietary data models, which are integrated via ontologies into a harmonized data stream that can flow across all units of the production facility.

[0060] The production sequences generally include not only production processes but also logistics processes.

[0061] In the process unit 7, specific production processes for production or work means such as robots are programmed in an executable program code (e.g. in a PLC code) in dependence on data from proprietary data models of the resource unit 6 and the product unit 8. The ontologies enable a harmonizing data stream between the process unit 7 and the resource unit 6 and the product unit 8 without having to provide interfaces for that purpose at a system level.

[0062] Product data 10 are provided and made available in the product unit 8. As FIG. 2 shows, in dependence on external, customer-specific product specifications 11 product data 10 are made available to the product unit 8 in proprietary data modules, for example as CAD data.

[0063] These product data 10 are processed and made available in the product unit 8. In particular, the product data 10 are stored permanently, preferably non-volatilely, as persistence data 12 in a working memory as unchangeable storage means.

[0064] Furthermore, using the ontologies of the product unit 8, digital models are generated from the product data 10, which are stored as so-called digital twins 13. The persistence data 12 and the digital twins 13 can be analyzed by means of an analysis unit 14.

[0065] On the whole, the resource unit 6, the process unit 7 and the product unit 8 form an ontology model with which all proprietary data models of the matrix cell production plant 1 are semantically networked, such that a standardized, harmonic data stream of all data of the overall system is achieved between all units of the matrix cell production plant 1, without the need to use physical interfaces at a system level to adapt data to be transmitted.

[0066] The resource unit 6 is used to prepare proprietary data from machine manufacturers who supply and provide work or production means such as processing machines and logistics means such as AGVs with defined functionalities.

[0067] The product unit 8 is used to prepare and provide customer-specific proprietary product data 10.

[0068] Finally, in the process unit 7 proprietary data are also generated by process designers by generating there executable program codes for production and logistics means.

[0069] The data and programs generated in the resource unit 6, the process unit 7 and the product unit 8 are fed to a validation layer 16 and a programming layer 17.

[0070] A check and validation of created program codes is performed in the validation layer 16. In particular, commissioning is carried out by checking whether the programmed processes are feasible, in particular whether they are collision-free.

[0071] After successful validation, machine codes for the production and work means are generated using the programming layer 17.

[0072] A normalization layer 18 is provided as a further component of the ontology model according to the invention. There, program code written in high-level languages is translated into application software such as PLC software.

[0073] Finally, an adapter layer 19 is provided, which establishes the connection to communication units 20 such as mail, internet and the like. In addition, the adapter layer 19 is used to establish connections with external units 21 of suppliers, partner companies and the like.

[0074] According to the invention, the standardized data stream generated with the ontologies between the individual units of the matrix cell production plant 1 is used to enable the individual matrix cells 2 to define and execute production processes automatically, and to enable the logistics means, i.e. the autonomous driving vehicles 3, to define and execute logistics processes automatically.

[0075] Appropriately, the superordinate control logic 4 is configured to define production specifications. In dependence on these, production processes are automatically generated in the matrix cells 2 and/or logistics processes are automatically generated in the logistics means.

[0076] In this context, the superordinate control logic 4 is advantageously configured to monitor compliance with the production specifications.

[0077] The automatic generation of production processes in the matrix cells 2 and/or logistics processes in the logistics means is carried out advantageously in dependence on the process and resource availabilities of matrix cells 2 and/or logistics means.

[0078] Furthermore, periods of process and resource availabilities can be taken into account.

[0079] The business management software provides business data concerning the production costs.

[0080] Such an intelligent machine behavior can be applied, for example, to matrix cells 2, which are configured for the production of parts.

[0081] The superordinate control logic 4 specifies production specifications according to which these matrix cells 2 must produce a specified number of parts at specified times, which are then needed in the production process.

[0082] However, the matrix cell 2 does not have to continuously produce parts for the production process and thus has several downtimes.

[0083] According to the invention, the matrix cell 2 automatically defines production processes in such a way that it produces spare parts that are not needed for the current production process. The execution of these production processes, i.e. the production of the spare parts, is carried out in controlled fashion locally at the matrix cell 2 during its downtimes.

[0084] FIG. 3 shows another example of intelligent machine behavior. There, an autonomous driving vehicle 3 is assigned to a series of matrix cells 2a-2f, which can carry out different production processes, for example different machining of parts or different positioning of parts.

[0085] Logistics processes can now be generated automatically in the autonomous driving vehicle 3. A logistics process consists of a specific sequence of production processes executed with all or part of the matrix cells 2a-2f. According to the defined logistics processes, the autonomous driving vehicle 3 then automatically drives to the matrix cells 2a-2f, such that the production processes can be executed there in the specified sequence.

LIST OF REFERENCE NUMERALS

[0086] (1) Matrix cell production plant [0087] (2) Matrix cell [0088] (3) Autonomous driving vehicle [0089] (4) Superordinate control logic [0090] (5) Computer system [0091] (6) Resource unit [0092] (7) Process unit [0093] (8) Product unit [0094] (9) Link [0095] (10) Product data [0096] (11) Product specification [0097] (12) Persistence data [0098] (13) Digital twin [0099] (14) Analysis unit [0100] (16) Validation layer [0101] (17) Programming layer [0102] (18) Normalization layer [0103] (19) Adapter layer [0104] (20) Communication unit [0105] (21) External unit