Computer-implemented method for use in a computer-aided production system, and production system

Abstract

The present invention relates to a computer-implemented method for use in a computer-aided production system (100), in particular for controlling an operation of a computer-aided production system (100), and to a production system (100), wherein the method comprises at least the following steps: a1) providing component data that are assigned to one or more components (101), wherein the component data contain information relating to two or more feature groups (106) that are assigned to one or more components, wherein each component in relation to which data are provided is assigned at least one feature group (106), wherein each feature group (106) comprises a group of features which at least partially define the component (101) to which the feature group (106) is assigned, and wherein each feature group (106) is assigned feature group data, a2) acquiring operating data of the production system (100) and assigning the acquired operating data of the production system (100) to at least one feature group (106), b) selecting (S2) at least one feature group (106), c) providing (S3) at least a proportion of the feature group data that are assigned to the at least one selected feature group (106), d) evaluating (S4) the provided feature group data and determining a value of at least one variable that characterizes the selected feature group (106), and e) storing, outputting and / or further processing the at least one value ascertained in step d).

Description

[0001] COMPUTER-IMPLEMENTED METHOD FOR USE IN A COMPUTER-AID PRODUCTION SYSTEM AND PRODUCTION SYSTEM

[0002] TECHNICAL FIELD

[0003] The present invention relates to a computer-implemented method for use in a computer-aided production system, in particular for controlling the operation of a computer-aided production system, wherein the production system is configured in particular for component processing. The invention further relates to a production system, a computer program, a computer-readable storage medium, and a data processing device.

[0004] BACKGROUND OF THE INVENTION

[0005] Computer-aided or computer-assisted production systems, in particular for component processing and / or manufacturing, are generally known from the prior art. In particular, CAx-supported systems are known (Computer-Aided x-systems), where the "X" stands for various workstations or process stages within production. In particular, for example, computer-aided or computer-assisted systems are known which comprise at least one CAD station (Computer-Aided Design), i.e., computer-aided construction, one CAM station (Computer-Aided Manufacturing), i.e., computer-aided production, and / or one CAQ station (Computer-Aided Quality), i.e., computer-aided quality assurance / testing. In addition, CAE (Computer-Aided Engineering), i.e., computer-aided development, CAP (Computer-Aided Planning), i.e., computer-aided work planning, CNC (Computerized Numerical Control), i.e.,computer-controlled manufacturing, computer-aided production planning and control (PPS) and computer-aided production data acquisition (BDE) are known.

[0006] Computer-aided or computer-supported production systems that feature one or more of the aforementioned computer-supported stations are generally referred to as CIM production systems, i.e., so-called Computer-Integrated Manufacturing production systems. According to https: / / de.wikipedia.org / wiki / Computer-integrated_manufacturing, last accessed on October 3, 2022, "CIM," as defined by the AWF (Committee for Economical Manufacturing, 1985), describes the integrated use of IT in all operational areas related to production and encompasses the information technology interaction between CAD, CAP, CAM, CAQ, and PPS. The aim here is to achieve the integration of the technical and organizational functions for product creation.

[0007] Computer-aided or computer-supported production systems, in particular so-called CIM production systems, as well as corresponding methods for use in these, in particular for the operation and control of such production systems, are generally known from the prior art.

[0008] An overview of this can be found, for example, in A. Agovic, T. Trautner, F. Bleicher, Digital Transformation - Implementation of Drawingless Manufacturing: A Case Study, Procedia CIRP, Volume 107, 2022, Pages 1479-1484, ISSN 2212-8271, https: / / doi.Org / 10.1016 / j.procir.2022.05.178.

[0009] Furthermore, for example, from WO 2020 / 204915 A1, a design and manufacturing system is known which comprises a multi-axis machine tool with a cutting head that can carry a plurality of available tools and a part holder, wherein the cutting head and / or the part holder are fully controllable in at least two axes, with a design system operable using a computer to generate a 3D model of a part to be manufactured, and with a machine learning model operable using the computer to analyze the part to be manufactured to identify features and develop a manufacturing plan based at least partially on the multi-axis machine tool and the plurality of available tools, wherein the manufacturing plan includes a tool type used for each feature,contains a feed rate for each tool type for each feature and a tool speed for each tool type for each feature.

[0010] WO 2019 / 226167 A1 further discloses a method for CAD operations and corresponding systems and computer-readable media. A method comprises receiving 3D solid model data of a part to be manufactured, receiving at least one rule from a rule database, applying the rule to the 3D solid model data using a rule engine, and generating an output according to the rule applied to the 3D solid model data. The rule may include an extraction section that identifies elements or features of the 3D solid model data, a logic section that applies a condition to the identified elements or features, and an action section that defines an action to be performed on identified elements or features that satisfy the condition.The output may include an annotation of product manufacturing information about elements or features of the 3D solid model data that match the rule.

[0011] WO 2018 / 083512 A1 discloses systems and a process for providing a machining method for manufacturing a feature of a part by receiving data from a set of features, wherein all feature data describe a feature to be manufactured and include a type of the feature and a set of attributes of the feature. Each machining method is assigned a set of ranking values ​​to rank machining methods applicable to the same range of feature attributes. Data of an additional feature to be manufactured is received, wherein the type of the additional feature is the predetermined type and the set of attributes of the additional feature is a specific set of attributes.At least one machining process of the selected processes is provided based on its assigned rank value to be assigned to the additional feature as a machining process for producing the additional feature.

[0012] WO 2016 / 178107 A1 describes a method for identifying geometric clones in a modeling system or for simulating design changes of a multi-part product, and corresponding data processing systems and computer-readable media. The described method comprises selecting a template of a geometric shape and generating and storing an image of the template, identifying a candidate geometric shape in the system, and exploring the identified candidate geometric shape from a starting point until returning to the starting point or reaching a junction. The method comprises generating a map of the examined candidate geometric shape, comparing the map of the examined candidate geometric shape with the map of the template, and marking the candidate geometric shape as a clone if it matches a predefined portion of the template.The use of features in production systems is also generally described in the VDI guideline VDI 2218, “Information processing in product development - Feature technology”, March 2003.

[0013] The objectives to be achieved with such processes and production systems are generally to achieve a higher degree of automation, reduce the error rate, avoid method, media and / or system discontinuities, improve process reliability, reduce data redundancy, improve data consistency, timeliness and quality, increase the standardization rate, increase audit security or improve version control of the data, reduce costs, increase transparency regarding costs and required capacities, and / or generally optimize the production system and its operation.

[0014] SUMMARY OF THE INVENTION

[0015] Against this background, it is an object of the present invention to provide an alternative method for use in a production system, ie for a production system, wherein it is a particular object of the present invention to provide an improved method which in particular enables improved operation of a production system, preferably optimized operation of a production system, in particular improved control of a production system.

[0016] Furthermore, it is an object of the present invention to provide an alternative production system, in particular an improved production system, which in particular enables improved operation, preferably optimized operation, in particular improved control.

[0017] Furthermore, it is an object of the present invention to provide an alternative, in particular improved, computer program, an alternative, in particular improved, computer-readable storage medium, and an alternative, in particular improved, data processing device, each of which in particular enables the provision of an alternative, in particular improved, production system. This object is achieved according to the invention by a method according to the invention, by a production system according to the invention, by a computer program according to the invention, by a storage medium according to the invention, and by a data processing device according to the invention having the features according to the respective independent patent claims. Advantageous embodiments of the invention are the subject of the dependent patent claims, the description, and the figures. The wording of the claims is incorporated into the content of the description by express reference.

[0018] A computer-implemented method according to the present invention can be designed in particular for use in a computer-aided production system, i.e., for a computer-aided production system, in particular for application in a production system. The production system is configured in particular for component processing, i.e., for the manufacture and / or processing of components. The method can in particular comprise one or more of the following steps: a1) Providing data, in particular component data, which can be assigned to one or more components that can preferably be manufactured and / or processed by the computer-aided production system, wherein the data can contain information on two or more feature groups that can be assigned to one or more components, wherein each component for which data is provided can be assigned at least one feature group,wherein a feature group can each comprise a group of features which can at least partially define the component to which the feature group can be assigned, and wherein feature group data can be assigned to each feature group, a2) capturing operating data of the production system and assigning the captured operating data of the production system to at least one feature group, whereby the captured operating data of the production system can become feature group data, b) selecting at least one feature group, c) providing at least a portion of the feature group data which can be assigned to the at least one selected feature group, wherein the provided feature group data preferably contains at least a portion of the operating data of the production system captured in step a2) and assigned to the feature group, d) evaluating feature group data, in particular the provided feature group data,and determining a value of at least one characteristic variable, in particular at least one variable characteristic of the feature group, and e) storing, outputting and / or further processing a determined value, in particular the at least one determined value in step d).

[0019] A "production system" in the sense of the present invention is in particular a system which is designed for processing and / or manufacturing at least one component, ie for component processing, wherein the production system does not have to be designed for the complete production or for a complete processing of the component, but only for carrying out at least one processing and / or manufacturing step within the process chain for processing and / or manufacturing the component.

[0020] A “computer-aided or computer-assisted or computer-aided production system” is in particular a production system which comprises at least one workstation which has a computer or a comparable device and / or is connected or connectable to such a device for data exchange, wherein the computer or the comparable device is in particular set up to at least partially perform a required task in the process chain of processing and / or manufacturing the component.

[0021] A production system within the meaning of the present invention has, in particular, at least one workstation, wherein a workstation within the meaning of the present invention is, in particular, a station which is designed to process at least part of the data assigned to a component.

[0022] A "workstation" within the meaning of the present invention can in particular be a production station, i.e. in particular a station with at least one machine tool. In particular, a workstation can be or comprise, for example, a cutting device, for example a milling machine, in particular a CNC milling machine, a lathe, in particular a CNC lathe, a forming machine, such as a press, or any other type of machine tool for production. A workstation can in particular be a boring machine, a machining center or a turning and milling machining center. The term "production" can in particular be understood in the sense of DIN 8580. A production station can accordingly be a station at which in particular at least one processing step of a production process according to DIN 8580 can be carried out. Iein other words, a production station is set up in particular to carry out at least one processing step of a production process, in particular a production process according to DIN 8580.

[0023] In addition to a production station, a workstation within the meaning of the present invention, particularly as part of a production system according to the invention, can also be a PPS station, i.e., a production planning and control station. In particular, a workstation can also be a work preparation station, a production program planning station, a quantity planning station, a scheduling and / or capacity planning station, an order monitoring station, an order initiation station, a design station, and / or a testing and / or measuring station.

[0024] In other words, a workstation within the meaning of the present invention can be any station at which data associated with the component are at least partially processed as part of a manufacturing and / or processing process of a component.

[0025] A workstation does not have to be designed to be able to process all of the data assigned to a component, but in the sense of the present invention it is sufficient if a workstation is designed to process only a subset of the data assigned to a component.

[0026] A workstation can, in particular, include or be a CAx station. Preferably, at least one workstation is or includes a CAD station, a CAM station, or a CAQ station, or a combination thereof.

[0027] A production system according to the present invention can in particular be a CIM production system.

[0028] A “component” within the meaning of the present invention is any workpiece, in particular any embodied workpiece, the production and / or processing of which comprises at least one physical step, in particular a physical manufacturing step.

[0029] The "processing" of data assigned to a component, ie in particular component data, means in the sense of the invention in particular at least one generation, processing, storage, reading out, recording, reading in, output, display, conversion, buffering, changing, comparing, checking, sorting, converting as well as any other data processing possibility, in particular any data processing possibility possible with the aid of a computer, in particular any electronic data processing possibility, and / or combinations thereof.

[0030] Data assigned to a component, i.e. component data, can in particular be data which define a geometry of the component (geometry data), such as dimensions, tolerances, in particular dimensional, form and position tolerances, and / or data which define one or more properties of the component (property data), such as material specifications, surface properties (roughness or the like). Component data can also be production data such as manufacturing parameters and / or specifications, such as the specification of which manufacturing process is to be used for at least one machining step of the component. Component data can also include associated machine tool data or control parameters or process parameters such as cutting speeds, feed rates, cutting depths, manufacturing aids, cutting heads, etc., and / or test and / or measurement data, which can in particular include test and / or measurement program information.

[0031] Data assigned to a component can in particular also be associated design data (e.g. FEM data such as lattice properties, number of nodes, etc.), manufacturing data (manufacturing process to be used, operating resources to be used, NC program to be used), required process parameters such as process temperatures, idle times and / or temperature profiles, and / or manufacturing process data, for example which quality controls are to be carried out after which step, order data, and / or component identification data, such as batch numbers, manufacturing time and location, etc.

[0032] Component data can also include work plan data, maturity level information, revision and / or change data, assembly information, associated equipment data, for example of suitable clamping devices or the like, as well as information on hazardous substance classes, shelf life or recycling (e.g. recycled volume / total volume) or on the CO2 balance.

[0033] Test program data can, for example, include information for a specific test or measurement. In particular, whether a component should be measured optically or tactilely, what surface finish (roughness) should be achieved, and what tolerances must be maintained.

[0034] In addition, a component, preferably one or more feature groups of the component, can be assigned or can be assigned, in particular, operating data of the production system, wherein operating data of the production system are in particular data that are or have been recorded during the operation of the production system and / or that are suitable for characterizing the operation of the production system.

[0035] Operating data that is or will be assigned to a component can, in particular, be data recorded and / or determined during the manufacture and / or processing of the component or a comparable component. Operating data is, in particular, data recorded during the operation of the production system, such as process parameters, consumption variables, error messages, throughput times, setup times, downtimes, chip sizes, tolerances, or the like. The operating data assigned to a component and / or one or more feature groups can be updated and / or supplemented continuously or periodically (cyclically or acyclically). This enables particularly effective control of the production system, in particular near-real-time adaptation of the production system (assuming a sufficient update frequency).

[0036] The operating data are preferably recorded in a step a2), which can be performed before, in parallel, and / or after step a1) and / or at least partially overlapping with it, and assigned to at least one feature group, whereby the recorded operating data of the production system become feature group data. This enables particularly advantageous operation of the production system, in particular particularly advantageous optimization and / or control of the production system.

[0037] Operating data can also be: Optical information (images / videos of the component or a group of features during or after machining, images / videos of the machining process and / or of one or more operating resources, tools, clamping devices or the like (e.g. one or more images of a tool cutting edge for an optical wear test before and after machining), the signal curve of one or more control signals, the power consumption and / or energy requirement of one or more machines, machine temperatures, error messages, chip sizes (volume, shape (flow chip, shear chip, tear chip, etc.)), as can be found for example at https: / / de. Wikipedia.org / wiki / Span_(Fertigungstechnik), last accessed on 17.October 2023, a material consumption (e.g. of auxiliary materials, oil, coolant), labor expenditure, cutting values ​​(particularly in connection with a machining tool and / or wear resistance, temperature, achievable quality), tool data (e.g. of machining tools and / or test tools, their suitability for machining component materials as well as their material and properties, data on wear resistance and / or wear condition, tool temperatures, quality achievable with a tool, maintenance data), sensor data (for recording vibrations, e.g. of the tool and / or holder system, main spindle and / or machine dynamics) as well as forces occurring during operation (cutting and clamping) and achieved tolerances, whereby this is only an exemplary, incomplete and therefore not exhaustive list.Other quantities not explicitly mentioned here may also be operating data and meet the general definition of the term “operating data” mentioned above.

[0038] Operating data that can be used to characterise and / or evaluate a welding process include, in particular: temperature, wire feed, gap width, electrode force, speed, current, voltage, power, wire consumption, gas consumption and welding time.

[0039] Operating data that can be used to characterize and / or evaluate a laser cutting process, for example, include: frequency, laser pulses per second, power, speed, blow-assist, Z-offset and the passage.

[0040] Operating data that can be used to characterize a waterjet cutting process, for example, include: feed rate, jet speed, cutting width, jet power, pressure.

[0041] Relevant operating data for characterizing or assessing a bending process include, in particular, the selection of the production tool (especially its dimensions (length, width, sheet thickness, bending force, and stiffness), the selection of the die, and the so-called K-factor (see https: / / de.wikipedia.org / wiki / Biegeverk%C3%BCrzung#Korrektur_durch_den_sog._k-Faktor, last accessed on October 17, 2023). The operating data can also include or be key figures that are or have been determined based on one or more recorded operating variables, such as production key figures such as system availability, the "Mean Time Between Failures," system efficiency, the proportion of setup time, production output, the scrap rate, the production error rate, and the throughput time, or the "Overall Equipment Efficiency," as described at https: / / wiki.hslu.ch / controlling / Produktionskennzahlen, last accessed on October 17, 2023.October 2023, or comparable key figures.

[0042] The data assigned to a component are in particular at least partially summarized into so-called feature groups, i.e. groups of features, wherein in particular at least one feature group is assigned to the component. For example, all data that are assigned to a specific hole, for example "Hole 1", in a workpiece, can be summarized to the feature group "Hole 1". For example, for a feature group of the type "Hole", the nominal diameter of the hole, the hole depth, form and position tolerances of this hole, surface qualities in various inner surfaces of the hole, etc., an alphanumeric identification name and / or an object color, which can be interpreted by the workstation and / or other recognition attributes, i.e.associated feature group data, and assigned to one or more components via the associated feature group, here a feature group “Bore”, for example feature group “Bore 1”.

[0043] It is particularly advantageous if every component that can be processed within the production system and which includes a corresponding feature group with the associated data is assigned to this feature group or this feature group is assigned to the component.

[0044] Particularly when many components within a production system have one or more identical feature groups, such an assignment of feature groups to components can easily achieve a high degree of standardization. When changes are made, only the data of each feature group needs to be changed, and not of each component. This significantly reduces the effort required to make changes and thus significantly improves a production system. In particular, simpler operation of the production system can be achieved. Above all, the effort required to update can be reduced. Furthermore, less storage space is required to store the changes. In addition, the

[0045] Simplify version control and increase audit reliability.

[0046] For example, features and their associated data can be grouped on the basis of so-called geometric form elements, i.e. in particular on the basis of geometric shapes that represent in particular basic geometric bodies or standard shapes.

[0047] For example, data and / or features that define a cylinder can be grouped into a feature group "Cylinder." The associated data that defines or characterizes a feature group is called "feature group data."

[0048] Exemplary form elements which can form particularly advantageous groups of features can be, for example: cylinders or cylindrical sections, bores, flat surfaces, chamfers, circles, partial circles, spheres, spherical sections - each positive or negative, ie formed as a recess or in solid material - grooves, cubes, cuboids and / or prisms.

[0049] For example, a borehole 1 can be assigned a nominal diameter 1 with a borehole depth 1 and form and position tolerances XY and / or an attribute for the unique identification and / or recognition of the form element.

[0050] The provision of data in step a1) of a method according to the invention comprises in particular the provision of data which contain information on one or more feature groups and / or are assigned to one or more components. The data can either contain only information about which feature group(s) is / are assigned to the component and / or information, i.e. data which directly defines the features of the group and / or the component at least in part. This means that for step a1) it is generally sufficient if only or at least partially only data is provided which can be used, for example, to determine which components which can be processed in a production system are all assigned to a specific feature group, for example the feature group “bore” or “cylinder”, but which cannot be used to determine how exactly the feature group is defined.For example, in the case of an engine block, this could be data showing that the engine block has 4 cylindrical bores in the “cylinder bore” feature group, without the data already precisely specifying the cylinder bore in this step. This information, how the cylinder bore is defined, i.e. precise feature group data such as nominal diameter, tolerances, surface qualities, honing process parameters, and any other associated machining processes and / or associated testing process(es) at a workstation (CAM, CAQ) and / or as mentioned above, can also be provided later when required, for example only for, with or in step c), when this information is needed for an evaluation, whereby in this case in particular only the feature group data from the selected feature group(s) is provided and not for additional feature groups.This means that significantly less data needs to be provided to provide the feature group data in step c), which can save data streams, storage requirements, network resources, computing power and other resources.

[0051] The provision of data may in particular comprise reading data from a memory, in particular from a computer-readable memory, capturing data, collecting data, generating data and / or entering data, and a combination thereof.

[0052] In particular, the acquisition of data can take place in a separate step before, after and / or at least temporarily simultaneously with the provision, in particular using one or more sensor devices.

[0053] Before providing corresponding data, especially when deposited, stored, or captured data is provided, it can first be checked whether the available data intended for provision has already been assigned to one or more components. If this is not the case, the available data, at least part of this data, can first be assigned to one or more components and / or feature groups.

[0054] The available data can be assigned, at least in part, to one or more components and / or one or more feature groups. In particular, the data can contain information on one or more feature groups and / or components.

[0055] In some cases it can be advantageous if the respective data is not assigned directly to one or more components, but rather only indirectly to a component via one or more feature groups. This has the advantage that no redundant assignments have to be maintained, but rather the data is, for example, only assigned to one associated feature group and only the feature group is assigned to the component, but not the data and the feature groups are directly assigned to the component. In particular, when there are a large number of components that can be processed within a production system, many of which have one or more identical feature groups, this can significantly reduce the amount of information that needs to be stored or maintained.Furthermore, in many cases this can lead to a reduction in the error rate, an improvement in process reliability, an improvement in data consistency, timeliness and quality, an increase in the standardization rate, an increase in audit security, an acceleration of automation across workstations and an improvement in data version control and, as a result, a reduction in costs, an increase in transparency regarding costs and the required capacities and thus a general optimization of the production system and its operation.

[0056] “Feature group data” in the sense of the present invention are data which are assigned to at least one feature group and which contain at least part of the information for defining the feature group(s).

[0057] Using the example of a geometric form element "bore," feature group data can be, for example, geometric data such as nominal diameter and borehole depth. However, in addition to geometric data, feature group data can also, as explained above in connection with data in general, primarily include operating data, particularly production data and / or inspection and measurement program data. In particular, feature group data can be any type of attribute that can be assigned to a feature group, such as machine parameters for manufacturing the component, identification data, coordinate measurement reference data, etc.

[0058] In particular, the feature group data of a feature group can be individual or all data that can define and / or characterize the feature group or the features combined into a group.

[0059] Feature groups do not have to be purely component-related groups of features or features combined into a group in a geometrically sensible way; feature groups can also be groups of very different features. A feature group can also be a combination of feature groups, in particular of different feature groups. The properties of a component can also be defined by different combinations of feature groups, for example by geometric addition or subtraction or swipes or the like of feature groups. A feature group can in particular be a group of features which, on the one hand, includes features of a geometric shape element and, on the other hand, features which are based on the recorded operating data, such as a throughput time, a scrap rate and / or costs, which affect other aspects of a component orof the production system. Feature group data can be, in particular, CAM data, CAQ data, and / or CMM data and / or operating data of the production system.

[0060] A feature group can also be a group of features that includes multiple feature subgroups, such as a "bore" feature group, which can include a wide variety of bores, in particular bores with different nominal diameters, whereby the bores with different nominal diameters can each represent individual feature subgroups. A feature group and / or one or more feature subgroups can alternatively or additionally be assigned to a workstation (CAx), for example, based on a revision status and / or identification by means of an ID number.

[0061] For example, groups of features have proven advantageous which each comprise features that characterize or define at least one geometric shape element, as well as further features related to at least one geometric shape element, which are based in particular on operating data, such as costs, throughput time and scrap rate and / or features that characterize the manufacturing process or one or more manufacturing steps and / or one or more testing processes.In particular, the feature groups "geometric shape element", "geometric shape element and costs", "geometric shape element and throughput time", "geometric shape element and scrap rate", "geometric shape element and tool" and "revision status of the geometric shape element" have proven advantageous with regard to improving the control of a production system, in particular with regard to improving the operation of a production system according to the invention, preferably with regard to optimising a production system. Although data is available, in particular data which is each assigned to one or more components and / or feature group data, an assignment of feature groups to one or more components orConversely, if at least one feature group is assigned to each component, a method according to the invention can in particular additionally comprise an assignment step which is preferably carried out or takes place before the data in step a 1 ) are provided, wherein in this assignment step, in particular at least one feature group is assigned to each component.

[0062] In an advantageous embodiment of a method according to the invention, this can in particular be carried out at least partially automatically, in particular with the aid of corresponding, predefined reference feature groups which can be compared with the component, and if there is sufficient agreement, a corresponding feature group, in particular a predefined and / or stored feature group or a newly created or newly to be created feature group, is assigned to the component depending on the reference feature group with which an at least partial agreement has been established.

[0063] Fully automated assignment is also conceivable, but semi-automated assignment still allows for manual control of the assignment. Fully automated assignment, on the other hand, enables faster assignment and avoids human errors, as well as assignment independent of working hours, which particularly enables efficient assignment outside of a production facility with limited staff, for example, on weekends or at night.

[0064] The term “manual” in the sense of the present invention means in particular the execution of individual actions and / or method steps by a user, operator, machine operator or the like.

[0065] “Partially automated” in the sense of the present invention means a process in which individual process steps are carried out manually, i.e. by a user, operator, or the like, and individual process steps are carried out with the aid of a corresponding computer device, automation device, or the like, in particular with the aid of a computer and / or a data processing device.

[0066] "Fully automated" means the execution of a process or process step without manual steps. Manual steps or procedural actions in this context can include, in particular, entering data, checking and / or releasing data, confirming actions, starting and / or stopping, and / or linking data, or similar activities.

[0067] The selection of at least one feature group in step b) is carried out in particular according to defined criteria, preferably according to predefined criteria. A corresponding criterion can, for example, be the frequency of a criterion, for example the frequency of occurrence of a feature group itself or the frequency of occurrence of a shaped element across all components that can be manufactured in a production system. Or the frequency of occurrence or production of a specific shaped element in a defined period of time. Or the error rate of the individual feature groups, whereby in particular the feature group with the highest error rate can be selected. In addition to the aforementioned criteria, the selection can also be made according to other criteria, such as quantity (pure frequency), robustness or scrap rate, or even a combination of criteria, such as quantity x process runtime.It is particularly advantageous if the group of characteristics that most frequently fulfills this criterion is selected.

[0068] In one possible embodiment of a method according to the present invention, the feature group to be selected in step b) can be selected from all feature groups associated with the provided data or to which the provided data is associated, or only from a subset of these feature groups. This means that, if necessary, filtering can be performed between the providing and selecting steps.

[0069] For example, the set of all feature groups from which a feature group is to be selected can be the set of all feature groups of one component, of multiple components, or only of selected components that can be manufactured in a production system. Alternatively or additionally, the set of all feature groups from which at least one feature group is to be selected can comprise a set of feature groups with one or more identical properties, for example, with one or more identical work plans and / or steps and / or one or more identical CAx data sets, such as a common CAD model, a common CAM setup, and / or a common CMM setup.The data assigned to a component can in particular be feature group data and can be assigned to at least one feature group, wherein feature group data are in particular only mandatorily linked to the feature group, but do not necessarily have to be directly linked to an associated component that is linked to the associated feature group.

[0070] Alternatively or furthermore, feature group data can also be data that is directly assigned to a component, in particular the component to which the corresponding feature group is assigned. Not all data directly assigned to a component necessarily has to be feature group data. It is also possible for a component to be assigned data that is not assigned to a feature group. These can be, for example, part numbers, identification numbers, or the like.

[0071] Likewise, feature groups can exist or be defined and thus be selectable, in particular one or more associated form elements to which no machining process or step is assigned. These can, for example, be surfaces on a component that are not machined. This means that the surface on the raw part and the finished part are identical and are not subject to any process.

[0072] After the selection in step b), at least a portion of the feature group data associated with the at least one selected feature group is provided in step c. The provision can also be performed in this step by reading from a memory, generating, capturing, retrieving, or the like.

[0073] If the feature group data from the at least one selected feature group is provided, it is evaluated in step d), and at least one value of at least one characteristic variable for the feature group is determined. Such a value can, for example, be the mean value of a throughput time of a defined geometric shape element and / or an average, actually achieved feed rate of a milling machine for milling the contour of a geometric shape element, particularly during roughing. However, such a value can also, for example, be an average achieved scrap rate due to an unachieved surface quality of a flat surface to be polished, or the like.

[0074] A "characteristic variable" for a selected feature group is understood to mean, in particular, a variable with which the feature group can be at least partially characterized. This does not have to be a variable that only allows conclusions to be drawn about the geometric properties of the component or dimensions, but can be any variable that can be related to the feature group of a component. However, the characteristic variable is particularly preferably a variable that in particular allows conclusions to be drawn about at least one process step in the manufacture of the associated feature group in a production system. Once the characteristic variable has been determined, it is stored, output and / or further processed in step e), in particular with the aid of a computer and / or a data processing device.

[0075] A characteristic value can be, for example: a frequency of occurrence of a feature group(s) in the components of the production system or across all or one or more selected workstations, a defined (target process duration) or an actual process duration (actual process duration) and / or these individually or combined cumulatively over the frequency of the feature group(s) and / or the associated costs.

[0076] A characteristic quantity can also be a revision history over a defined period of time, a current revision status, a maturity level and / or a physical or economic quantity.

[0077] Preferably, each change to a feature group or the associated feature group data is subject to a revision history, given by the revision status, which defines both the maturity level in the product development process and the associated economic and physical variables, which are provided by the feature group data, in terms of time.

[0078] The outputting may in particular comprise displaying on a display or other display device and / or outputting an advisory tone or signal tone or the like and / or voice information.

[0079] Further processing can, in particular, comprise at least one generation of a signal, for example a control signal for controlling at least one machine at at least one workstation and / or a data signal with data information for transmission to one or more workstations. A data signal can, for example, be a signal containing data information about the time of the last change to the feature group or at least one parameter value of the feature group data. This data signal can, for example, be used to ensure that no machining operation is performed at a production station if a machining program is based on older data than an associated feature group that is to be machined at this workstation.

[0080] Further processing may alternatively or additionally include, in particular, checking the determined value, for example, checking whether this value lies within a defined limit range and / or exceeds or falls below a defined threshold. In this case, further processing may, for example, include generating a blocking signal stating that the production of components to which the feature group from which the feature group data was evaluated is assigned, and for which a characteristic value outside a permissible limit range has been determined, is only permitted after a separate check and / or is blocked until approval has been granted by an authorized body.For example, corresponding machine programs for processing the component, which include the respective associated feature group, may be locked until corresponding changes to the component and / or feature group data have been made by the design department or one of the other workstations and these have been manually released, in particular by an authorized body or person.

[0081] This makes it easy to achieve data consistency and quality across the entire production system. In particular, this approach ensures that, for example, the correct data is always available for a processing operation at a workstation. This can reduce defective production and, consequently, lower the scrap rate.

[0082] In particular, the further processing may comprise generating and / or outputting and / or displaying and / or transmitting one or more control signals for manual, semi-automated and / or automated fully automated control of a production system depending on the at least one value determined in step d).

[0083] An advantageous embodiment of a production system according to the invention can further comprise a control step for manual, semi-automated and / or automated fully automated control of the production system, which is carried out in particular as a function of the at least one value determined in step d).

[0084] For this purpose, in an advantageous embodiment of a method according to the present invention, in step e) at least one determined value can be output, which is used in a further step of the method, in particular for controlling the production system.

[0085] In this case, the term "control" does not encompass "control" per se, but rather also inducing a change in at least one control parameter and / or a change in at least one other parameter of the production system. This alone can achieve advantageous optimization of the production system.

[0086] Control parameters are, in particular, parameters with which the processing result of one or more components and / or one or more operating parameters of the production system can be influenced, whereby a change in a control parameter is reflected, in particular, in a change in the operating data, in particular in the change in one or more operating variables of the production system, or should at least be reflected in the near future.

[0087] In addition to at least one workstation, a production system can in particular further comprise at least one production data management system (PDMS), in particular a central PDMS, with the aid of which the data can be provided in particular centrally, wherein the data can in particular be received by the PDMS and sent from these to one or more workstations.

[0088] In particular, a PDMS can comprise at least one data storage device. At least one data storage device can be a cloud data storage device. This easily enables a flexible architecture of a production system.

[0089] Alternatively or in addition to central storage in the PDMS, the data can also be stored directly in a production planning and control system of the production system.

[0090] A production system according to the present invention is preferably designed in particular to exchange the data wired or wirelessly between the individual workstations and / or the production data management system.

[0091] In one possible embodiment of a method according to the present invention, at least one method step is carried out using a data processing device and / or a computer system. A corresponding data processing device and / or a corresponding computer system can be integrated, in particular, into one of the workstations and / or several of the workstations and / or into the production data management system, but is connected or capable of being connected to at least one of these units via (data) communication.

[0092] All steps of a method according to the present invention can be repeated once or multiple times. Where technically feasible and possible, the individual method steps described herein can also be performed in a different order and / or individual method steps can be performed again before or after.

[0093] In an advantageous embodiment of a method according to the present invention, steps c), d) and e) are carried out in the order described above, i.e. first c), then d) and then e).

[0094] Depending on the design of a production system, however, it may be advantageous in some cases to carry out steps c), d) and e) in a different order, in particular in a second or further cycle, for example after the steps a1) to e) have been carried out once in a first cycle.

[0095] This means that prescribed procedures can also be applied iteratively.

[0096] In particular, in a second cycle, for example, feature group data of several selected feature groups can first be provided, evaluated, and then, on the basis of the provided feature group data, one or a few feature groups can be selected, for example the most frequently occurring feature group or the five most frequently occurring feature groups.

[0097] In particular, the method can be used to control an operation of the computer-aided production system, wherein it can be configured for manual control of the production system, for semi-automated control of the production system, for fully automated control of the production system or for a combination thereof.

[0098] For a particularly advantageous result of a method according to the invention or for a particularly advantageous production system, at least one feature group is a group of features relating to a geometric shape element or a group of features which has features relating to a geometric shape element, wherein the associated feature group data characterize and / or define the shape element.

[0099] It has been shown that almost every component can be defined almost completely by one or more geometric form elements and their associated data. This allows components to be grouped according to form elements. If machining data and / or operating data are assigned to the form elements, i.e., the respective "Form Element..." feature groups, for example, machine programs such as NC programs for manufacturing these form elements, standardization, adaptation, modification, and data consistency can be achieved across many components with little effort.

[0100] In one possible embodiment of a method according to the present invention, at least one feature group, in particular each feature group, has at least one geometric shape element, in particular a geometric base body, and / or at least one feature dependent on a geometric shape element, wherein the associated feature group data contain, in particular, operating data, preferably geometry and / or production data and / or test and / or measurement (program) data for the at least one geometric shape element. In particular, each shape element can be assigned at least one data set with data on the relative and / or absolute position of the shape element. Alternatively or additionally, operating data is preferably assigned to each shape element.Alternatively or additionally, each feature group, in particular each form element, can be assigned an ID number for unique identification, in particular for unique identification of the feature groups and feature group data.

[0101] A geometric shape element can in particular have or be a bore, an elongated hole, a thread, a pin, a cylinder, a flat surface, a cuboid, a chamfer, a pocket, a cone, a truncated cone, a groove, a sphere, a sphere segment, a circle, a circle segment or the like, or can be formed or defined at least partially from a combination of these.

[0102] Feature group data can in particular be design data (geometric data, dimensions, tolerances, weight, material, ...), administrative data (order number, part number, ...), manufacturing data (feed rate, cutting speed, tool data, NC program, ...), production data (actual manufacturing data, throughput times, ...), test data, cost information, planning data or other data.

[0103] A feature group can in particular comprise or be a combination of feature (sub)groups, for example a combination of the feature groups “geometric shape element” and “costs” or “geometric shape element” and “throughput time” or “geometric shape element” and “rejection rate”, wherein at least one feature group and / or feature (sub)group in particular always comprises or is a “geometric shape element”, and wherein each feature subgroup is in particular also a feature group and can in particular be selected in step b).

[0104] A component can be assigned several feature groups and / or feature subgroups, wherein the feature groups and / or feature subgroups are in particular different and / or belong to one and the same main feature group.

[0105] A main feature group can, for example, be formed by the geometric shape element "bore," and a sub-feature group can be, for example, a feature group "bore with a defined nominal diameter." A feature subgroup is, in particular, a feature group that comprises at least one parameter and an associated parameter value, which further specifies the feature subgroup compared to the associated higher-level main feature group. A feature subgroup can have further subgroups. A feature group or subgroup can, for example, be a bore, for example a "bore with nominal diameter XY." This feature group or subgroup can, for example, comprise two (further) feature subgroups, such as "bore with nominal diameter XY with countersink" and "bore with nominal diameter XY with countersink."

[0106] In a further possible embodiment of a method according to the present invention, particularly in an advantageous embodiment, the selection of at least one feature group is carried out depending on a frequency distribution of at least one of the feature groups and / or according to the frequency of a specific criterion that the individual feature groups fulfill. A selection based on the frequency distribution of at least some of the feature groups, each of which is assigned to a geometric shape element or represents a geometric shape element, has proven particularly advantageous.

[0107] The selection can be made, particularly depending on the frequency distribution, across all characteristic groups occurring within a production system or only across a portion of the characteristic groups occurring.

[0108] Making the selection based on a frequency distribution has proven particularly advantageous for a production system because the Pareto principle generally applies, according to which in a production system around 80% of the processing processes are attributable to only around 20% of the feature groups, or to put it the other way around, 20% of the feature groups form the basis for or define 80% of the processing processes. In many production systems, in particular around 80% of the processing processes are attributable to only around 20% of all form elements within this production system. This means that if you can identify those 20%, and in particular reliably identify the 20% of the form elements that cause around 80% of the effort, a lot can be achieved by optimizing these 20%. This can lead to particularly efficient optimization of a production system.

[0109] In this context, however, the question arises as to how the 20% of "correct" components can be clearly identified. For this purpose, it has proven advantageous to use feature groups and select one or more feature groups based on the resulting frequency distribution of the feature groups. In particular, the most frequently occurring feature group and, if necessary, further feature groups are selected in descending order of frequency, especially until approximately 20% of all occurring feature groups are captured. These can then be evaluated in a further step, in particular their associated feature group data, and appropriate measures can be initiated if necessary.

[0110] For a production system, it has proven particularly advantageous to use feature groups that comprise at least one geometric shape element and / or contain or group features of a geometric shape element, with associated feature group data that define and / or characterize the respective geometric shape elements. Therefore, the selection can be based, in particular, on a frequency distribution of feature groups based on at least one geometric shape element across some or all components processed in the production system.

[0111] If you assign all the components that are processed within a production system corresponding feature groups, in particular feature groups based on one or more geometric form elements, i.e. you mentally "break the component down" into several of these feature groups or in particular if each component is made up of one or more feature groups, in particular constructively, the individual feature groups, in particular the individual geometric form elements, represent the basis, in particular a type of building block, for all the components to be processed within the production system. In a similar way to how the individual words of a language can be put together to form sentences and entire texts, the components can be put together from the feature groups. In a similar way to language, the individual feature groups orForm elements occur with varying frequency in individual components and, in particular, within the production system. This means that not all generally occurring feature groups, or in particular all geometric form elements, occur with equal frequency; rather, some occur more frequently and others less frequently, with some of the feature groups occurring disproportionately often, similar to the behavior of words in a language.

[0112] If it is possible to identify the relevant 20% of the feature groups, which account for approximately 80% of the effort or so of a production system, a particularly efficient optimization of the production system of the products and the associated product development process (PEP) can be achieved, even at least partially automated.

[0113] In particular, by assigning feature groups to components and processes within the production system, especially to individual process steps within the product development process, for example in production planning and / or production planning and control, particularly based on geometric form elements, standardization can be efficiently achieved across a company's entire component spectrum. Standardization, in turn, enables the efficient collection of operational data and consistent key performance indicators such as duration, costs, etc. By means of consistent operational data acquisition and / or generally consistent data collection across the production system, the production system, especially production planning and control, can be supplied with the determined key performance indicators, and the operation and, in particular, the control of the production system can be continuously improved.This enables a form of self-management and self-organization of the production system, particularly in production planning and control. Furthermore, manufacturing processes that occur frequently, cause high capacities or costs, or are unstable or have low process reliability can be identified, filtered out, and analyzed. Based on the subsequent evaluation results obtained for the selected feature groups, in particular from form element-related feature group data and the key figures (characteristic variables) determined on this basis, such as frequency, throughput times, capacity requirements, costs, and scrap, individual processes or process steps of the production system can be optimized through improved / modified control of the respective process or process step.

[0114] This allows for an improvement and / or optimization of approximately 80% of the associated feature groups with minimal effort, namely based on approximately 20% of relevant feature groups from a developed set of feature groups. In particular, high data consistency and particularly efficient central management of all data in the production system can be achieved with just a few feature groups.

[0115] The correct definition of the feature groups is crucial for selecting the right, relevant feature groups. This means that the feature groups should be defined in such a way that they have sufficient, but not excessive, resolution with respect to the component spectrum of the production system. This means that the type and number of feature groups available for selection, particularly depending on their frequency, should be selected appropriately.

[0116] For a production system, it has proven particularly advantageous in some cases if the feature groups are selected in such a way that a frequency distribution is established that approximates a frequency distribution according to Zipf's law, with the most frequently occurring feature group, i.e., the feature group at rank 1, having a frequency of approximately 5-10%, in particular approximately 7-12%, and in particular approximately 10%. And the other feature groups in the subsequent ranks have a frequency that roughly follows Zipf's law.

[0117] The mathematical definition of Zipf's law is: If the elements of a set—for example, the words in a text—are ordered by their frequency, the probability p of their occurrence is inversely proportional to the position n on the frequency list. The position is also called rank: p(n)=1 / n — >p(1) / n with n=RANK='\ ,2, ... ,100000

[0118] Depending on how frequently the most frequent element (word) occurs, the frequency of all other elements can be estimated using the Zipf distribution function. Let's assume the most frequent element occurs with a frequency of 10%: p(1) = 10%. Then, the frequency of the subsequent ranks can be determined.

[0119] So we know that:

[0120] RANK 1: p(1) = p(1) / 1 = 10% at R=1

[0121] RANK 2: p(2) = p(1) / 2 = 5% at R=2

[0122] RANK 3: p(3) = p(1) / 3 = 3.3% at R=3 etc...

[0123] In a further possible embodiment of a method according to the present invention, the feature group is selected using Zipf's law based on the determined frequency distribution. A rank is assigned to the feature groups depending on their frequency according to Zipf's law, and the feature group is selected depending on its rank, with the highest-ranking feature group being selected in particular. Alternatively, the second-highest or a lower-ranking feature group can also be selected.

[0124] It is particularly advantageous to select the feature groups with the highest frequency, which represent approximately the most frequent 15-30%, especially the most frequent 20%.

[0125] The frequency distribution of the individual feature groups should preferably be

[0126] Zipf's distribution function, as it has been shown that this produces particularly good optimization results. This means that the feature group at rank 1 should have a frequency of approximately 10%, that at rank 2 approximately 5%, and so on.

[0127] However, if the determination and / or frequency distribution of the feature groups reveals that, for example, the feature group in rank 1 occurs with a frequency of 50%, this is particularly an indication that the underlying feature group definition has not been selected appropriately, in particular that it does not have sufficient “resolution”.

[0128] In this case, it may be advantageous, for example, to assign at least one additional parameter and corresponding values ​​to the feature group at rank 1 or to further feature groups, and, for example, to define feature subgroups and execute a second process cycle, possibly repeating the individual process steps until the frequency distribution approaches the Zipf distribution function. For example, if the geometric form element "hole" occurs most frequently at around 50%, it may be expedient to define sub-feature groups of the "hole" feature group, for example, depending on the respective nominal diameter of the holes, to redetermine the frequency distribution of the feature groups using the new feature groups, and then to select the highest-ranking feature groups, analyze them, and, if necessary, initiate measures. This is the only way to achieve efficient control of the production system.If the analysis / optimization of the production system were based on all drilling operations, too many components would be optimized, or too much effort would be required to significantly increase the level of automation, especially up to 80% automation. While this would achieve the desired optimization, it might result in a poorer cost-benefit ratio.

[0129] In some cases, it may also be advantageous to choose the feature group definitions in such a way that one approximates an adapted / modified Zipf distribution function, which may be better suited to the production system in question and the associated components.

[0130] For example, the Zipf distribution function can be adapted to optimize feature group selection using compression and / or stretching parameters and / or one or more offsets. In some cases, it may also be advantageous to use a frequency distribution function other than the Zipf distribution function. However, the Zipf distribution function has proven particularly advantageous for production systems.

[0131] Particularly when, due to the production system, only very few feature groups are defined and, as a result, one feature group (the most common) has a frequency of more than 20% and a meaningful increase in the "resolution" is not possible due to a lack of appropriate subdivision options, it can be advantageous to use a different distribution function as the basis to which the frequency distribution should approximate. For example, in this case, a stretched Zipf distribution function (using appropriate parameters) or another distribution function can be used. However, a left-skewed frequency distribution appears to be advantageous in any case. Approaches or corresponding frequency distributions based on "Benford's Law", the "Pareto Principle", the "Pareto Effect", the "20 / 80 Rule", a representation according to "ABC Analysis" and / or a representation according to the so-called "Top Task Analysis" are particularly advantageous.

[0132] However, it is generally important for a good result that the resolution of the feature groups on whose frequency distribution the selection is based is appropriately chosen. This can be verified, in particular, with a defined frequency distribution, especially one adapted to the respective production system. In particular, through a comparative representation (comparison plot).

[0133] In a further possible embodiment of a method according to the present invention, in particular in a further step e), it is checked whether the value determined in step d) lies within a predefined, permissible value range and / or below or above a defined limit. This makes it easy to determine whether the production system is operating as desired or whether a change and / or optimization of the production system's control system is required.

[0134] One or more permissible value ranges can in particular be specified, ie in particular predefined and stored in a memory and read out from this when required, and / or can be or have been obtained from recorded process data of the production system, ie based on so-called operating data.

[0135] In a further possible embodiment of a method according to the present

[0136] According to the invention, in a further step, in particular in a further step f), preferably depending on the value of the at least one characteristic variable determined in step d), at least one measure is initiated, wherein preferably at least one parameter value is changed, in particular of at least one parameter of the feature group data of the at least one selected feature group. And / or one or more parameters and their associated values ​​are added to or removed from the data, in particular to the feature group data of the at least one selected feature group, wherein in particular a value of at least one control parameter for controlling the production system and / or at least one value of another parameter, in particular a component parameter, is changed or added.

[0137] In particular, one or more parameters of product definitions (geometric data of one or more components, clamping devices, etc.), manufacturing definitions (production parameters, machine parameters, equipment parameters, etc.), inspection definitions (inspection programs, target tolerances, etc.), assembly definitions (assembly processes, assembly aids, assembly steps, assembly sequences, etc.) as well as planning definitions (selection and definition of planning stages, work plans, work steps, processing sequence, use of the production system for this (which workstation)) and / or maintenance definitions (maintenance measures, maintenance times, etc.) can be adapted, changed and / or added and / or removed. This allows a particularly good and needs-based adaptation of the production system to be achieved.The advantageous selection of a group of features according to the invention makes it possible to achieve a significant improvement of the production system with little effort, in particular a significant optimization of its operation (assuming a suitable adaptation / change / addition / removal of one or more parameters).

[0138] In the further course of the operation of a production system, the control of the production system takes place in particular depending on and / or taking into account the at least one or more parameters changed and / or added in step f).

[0139] In particular, an action is initiated if the test reveals that the determined value is outside a permissible range. For example, if it is determined that a mold element has a particularly high scrap rate, it may be advantageous to change the values ​​of one or more machining parameters at one of the associated production stations where the mold element in question is being machined (e.g., specify a different tool and / or adjust the feed rate, speed, etc.), or to correct any incorrect design data underlying the mold element, or to check the quality of the component blanks.

[0140] If a production system has several similar workstations for processing a mold element, it is possible, for example, to easily determine whether the scrap rate is within a defined tolerance range around the average scrap rate across all machines or outside of it, and thus the control of the production system should be adjusted to reduce the scrap rate of the mold element in question.

[0141] In an advantageous embodiment of a method according to the present invention, in a further step c1), at least one parameter value of the provided feature group data is changed and preferably, in particular also in a further step d1), the feature group data of at least some components, preferably of all components, to which the feature group with the feature group data is assigned, of which at least one parameter value has been changed, is updated.

[0142] In this case, at least one parameter value is preferably adapted, preferably as a function of the value of at least one characteristic variable of the feature group determined in step d), preferably a parameter which is suitable for controlling the production system and in particular such that an improved operation of the associated production system can be achieved, in particular an optimization.

[0143] An adaptation can in particular comprise component optimisation, i.e. an adaptation of the component data, e.g. geometry data, and / or an adaptation of machine / workstation data for processing on a production station. An adaptation can however also comprise a change in production planning, for example a change in process planning, e.g. shifting the processing of a form element from one processing machine to another. An added parameter (value) can for example be a blocking flag which indicates or contains information that, for example, form element XY may no longer be manufactured on machine Z. Such a blocking flag can, for example, trigger a blocking of processing on machine Z if a component with the relevant form element XY inadvertently ends up on machine Z for processing. This can be particularly advantageous in production systems with CAx workstations orCAx processing processes that are downstream of one or more CAD processing stations or steps.

[0144] Data to be added can also be new test and measurement program information, for example a new, additional measuring point, an additional tolerance specification or the like.

[0145] Process data can also be data that can be added or changed in the form of parameters and associated values, such as temperature specifications or temperature curves to define temperature control in a machining process.

[0146] Physical quantities can also be corresponding (added) data.

[0147] In some cases it may be necessary, for example, to restrict previously freely selectable values ​​of a parameter to a defined, permissible range and / or to widen or narrow tolerance bands.

[0148] In a further possible embodiment of a method according to the present invention, the changed parameter value and / or one or more parameters to be added and their parameter values, as well as information about the associated change(s), are stored in a production data management system, in particular centrally. This makes it particularly easy to reduce data redundancy, improve data consistency, timeliness, and quality, increase the standardization rate, increase auditability, and improve data version control. Furthermore, central data storage and the resulting reduction in data redundancy can reduce the error rate in many cases. This, in turn, has a beneficial effect on process reliability and costs.

[0149] In particular, all data, preferably all feature groups and

[0150] Component data should be stored in a production data management system, especially centrally. In principle, however, the data can also be stored decentrally, or both, i.e., partially (some data centrally, some decentrally). Appropriate access is the only important factor. For example, at least some of the data can be stored in a production planning and control system of the production system.

[0151] However, if the data assigned to a component and / or a feature group and its changes are stored centrally in a production data management system (PDMS) and this system is linked to the individual workstations, i.e. in particular connected or connectable via data communication, data changes can be implemented quickly and without great effort across many components and transmitted to the respective workstations or, conversely, values ​​changed at workstations can be played back directly to each component via the associated feature group.

[0152] In a further possible embodiment of a method according to the present invention, the parameter value and / or one or more parameters to be added and their parameter values ​​as well as information about the associated change(s) are changed across all components to which the at least one selected feature group is assigned, wherein the change(s) and / or updates can be carried out in particular manually, semi-automatically or fully automatically.

[0153] If the data assigned to a component and / or a feature group and its changes are stored centrally in a production data management system (PDMS) and this system is linked to the individual workstations, i.e., in particular, if it is connected or connectable via data communication, data changes can be implemented quickly and easily across many components by assigning feature groups to components and transmitted to the respective workstations. Conversely, values ​​changed at workstations can be directly transmitted back to each component via the associated feature group, since not all components need to be changed, but only the feature group data, the number of which is considerably smaller than the number of components. Thus, considerably fewer changes are required.However, significant improvements can also be achieved by storing the data directly in an associated production planning and control system of the production system.

[0154] This enables easier version control and tracking of changes. In particular, the resources required to manage changes (for example, the required storage space) can be significantly reduced.

[0155] Furthermore, this approach allows the maturity level of a component to be determined with little effort, particularly within the CAx chain of the associated production system, namely via the respective maturity levels of the feature group(s) assigned to the component. The maturity level of a feature group across one or more workstations or across the entire CIM architecture is defined in particular by the revision status or the version or change status of the feature group, in particular by the revision status or the version or change status of the associated feature group data. In an advantageous embodiment of a method according to the invention, this maturity level can therefore be determined in particular using the revision status and / or the version and / or change status of some or all of the feature group data of a feature group.In a further possible embodiment of a method according to the present invention, the maturity level of the component can also be determined from the maturity level of one or more feature groups of a component.

[0156] In a further possible embodiment of a method according to the present invention, in particular during operation of the production system, before starting a work process at a workstation of the production system for processing a component, the data provided locally at or in the workstation for processing the component are at least partially compared with the data stored centrally in the production data management system, wherein in the event of a data inconsistency, in particular the work process for processing the component is at least temporarily blocked and / or stopped and / or ended, in particular until an authorized release is given, preferably a manual release.

[0157] For example, it can be checked whether the programs, etc., stored at the workstation for processing the component are based on the most recent or current data assigned to the component, or whether changes made at the workstation for improved processing have been assigned to the component and / or the affected feature group(s) of the component and stored in the central production data management system. If a data inconsistency is detected, a warning message (acoustic and / or via a visual display) can be issued, indicating that the data is out of date.

[0158] If feature groups are also assigned to machine data and / or process data, and to the individual components via the feature groups, a simple revision control can be implemented for these components over part or the entire process chain with little effort, in particular with few resources.

[0159] An improvement / optimisation of the operation of a computer-aided production system can be achieved even without the above-described selection of a feature group and the associated evaluation of the associated feature group data if the changed parameter value and / or one or more parameters to be added and their parameter values ​​as well as information about the associated change(s) are stored centrally in a production data management system, and before a work process is started at a workstation of the production system for processing a component, the data provided locally at or in the workstation for processing the component are compared with the data stored centrally in the production data management system, wherein in the event of a data inconsistency, in particular the work process for processing the component is blocked, preferably for all affected components, at least temporarily.

[0160] This could, for example, be achieved with a computer-implemented method for controlling the operation of a computer-aided production system, in which the feature group data of a feature group can be updated, in particular, at regular intervals, wherein, in particular, after each change to the feature group data made by an operator at a processing station, a production system-wide change is or can be proposed, which becomes or can become binding across the production system after successful, authorized release.

[0161] A computer-implemented method, preferably for use in a computer-aided production system, in particular for operating a computer-aided production system and / or for controlling a computer-aided production system, can accordingly also comprise only one or more of the following steps: a1) Providing data that can be assigned to one or more components, wherein the data can contain information on two or more feature groups that are assigned to one or more components, wherein at least one feature group can be assigned to each component for which data can be provided, and wherein feature group data can be assigned to each feature group, a2) Acquiring operating data of the production system and assigning the acquired operating data of the production system to at least one feature group, whereby the acquired operating data of the production system can become feature group data,b) selecting at least one feature group, c1) changing at least one parameter value, in particular at least one parameter value of the provided feature group data, d1) updating the feature group data of at least some components, preferably of all components to which the feature group with the feature group data is assigned, of which at least one parameter value has been changed.

[0162] In particular, at least one method step can be carried out with the aid of a data processing device and / or with the aid of a computer system.

[0163] This can significantly improve the process reliability of a production system. In particular, it makes it easy to ensure that the most up-to-date data is always used.

[0164] A computer-aided production system according to the present invention can be characterized in particular by being designed and configured to carry out one of the methods described above, wherein the production system can in particular comprise corresponding means for carrying out such a method. The computer-aided production system can in particular comprise one or more workstations, wherein the workstations can in particular be interconnected via communication (wireless and / or wired). A production system can comprise one or more identical or identical workstations, as well as different workstations.

[0165] At least one workstation is particularly configured to process at least a subset of data associated with a component.

[0166] The production system may comprise at least one data processing device and / or at least one computer system.

[0167] A production system according to the present invention may in particular be configured to collect and store production system data during operation.

[0168] A production system according to the present invention can in particular be configured to assign production system data, in particular production system data acquired during operation, at least partially in a feature group-specific or feature group-related manner, in particular in a form element-related manner, and preferably at least partially automated, preferably fully automated.

[0169] A production system according to the present invention can in particular be configured to assign production system data acquired in connection with the processing of a component, in particular during the processing of a component, in a feature group-specific and / or feature group-related manner to the feature group(s) assigned to the component, in particular in a form element-related manner, ie to the form elements assigned to the component.

[0170] In a possible embodiment of a production system according to the present invention, the production system is further configured, in particular, to at least partially compare the data provided locally at or in the workstation for processing the component with the data stored centrally in the production data management system before starting a work process at a workstation of the production system for processing a component, wherein the production system is further configured, in particular, to at least temporarily block and / or stop and / or terminate, in particular, the work process for processing the component in the event of a data inconsistency.

[0171] A computer program according to the present invention may in particular comprise instructions which, when the program is executed by a computer, cause the computer to carry out one of the methods described above.

[0172] A computer-readable storage medium according to the present invention is in particular a computer-readable storage medium on which a computer program is stored, in particular a computer program which comprises instructions which, when the program is executed by a computer, cause the computer to carry out one of the methods described above.

[0173] A data processing device according to the present invention can in particular be a computer or a control device for a production system according to the invention, wherein the data processing device can comprise means for carrying out a method according to the present invention.

[0174] A further aspect of the present invention can be a database, a database structure or a database system which can be communicatively connected in particular to a previously described data processing device and / or can be part of the latter, wherein the database comprises in particular data and relations associated with the data which are at least partially feature group data and are associated with at least one feature group, wherein the database is set up for use in a previously described production system and the data and relations are stored in the database in such a way that at least part of the data stored in the database makes it possible to carry out a previously described method.

[0175] All preferred embodiments and their advantages described herein with reference to the method apply accordingly to a production system according to the invention, a computer program according to the invention, a computer-readable storage medium according to the invention and a data processing device according to the invention and vice versa, insofar as this is technically possible in each case.

[0176] Further features of the invention emerge from the claims, the figures, and the description of the figures. All features and combinations of features mentioned above in the description, as well as the features and combinations of features mentioned below in the description of the figures and / or shown alone in the figures, can be used not only in the respective specified combination, but also in other combinations or even on their own.

[0177] The invention will now be explained in more detail using a preferred embodiment and with reference to the accompanying drawings.

[0178] BRIEF DESCRIPTION OF THE DRAWINGS

[0179] They show:

[0180] Fig. 1 : in schematic principle representation an embodiment of a production system according to the invention

[0181] Fig. 2: a flowchart with method steps of an embodiment of a method according to the invention,

[0182] Fig. 3: a flow chart with further possible process steps of a process according to the invention,

[0183] Fig. 4: a flow chart with process steps of another possible, particularly advantageous method for use in a computer-aided production system,

[0184] Fig. 5: the reference form elements or the feature groups “bore” and “cuboid” of the component from Fig. 1 in an enlarged view,

[0185] Fig. 6: an exemplary, schematic representation of a possible assignment of

[0186] Feature groups and feature group data for a component with the feature groups in the center of the image,

[0187] Fig. 7: an example of a first determined for a production system

[0188] Frequency distribution of feature groups, here geometric form elements, of components that are processed by an associated production system,

[0189] Fig. 8: the frequency distribution from Fig. 7, where those geometric

[0190] Form element, which is highlighted approximately 80% of all form elements that are processed in the production system, Fig. 9: in schematic principle representation of the curve of a Zipf

[0191] Distribution, ie the curve of a frequency distribution that follows Zipf's law,

[0192] Fig. 10: a table with the functional variables underlying a Zipf frequency distribution and their relationship,

[0193] Fig. 11 : Example data of a Zipf distribution, where the last row represents the cumulative probability of occurrence of the formula elements,

[0194] Fig. 12: a table with sample data on the frequency distribution of different feature groups, here of different geometric form elements that are processed in a computer-aided production system, with the form elements sorted by ranks depending on their frequency,

[0195] Fig. 13: a table showing the frequency distribution of sub-form elements X... of the form element X, which are processed in a computer-aided production system, where the sub-form elements are sorted by ranks depending on their frequency,

[0196] Fig. 14: the frequency distribution of the form elements from Figs. 7 and 8 with form elements or feature groups divided into sub-form elements,

[0197] Fig. 15: a schematic curve of the frequency distribution from Fig. 14 for the frequency distribution of the feature group “geometric form element” over the associated geometric form elements sorted by rank,

[0198] Fig. 16: a schematic curve of a frequency distribution for the frequency distribution of the feature group “geometric form element x throughput time” over the associated geometric form elements sorted by rank,

[0199] Fig. 17: a schematic curve of the frequency distribution from Fig. 14 for the frequency distribution of the feature group “geometric form element x costs” over the associated geometric form elements sorted by rank, Fig. 18: a schematic diagram of an embodiment for the interface organization and for possible data and information flows between different workstations of a production system according to the invention, and

[0200] Fig. 19: a further schematic diagram of an embodiment of possible data and information flows starting from a feature group reference template (feature group reference data set) to various CAx workstations of a production system according to the invention.

[0201] DESCRIPTION OF PREFERRED EMBODIMENTS

[0202] Fig. 1 shows a schematic diagram of an embodiment of a production system 100 according to the invention, wherein the production system 100 according to the invention is designed to carry out a method according to the invention and has a production data management system 120 with a data processing device 130 according to the invention and a data memory 140 located in a cloud 110.

[0203] Furthermore, this exemplary embodiment of a production system 100 according to the invention comprises a plurality of workstations 10, 20, 30, 50, 60, 70, 80 and 90, which are each designed in particular to process at least a subset of data associated with a component 101, which is symbolized in Fig. 1 by a star with a bore 106 in the center, or to at least partially physically process the component 101.

[0204] Component 101 can, for example, be a Christmas candlestick or the like. However, the geometry of component 101 is not important in this case. Only a component has been chosen to allow a simplified, pictorial representation for better understanding. All features and advantages and the like described in connection with component 101 are not to be understood as limitations, but merely as examples for the basic description of the present invention.

[0205] Likewise, all embodiments described in connection with the exemplary embodiment of the production system 100 according to the invention are not to be understood as limiting, but merely as exemplary explanations of the invention. The described production system 100 and the method for operating this production system 100 described in this context are each examples of a possible embodiment based on the present invention.

[0206] In this exemplary embodiment of a production system according to the present invention, workstations 10, 20, and 30 of production system 100 are each organizationally assigned to production planning and are designed, in particular, for product-specific processing. Workstation 10 is, in particular, a CAD workstation, workstation 20 is, in particular, a CAM workstation, and workstation 30 is, in particular, a CAQ workstation. Workstations 50 to 90, on the other hand, are assigned to production planning and control (PPS), which is symbolized in Fig. 1 by block 40, and are configured and set up, in particular, for order-related processing.

[0207] The workstation 50 is in particular a product program planning workstation, the workstation 60 a quantity planning workstation, the workstation 70 a scheduling and capacity planning workstation, the workstation 80 an order monitoring workstation and the workstation 90 an order initiation workstation.

[0208] All workstations 10 to 30 and 50 to 90 are each connected to the production data management system 120 or the associated data processing device 130 by data communication, in this embodiment in particular via a wireless communication connection (WLAN) or radio or in another wireless manner, which is symbolized by the connecting lines with the reference numerals 104 and 105.

[0209] In addition, the individual workstations 10 to 30 and 50 to 90 are also connected to each other via data communication and are also in data communication with the data storage 140 in the cloud 110 via the data communication connections 102 and 103, which in this embodiment are also designed as wireless communication connections.

[0210] This enables efficient and rapid data exchange between the individual workstations 10 to 30 and 50 to 90, and thus between all components of the production system 100. This enables high data consistency, rapid provision of current data at each workstation 10 to 30 and 50 to 90, and thus optimal data processing at the individual workstations 10 to 30 and 50 to 90.

[0211] A high level of data integrity and consistency can be achieved through the central storage of data in the data storage 140 and the central production data management system 120, via which the workstations are supplied with the respective data and via which data can be played back from the workstations. In particular, the data for each component 101 can be kept up-to-date with minimal effort in almost real time at each workstation 10 to 30 and 50 to 90, and thus, for example, the current data can be provided before each work step at a workstation 10 to 30 and 50 to 90. This reduces defective production based on incorrect data assigned to a component, thus lowering the scrap rate, optimizing the production system, and reducing costs.

[0212] For particularly efficient operation of a production system 100 according to the invention, one or more feature groups 106 are each assigned to the individual components 101 that can be processed within the production system 100. These, in turn, are each assigned corresponding feature group data, wherein at least one feature group 106 assigned to a respective component 101 comprises a group of features relating to a geometric form element 106 and, in particular, comprises or is a feature group 106 of the "geometric form element" type. This enables particularly efficient operation of a production system 100. It has been found that almost all components 101 can be composed of several, in particular so-called standard geometric form elements.

[0213] Such an example of a geometric form element which can form a first feature group is, for example, the geometric form element bore 106 of the component 101. The feature group data assigned to the form element or the feature group “geometric form element” can be used to define the associated form element 106 or the associated feature group 106.

[0214] Corresponding feature group data can, for example, be geometric data such as dimensions, relative and absolute positions, form and position tolerances, but also information such as surface qualities, materials, or production data, such as process parameters for production such as cutting speeds, feed rates or the like, for example in a machining process, required production aids for recording, chucks, as well as test programs, plans and points or other measures for quality assurance, machine data or information on which machine, for example, the component is to be manufactured, flow charts for defining individual processing steps, etc.In addition, other data, such as process parameters such as temperature control curves, rest times, drying times, maximum permissible throughput times, maximum permissible rest times before further processing, costs, capacity requirements, outline times, cleaning instructions or the like, can also be assigned to a feature group.

[0215] In this way, most or even all components in many production systems can be defined, particularly via the various feature groups, whereby only the individual feature groups need to be assigned to a component, but not the individual feature group data. Rather, it is sufficient if the individual feature group data is only assigned to the feature groups, but the assignment of the individual parameters for each component is not saved separately. Since there are considerably fewer feature groups in a production system than there are usually components, the storage requirements for all data relating to the individual components can be considerably reduced, and a high degree of standardization can be achieved in a simple manner with minimal effort. However, it is essential that suitable feature groups are assigned to the components, and these, in turn, suitable feature group data in order to fully exploit this effect.

[0216] A further advantage of this approach is that particularly simple changes and updates to data can be made by making a single change to a feature group or the associated feature group data on a large number of components 101, namely on all those components to which the associated, changed feature group 106 is assigned. This can result in considerable savings in the operation of a production system 100; in particular, fewer resources are required for storing, processing, and documenting changes. In other words, version control or assurance and change management can be considerably simplified. This also makes version control or assurance possible in a simple manner.The audit security known from design can be easily extended to all workstations (10 to 30 and 50 to 90) within a production system. This allows production data, such as machine data and manufacturing parameters assigned to a feature group, for example, a geometric form element for its production, to be assigned to version control and change management, along with the geometric data defining the geometry of the respective element. This creates the possibility of comprehensive and audit-proof data management.

[0217] Furthermore, this approach enables particularly efficient operation and, in a particularly simple manner, advantageous, in particular improved control and / or optimization of a production system designed according to this approach.

[0218] A particularly advantageous operation or a particularly advantageous control of a production system according to the invention can be achieved, for example, with a method according to the present invention.

[0219] Fig. 2 shows a flowchart with the first four method steps S1 to S4 of an embodiment of a method according to the invention for use in a computer-aided production system, such as a production system 100, in particular for controlling an operation of the computer-aided production system 100.

[0220] Fig. 3 shows a flowchart with further possible method steps of a method according to the invention, which follow immediately in this embodiment. The embodiment of a method according to the present invention described here comprises, in particular, at least the following steps:

[0221] S1: a1) Providing component data that is assigned to one or more components 101 that can be processed by the computer-aided production system 100, wherein the component data contains information on two or more feature groups 106, each of which is assigned to one or more components 101, wherein each component 101 to which data is provided is assigned at least one feature group, wherein a feature group 106 comprises a group of features that at least partially define the component 101 to which the feature group is assigned, and wherein each feature group 106 is assigned feature group data, and a2) Acquiring operating data of the production system 100 and assigning the acquired operating data of the production system 100 to at least one feature group 106, whereby the acquired operating data of the production system 100 becomes feature group data,

[0222] S2: b) selection of at least one group of features 106,

[0223] S3: c) Providing at least part of the feature group data associated with the at least one selected feature group 106, wherein the provided feature group data contains at least part of the operating data of the production system 100 acquired in step S1 and associated with the feature group 106,

[0224] S4: d) Evaluating the provided feature group data and determining a value of at least one characteristic quantity for the selected feature group, ie, the value of a key figure for the selected feature group,

[0225] S5: e) storing, outputting and / or further processing the at least one value determined in step d),

[0226] S6: f) Initiating at least one measure depending on the value of the at least one characteristic variable determined in step d), wherein at least one parameter value of at least one parameter of the feature group data of the at least one selected feature group is changed and / or one or more parameters and their associated values ​​are added to the feature group data of the at least one selected feature group, wherein in particular a value of at least one control parameter for controlling the production system and / or at least one value of a component parameter is changed or added,

[0227] S7: g) storing the changed parameter value(s) and / or the added parameter(s) and their parameter values ​​as well as information about the associated change(s) centrally in a production data management system, and

[0228] S8: h) Checking data consistency during operation of the production system, in particular before starting a work process at a workstation of the production system for processing a component, wherein for this purpose the data provided locally at or in the workstation for processing the component are at least partially compared with the data stored centrally in the production data management system, wherein in the event of a data inconsistency the work process for processing the component is at least temporarily blocked and / or stopped and / or terminated and / or updated manually, partially automated or fully automated.

[0229] With reference to the production system 100 from Fig. 1, in step a1) or S1, data associated with the component 101 and with further components not shown here are provided, which contain information on at least the feature group 106 (“geometric form element bore”) and at least one further feature group, in particular on further geometric form elements, for example triangular form elements, by means of which the tips of the star of the component 101 are defined, wherein recorded operating data are also associated with these form elements, such as manufacturing parameters such as cutting speeds and parameters that were recorded during the manufacture of a component with this form element.

[0230] Based on these data, in step S2 (b)) a feature group is selected from the set of all feature groups for these data, wherein in a particularly advantageous embodiment of a method the most frequently occurring feature group is selected.

[0231] A group of features is assigned to each of the respective feature groups, which at least partially define the component 101, with corresponding feature group data being assigned to each feature group. For example, a nominal diameter, a borehole depth, and corresponding process parameters for the associated drilling machine are assigned to feature group 106, "geometric form element bore," which define how the borehole is to be produced, how the workpiece is to be clamped and with which production resources, which tool is to be used to produce the borehole, and, for example, how the borehole is to be subsequently inspected with regard to its dimensional accuracy and form and position tolerances. Alternatively or additionally, this may also include the provision of a machining program, for example an NC program, for machining and / or manufacturing the borehole and / or the creation of a testing process.The machining program and / or the inspection process can in particular also be generated and created manually, semi-automatically, or fully automatically. In one possible embodiment, the machining program and / or the inspection process can be generated and / or created based on one or more already known machining programs and / or inspection processes of the associated feature group or one or more comparable feature groups. If a comparable feature group is used as a basis for this, it can be particularly advantageous to select the feature group from the comparable feature groups that has the highest frequency, i.e., occurs most frequently.

[0232] After the data for the feature groups 106 assigned to the component 101 and further feature groups have been provided, at least one feature group is selected from the feature groups for which data has been provided, and the associated feature group data is provided (step (b) or S2).

[0233] The selection of the feature group in step b) or S2 is carried out in particular depending on a frequency distribution of the feature groups, in particular according to the frequency of a certain criterion, whereby in particular the feature group that occurs most frequently for this criterion is selected.

[0234] In a further step, the respective feature group data are provided (step S3 or c)) and subsequently evaluated (step d) or S4) and at least one variable characteristic of the selected feature group, ie in particular a key figure characteristic of the feature group, for example a scrap rate, is determined.

[0235] In a further step S5 or e), the determined characteristic variable is stored in this embodiment of a method according to the invention, in particular in the data memory 140 in the cloud 110, output and further processed.

[0236] The output is carried out in particular by displaying the determined key figure or the value of the determined characteristic quantity on a display device or by means of a display device.

[0237] During further processing, the data processing device 130 is used to check whether the value determined in step d) or S4 lies within a permissible limit range.

[0238] If not, a corresponding measure is initiated in step S6 or f), in particular at least one parameter value of the associated feature group data is changed and / or added in order to adapt, in particular to improve, the operation of the production system, in particular the control of the production system.

[0239] For example, one or more process parameters and / or machine tool control parameters of a machine tool can be changed if a scrap rate of an associated manufacturing step on a machine tool for a machining process when machining a form element is above a permissible limit.

[0240] In a further step S7 or h), the changed or added parameter value(s) are stored, in particular in the data storage 140 centrally in the cloud 110, in particular together with information about the associated change(s).

[0241] Furthermore, for a particularly advantageous operation of the production system 100, during operation of the production system in step S8 or h) before starting a work process at one of the workstations 10 to 30 or 50 to 90 for processing the form element 106, a data consistency is checked, wherein for this purpose the data provided locally at or in the workstation 10 to 30 or 50 to 90 for processing the form element 106 are at least partially compared with the centrally stored data, wherein in the event of a data inconsistency the work process for processing the form element 106 is at least temporarily blocked and / or stopped and / or ended.

[0242] Let's assume that feature group 106 ("geometric feature hole") is the most frequently occurring feature group among the feature groups for which data was provided in step a) or S1. Then, after this feature group 106 has been selected, the associated feature group data is evaluated and analyzed.

[0243] A characteristic value could, for example, be the scrap rate for the last four weeks. One result of this analysis could be, for example, that for the production of hole 106, i.e., for the production of the geometric form element hole 106, the current, determined scrap rate for the last four weeks, which can be determined, for example, from the recorded operating data assigned to the form element, is 10%, while the average scrap rate for the last year was 5%.

[0244] If a maximum scrap rate of, for example, 7% is permitted, appropriate measures are initiated to reduce the scrap rate again. In particular, the control of the production system 100 is adjusted, whereby at least one control variable is adjusted or changed, i.e., a parameter for controlling the production system that particularly affects the scrap rate of the associated feature group "form element bore" 106. For example, a cutting speed, a selected tool, a feed rate, or the like can be adjusted.

[0245] The change is saved centrally and distributed to all affected workstations on which the form element 106 is processed within the production system.

[0246] Before starting a work process at one of the workstations 10 to 30 or 50 to 90 for processing the form element 106, a data consistency is checked in each case, wherein for this purpose the data provided locally at or in the workstation 10 to 30 or 50 to 90 for processing the feature group 106 are at least partially compared with the centrally stored data, wherein in the event of a data inconsistency the work process for processing the form element 106 is at least temporarily blocked and / or stopped and / or terminated.

[0247] Fig. 4 shows a flowchart with method steps of another possible, particularly advantageous method for use in a computer-aided production system, wherein this example of an advantageous method for a production system comprises the following steps, which can be carried out in particular in addition to or alternatively to a method according to the invention:

[0248] S1A: a1) Providing data that are assigned to one or more components 101, wherein the data contain information about two or more feature groups 106, each of which is assigned to one or more components 101, wherein each component 101 to which data is provided is assigned at least one feature group 106, wherein a feature group 106 comprises a group of features that at least partially define the component 101 to which the feature group 106 is assigned, and wherein each feature group 106 is assigned feature group data,

[0249] S2A: b) selecting at least one feature group 106,

[0250] S3A: c1) Changing at least one parameter value of the provided feature group data,

[0251] S4A: d1) Updating the feature group data of at least some components 101, preferably of all components to which the feature group 106 with the feature group data is assigned, of which at least one parameter value has been changed. These method steps enable a particularly efficient implementation of changes, in particular an efficient and revision- or version-controlled implementation and documentation of changes to a large number of components with little change effort and little memory requirement, since the changes only need to be made to the associated feature group 106, but not to each component 101.

[0252] In the production system 100, the method steps described above are each carried out using the data processing device 130.

[0253] Fig. 5 shows the reference form elements, or rather the feature groups "borehole" and "cuboid," of the component from Fig. 1 in an enlarged view. In addition to the first feature group 106 "geometric form element borehole," component 101 is also assigned, in particular, a second feature group 109 "geometric form element cuboid." The geometric combination of these feature groups 106 and 109, in particular, the geometric subtraction of 106 from 109, results in component 101.

[0254] Fig. 6 shows an exemplary, schematic representation of a possible assignment of feature group data to feature groups 106, 109 or a combination of feature groups and / or to a component 101. In addition to feature groups 106, 109, which include or represent geometric form elements, other feature groups and feature group data can also be assigned to the component, such as feature groups with feature group data of the category 107 (“Components / Year”), 108 (“Number / Type of Feature Groups”), 111 (“Material”), 112 (“Key Figures / KPIs”) and further categories in the form of main and subcategories 113 (main category “Test and Production Process Data”), 114 (subcategory “Production Resources and Production Aids”), 115 (subcategory “Strategy / Production Organization”) and 116 (subcategory “Test and Production Parameters”).

[0255] Fig. 7 shows an example of a first frequency distribution of feature groups, here geometric form elements, of components processed by the associated production system 100, determined for the production system 100. The most frequent feature group is of the "bore" type and, in particular, accounts for approximately 50% of all feature groups. Fig. 8 shows the frequency distribution from Fig. 7, highlighting those geometric form elements that account for approximately 80% of all form elements processed in the production system.

[0256] Optimizing the most frequent feature group would therefore affect more than the 20% that are only being optimized in order to adapt the production system to maximum efficiency. Therefore, a change in the feature group definitions is necessary to obtain a more suitable "resolution" of the feature groups. To this end, the method steps S1 to S8 according to the invention are repeated iteratively until a frequency distribution of the feature groups is established that, in particular, approximates a Zipf distribution function.

[0257] Once this has been achieved and the feature groups most relevant to the production system have been identified and each of these feature groups can be assigned a unique process within the CAx chain, the production system can then be optimized with little effort.

[0258] Fig. 9 shows a schematic representation of the curve of a Zipf distribution, ie a frequency distribution that follows Zipf's law.

[0259] Fig. 10 shows a table with the functional variables underlying a Zipf frequency distribution and their relationship, in particular the occurrence of the probabilities of the first 10 ranks when the frequency at rank 1 is 10%.

[0260] Fig. 11 shows example data from a Zipf distribution, with the last row representing the cumulative occurrence probability of the formula elements. With such a frequency distribution, the first 10 ranks of feature groups represent approximately 30% of all feature groups, thus representing a suitable "resolution" of a frequency distribution. Once the most relevant feature groups for the production system have been identified with a suitable "resolution" and each of these feature groups can be assigned a unique process within the CAx chain, the production system can subsequently be optimized with little effort.

[0261] That is, the frequency distribution determined in a first step from Fig. 7 is adjusted in one embodiment of a method according to the present invention by repeating the method steps, for example, by adding and / or modifying feature group data, which in particular enable a subdivision into further sub-feature groups, until a frequency distribution according to Zipf's law is established. The frequency distribution according to Zipf's law appears to apply to most production systems.

[0262] It has been shown that with a basic set of approximately 60,000 form elements in a company, approximately the most common 1,600 form elements are crucial for efficient control of the production system, in particular for efficient standardization and optimization of the production system, especially for an improvement of 80% of the machining processes in production planning.

[0263] Fig. 12 shows a table with sample data on the frequency distribution of various feature groups, here of various geometric form elements 1 to 20, which are processed in a computer-aided production system 100. The form elements are sorted by rank depending on their frequency. Form element 1 ("hole") has a frequency of more than 22%. However, this is not yet meaningful because no clear manufacturing process is assigned to the form element.

[0264] By adding the nominal diameter and dividing the form element into sub-feature groups XY to XZ and determining the frequency distribution with the "new" feature groups, the resolution is significantly improved, and the form element of the "bore" type with a respective nominal diameter can be identified, which occurs most frequently among the form elements of the "bore" type. A unique manufacturing process can now be assigned to this form element. This process therefore has the greatest relevance and can be attributed the greatest potential for improvement with regard to the control and operation of the production system (here: form element XY). This is illustrated in Fig. 13, which shows a table for the frequency distribution of sub-form elements X... of form element 1 that can be processed in the computer-aided production system 100, wherein the sub-form elements are sorted by rank depending on their frequency.This example shows that for the underlying production system to which the data belongs, even when broken down into sub-form elements with only ten data sets or feature groups and feature group data, 20% of all processes are already captured in the CIM architecture of the production system. Since the sub-form elements have the same effect as the higher-level form elements (a frequency distribution according to a nonlinear, strictly monotonically decreasing function of the form x~). e with e = 1 according to Zipf's law or the Pareto principle, where x describes the rank of the frequency list or ranking list). In its original form, Zipf's law is free of parameters and e = 1. This allows approximately 20% of the total effort in the CIM architecture to be covered with just a few sub-form elements, in this case with only 10.

[0265] Particularly advantageous is an evaluation depending on the frequency of all mold elements per work step / work plan / component / assembly / product / year, the manufacturing time of each individual mold element and the cumulative manufacturing time of a mold element / component / assembly / product / year, the manufacturing costs of each individual mold element and the cumulative costs per mold element / component / assembly / product / year, a mold element-related scrap rate, which is a measure of the process robustness, as well as the cumulative scrap rate per mold element / component / assembly / product / year, and / or a revision status.

[0266] The quantity of form elements assigned to a component can, in particular, define the component. The quantity of components assigned to an assembly can, in particular, define the assembly. The quantity of assemblies assigned to a product can, in particular, define the product. The costs and / or capacities of a product can, in particular, be defined by associated form elements or associated feature groups and the associated feature group data. The cumulative quantity of costs for each individual form element can define the costs of the work step / work plan / component / assembly / product / year across the feature groups.

[0267] This means that 80% of all process-related expenditures in the CIM architecture of the associated production system can be identified using 20% ​​of the form elements sorted by frequency.

[0268] Fig. 14 shows the frequency distribution of the form elements from Figs. 7 and 8, with form elements or feature groups divided into sub-form elements. Fig. 15 shows a schematic curve of the frequency distribution from Fig. 14 for the frequency distribution of the feature group "geometric form element" across the associated geometric form elements sorted by rank, where the approximation to the Zipf distribution function is evident. With 20% of the feature groups, an area of ​​approximately 80% under the curve can be covered.

[0269] Fig. 16 shows a schematic curve of a frequency distribution for the frequency distribution of the feature group "geometric form element x lead time," sorted by rank across the associated geometric form elements, which corresponds to the representation of the cumulative lead time. 20% of the feature groups (of the associated form elements) are responsible for approximately 80% of the lead time (area under the curve up to the 20% limit).

[0270] Fig. 17 shows a schematic curve of the frequency distribution from Fig. 14 for the frequency distribution of the feature group "geometric feature x cost" across the associated geometric features sorted by rank, which corresponds to the representation of the cumulative costs. 20% of the feature groups (of the associated features) are responsible for approximately 80% of the costs (area under the curve up to the 20% limit).

[0271] Fig. 18 shows a schematic diagram of an exemplary embodiment for the interface organization and for possible data and information flows between the various workstations 10, 20, and 30 of a production system 100 according to the invention. A feature group reference template TRef (feature group reference data set, see Fig. 5) is associated, in particular, with a CAD workstation 10, and the associated data is initially forwarded to this after a change. From there, the data, in particular the changed data, can be forwarded to a CAM station 20, which can assign all components to which the respective feature group is assigned, for example, as component reference data DRef.At a test station 30, the component target data 101 target and the component actual data 101 actual meet and measures derived from these can be fed back in the form of data changes of the feature group data into the feature group reference data TRef and, for example, into the process data or the processing data of the individual work stations 10, 20 and 30.

[0272] Fig. 19 shows a further schematic diagram of an embodiment of possible

[0273] Data and information flows originating from a feature group reference template (feature group reference data set) to various CAx workstations of a production system according to the invention. This schematic diagram particularly shows an update process, in particular the feature group-related data update, which can also be referred to as feature group-related process revision. The vertical chain represents the processes of the CAx chain CAD-CAM-CAQ.

[0274] An advantageous production system can further be configured to perform a duplication step so that at least one (reference) feature group and its associated feature group data can be at least partially duplicated or copied. Optionally, the production system can further be configured to perform an adaptation step to adapt the copied feature group (template) and / or its feature group data to generate a new feature group.

[0275] In particular, the “copying” of the position and orientation of an object, in particular of a form element, of geometric bodies, associated features, associated machine (machining) features and / or parameters, appears to be advantageous.

[0276] It can be particularly advantageous to maintain a bidirectional link (relationship) between the original feature group (template) and the new feature group generated based on the feature group template. This enables particularly efficient revision, for example, starting from the reference feature group for all "dependent" feature groups generated based on the reference feature group, and vice versa. This means that if a change is required to the new feature group, this can be integrated into the feature group template and, if necessary, via this template into all dependent feature groups.

[0277] FURTHER EXAMPLES

[0278] Further embodiments and / or features may be:

[0279] No. 1: A computer-implemented method, preferably for use in a computer-aided production system, in particular for operating a computer-aided production system for component processing and / or manufacturing and / or for controlling a computer-aided production system for component processing and / or manufacturing, wherein in particular at least one method step is carried out with the aid of a data processing device and / or with the aid of a computer system, and wherein the method comprises the following steps: a) Providing data, in particular component data, which are assigned to one or more components, wherein the data contain information on two or more feature groups which are assigned to one or more components, wherein each component for which data is provided is assigned at least one feature group, wherein a feature group each comprises a group of features which the component,to which the feature group is assigned, and wherein each feature group is assigned feature group data, b) selecting at least one feature group, c) providing at least part of the feature group data assigned to the at least one selected feature group, d) evaluating the provided feature group data and determining a value of at least one variable characteristic of the selected feature group, e) storing, outputting and / or further processing the at least one value determined in step d).

[0280] No. 2: A computer-implemented method according to No. 1, wherein before and / or after the provision of data in step a), in particular a recording of data takes place, in particular operating data of the production system, preferably in a separate step, in particular for recording the data to be provided later, preferably using one or more sensor devices, in particular within the production system.

[0281] No. 3: A computer-implemented method according to No. 1 or 2, wherein, prior to the provision of data in step a), available data (deposited / stored or recorded data) are assigned to one or more components, wherein the data in particular contain information on one or more groups of features.

[0282] No. 4: A computer-implemented method according to No. 3, wherein each component is assigned in particular at least one feature group, preferably at least partially automated, in particular with the aid of corresponding predefined reference feature groups, which are compared with the component, wherein, if there is sufficient agreement, the sufficiently matching feature group is assigned to the component.

[0283] No. 5: A computer-implemented method according to Nos. 1 to 4, wherein the

[0284] Feature group data is linked to the associated feature group or to the associated feature group and the component to which the associated feature group is assigned.

[0285] No. 6: A computer-implemented method according to Nos. 1 to 5, wherein a feature group comprises, in particular, a group of features relating to a geometric form element, in particular a geometric basic body, and the associated feature group data characterize and / or define at least the form element.

[0286] No. 7: A computer-implemented method according to No. 6, wherein a geometric shape element comprises or is in particular a bore, an elongated hole, a thread, a pin, a cylinder, a flat surface, a cuboid, a chamfer, a cone, a truncated cone, a groove, a sphere, a sphere segment, a circle, a circle segment or the like, or is at least partially formed or defined from a combination of these.

[0287] No. 8: A computer-implemented method according to Nos. 1 to 7, wherein the feature group data may be design data (geometric data, dimensions, tolerances, weight, material, ...), administrative data (order number, part number, identification number, other recognition attribute, ...), manufacturing data (feed rate, cutting speed, tool data, NC program, ...), production data (actual manufacturing data, throughput times, ...), inspection data, cost information, planning data or other data, in particular physical or economic data.

[0288] No. 9: A computer-implemented method according to Nos. 1 to 8, wherein a feature group comprises or is a combination of feature (sub)groups, for example a combination of the feature groups “geometric shape element” and “costs” or “geometric shape element” and “throughput time” or “geometric shape element” and “rejection rate”, wherein at least one feature group and / or feature (sub)group is in particular always a “geometric shape element”, and wherein each feature subgroup is or can be in particular also a feature group and can be selected in particular in step b).

[0289] No. 10: A computer-implemented method according to Nos. 1 to 9, wherein a component is assigned multiple feature groups and / or feature subgroups, wherein the feature groups and / or feature subgroups are, in particular, different and / or belong to one and the same main feature group. No. 11: A computer-implemented method according to No. 10, wherein a main feature group is formed by the geometric form element "bore" and a sub-feature group is, in particular, a feature group "bore with a defined nominal diameter."

[0290] No. 12: A computer-implemented method according to Nos. 1 to 11, wherein steps c), d), e) are carried out in the following order: c), d) and e).

[0291] No. 13: A computer-implemented method according to Nos. 1 to 12, wherein at least steps b) and c) and / or b) to e) are repeated at least once, wherein the selection of the feature group in step b) of the second cycle is based in particular on the result of the evaluation from step e) of the first cycle.

[0292] No. 14: A computer-implemented method according to Nos. 1 to 13, wherein in a further step c1) at least one parameter value of the provided feature group data is changed and preferably, in particular also in a further step d1), the feature group data of at least some components, preferably of all components, to which the feature group with the feature group data is assigned, of which at least one parameter value has been changed, is updated.

[0293] No. 15: A computer-implemented method according to Nos. 1 to 14, in particular according to No. 14, wherein the feature group data of a feature group are updated at regular intervals, wherein in particular after each change to the feature group data made by an operator at a processing station, a production system-wide change is proposed, which becomes binding throughout the production system after successful release.

[0294] No. 16: A computer-implemented method, preferably for use in a computer-aided production system, in particular for operating a computer-aided production system and / or for controlling a computer-aided production system, wherein the method comprises the following steps and in particular at least one method step is carried out using a data processing device and / or with the aid of a computer system: a) providing data associated with one or more components, wherein the data contains information on two or more feature groups associated with one or more components, wherein each component for which data is provided is associated with at least one feature group, and wherein each feature group is associated with feature group data, b) selecting at least one feature group, c1) changing at least one parameter value of the provided feature group data,d1) Updating the feature group data of at least some components, preferably of all components to which the feature group with the feature group data is assigned, of which at least one parameter value has been changed.

[0295] No. 17: A computer-aided production system for carrying out a process according to Nos. 1 to 16.

[0296] No. 18: A computer-aided production system according to No. 17, wherein the production system has one or more workstations, wherein the workstations are in particular networked with one another for communication purposes (wireless and / or wired).

[0297] No. 19: A computer-aided production system according to No. 17 or 18, wherein the production system comprises at least one data processing device and / or at least one computer system.

[0298] No. 20: A computer-aided production system according to Nos. 17 to 19, wherein the production system is configured to collect and store production system data during operation.

[0299] No. 21: A computer-aided production system according to Nos. 17 to 20, wherein the production system is configured to assign production system data, in particular production system data acquired during operation, at least partially in a feature group-specific or feature group-related manner, in particular in a form element-related manner, and preferably at least partially automated, preferably fully automated.

[0300] No. 22: A computer-aided production system according to No. 21, wherein the production system is configured to assign production system data acquired in connection with the processing of a component, in particular during the processing of a component, in a feature group-specific and / or feature group-related manner to the feature group(s) assigned to the component, in particular form element-related, ie to the form elements assigned to the component.

[0301] No. 23: A computer-aided production system according to Nos. 17 to 22, wherein the production system is configured to display information about the last change and / or the change history of at least some of the feature group data.

[0302] No. 24: A computer-aided production system according to Nos. 17 to 23, wherein the production system comprises at least one display device for displaying feature group data and / or change information to the feature group data, preferably at each workstation.

[0303] No. 25: A computer-aided production system according to Nos. 17 to 24, wherein the production system comprises a production data management system, in particular for managing the component data, the components that can be processed within the production system and / or for managing the feature group data, wherein the production system is in particular set up to store the data centrally, preferably on at least one server, in particular on at least one server that is part of the production system and is in particular located in the same network as at least one workstation, and / or on an external server in a cloud.

[0304] No. 26: A computer-aided production system according to Nos. 17 to 25, wherein the production system is configured, before starting a work process at a workstation of the production system for processing a component, to at least partially compare the data provided locally at or in the workstation for processing the component with the data stored centrally in the production data management system, wherein the production system is further configured, in particular, to at least temporarily block and / or stop and / or terminate, in particular, the work process for processing the component in the event of a data inconsistency.

[0305] No. 27: A computer-aided production system according to Nos. 17 to 26, wherein the production system has an evaluation device, in particular an evaluation and display device, which is configured for a feature-group-related evaluation of component and / or production system data, in particular for a form-element-related evaluation of component and / or production system data. No. 28: A computer-aided production system according to No. 27, wherein the evaluation device is configured to evaluate production system data based on feature groups, in particular form-element-related, according to frequency, costs, resources or capacity requirements, and process reliability or robustness and / or scrap rate, in particular per feature group, preferably per form element.

[0306] No. 29: A computer-aided production system according to No. 28, wherein the evaluation device is designed to distinguish between groups of features, in particular form elements, according to whether they require processing, in particular a physical processing step, or not.

[0307] No. 30: A computer-aided production system according to Nos. 17 to 29, wherein the production system has an evaluation device, in particular an evaluation and display device, which is configured to generate and in particular to output and / or store a component-specific feature group parts list, in particular a component-specific form element parts list, preferably including associated change information.

[0308] No. 31: A computer-aided production system according to Nos. 17 to 30, wherein the production system has an evaluation device, in particular an evaluation and display device, which is set up for a feature group-related capacity requirement and / or cost calculation, in particular for a form element-related capacity requirement and / or cost calculation.

[0309] No. 32: A computer program, the computer program comprising instructions which, when executed by a computer, cause the computer to carry out a method according to any one of Nos. 1 to 16.

[0310] No. 33: A computer-readable storage medium, wherein a computer program according to No. 33 is stored on the computer-readable storage medium, which computer program comprises instructions which, when executed by a computer, cause the computer to carry out a method according to one of Nos. 1 to 16.

[0311] No. 34: Data processing device, in particular a computer or a control device for a production system according to one of Nos. 17 to 31, comprising means for carrying out the method according to one of Nos. 1 to 16. Although some aspects have been described in the context of a device, in particular in connection with a production system and / or a data processing device, it is clear that these aspects also represent a description of the corresponding method, insofar as this is technically possible, wherein in particular a block or a device corresponds or can correspond in particular to a method step or a function of a method step. Analogously, aspects that are described in the context of a method step, insofar as this is technically possible, also represent a description of a corresponding block or element or a property of a corresponding device.

[0312] This means, in particular, that the preferred embodiments presented with reference to the method described above and their advantages also apply accordingly to a production system according to the present invention as well as to a computer program, a computer-readable storage medium and a data processing device according to the present invention and vice versa, even if this is not explicitly described again in each case at the corresponding points in this application, in particular in order to avoid repetition.

[0313] The embodiments of the present invention can be implemented in a computer system and / or with the aid of a computer system, in particular with a computer system for a production system or with a computer system within a production system. The computer system can in particular comprise a data processing device according to the present invention or alternatively also be a part thereof.

[0314] The computer system may be a local computing device (e.g., a personal computer, laptop, tablet computer, or mobile phone) having one or more processors and one or more memory devices, or a distributed computing system (e.g., a cloud computing system having one or more processors or one or more memory devices distributed at different locations, e.g., at a local client and / or one or more remote server farms and / or data centers). The computer system may include any one or more such circuits, or one or more combinations of circuits. In one embodiment, the computer system may include one or more processors, which may be of any type.As used herein, processor may mean any type of computing circuit, such as, but not limited to, a microprocessor, a microcontroller, a complex instruction set microprocessor (CISC), a reduced instruction set microprocessor (RISC), a very long instruction word (VLIW) microprocessor, a graphics processor, a digital signal processor (DSP), a multi-core processor, a field-programmable gate array (FPGA), or any other type of processor or processing circuit. Other types of circuitry that may be included in the computer system may be a purpose-built circuit, an application-specific integrated circuit (ASIC), or the like, such as one or more circuits (e.g., a communications circuit) for use with wireless devices such asmobile phones, tablet computers, laptop computers, two-way radios and similar electronic systems.

[0315] The computer system may include one or more storage devices, which may include one or more storage elements suitable for the particular application, such as main memory in the form of random access memory (RAM), one or more hard disks, and / or one or more drives handling removable media such as CDs, flash memory cards, DVDs, and the like. The computer system may also include a display device, one or more speakers, and a keyboard and / or controller, which may include a mouse, trackball, touchscreen, voice recognition device, or any other device that allows a system user to input information to and receive information from the computer system.

[0316] Some or all of the method steps may be performed by (or using) a hardware device, such as a processor, a microprocessor, a programmable computer, or an electronic circuit. In some embodiments, one or more of the key method steps may be performed by such a device.

[0317] Depending on specific implementation requirements, embodiments of the invention can be implemented in hardware or software. The implementation can be carried out using a non-volatile storage medium such as a digital storage medium, such as a floppy disk, a DVD, a Blu-ray, a CD, a ROM, a PROM and EPROM, an EEPROM, or a FLASH memory, on which electronically readable control signals are stored that interact (or can interact) with a programmable computer system, in particular a computer system according to the invention, and / or a data processing device, in particular a data processing device according to the invention, such that the respective method is carried out. Therefore, the digital storage medium can be computer-readable.

[0318] Some possible embodiments according to the invention comprise a computer-readable storage medium, in particular a data carrier, with electronically readable control signals that can interact with a programmable computer system, in particular a computer system according to the invention, and / or a data processing device, in particular a data processing device according to the invention, so that one of the methods described herein is carried out.

[0319] In general, embodiments of the present inventions, in particular embodiments of the method inventions, can be implemented as a computer program product with a program code, wherein the program code is effective for executing one of the methods when the computer program product is running on a computer. The program code can, for example, be stored on a machine-readable medium.

[0320] Further embodiments include a computer program for performing one of the methods described herein, which is stored on a machine-readable carrier.

[0321] In other words, an embodiment of the present invention may therefore be a computer program having a program code for carrying out one of the methods described herein, wherein the computer program runs on a computer.

[0322] A further possible embodiment of the present invention is therefore, for example, a storage medium (or a data carrier or a computer-readable medium) comprising a computer program stored thereon for carrying out one of the methods described herein when executed by a processor. The data carrier, the digital storage medium, or the recorded medium is typically tangible and / or non-seamless. A further embodiment of the present invention may, for example, be a device as described herein, comprising a processor and the storage medium.

[0323] A further embodiment of the invention may be a data stream or a signal sequence representing the computer program for carrying out one of the methods described herein. The data stream or signal sequence may, for example, be configured such that transmission can or does occur via a data communication connection, for example, via the Internet.

[0324] A data stream or signal sequence transmitted via a data communication connection can also comprise only individual data or data packets from individual process steps and does not necessarily have to represent the computer program. For example, a data stream or signal sequence can contain component and / or feature group data, which, for providing data in step a), are transmitted via a data communication connection to a data processing device, for example via WLAN or LAN, in particular from one or more workstations and / or from one or more readable data memories of the production data management system to the data processing device.

[0325] Likewise, a data stream or a signal sequence can contain component and / or feature group data and / or one or more evaluation results and values ​​determined during the evaluation in step d), which are transmitted via a data communication connection from a data processing device, for example via WLAN or LAN, in particular to one or more workstations and / or to one of the several data memories of the production data management system.

[0326] A further embodiment comprises a processing means, for example a computer or a programmable logic device, configured or adapted to carry out any of the methods described herein.

[0327] A further embodiment comprises a computer on which the computer program for carrying out one of the methods described herein is installed.

[0328] Another embodiment according to the invention comprises a device or system configured to transmit (e.g., electronically or optically) a computer program for performing any of the methods described herein to a recipient. The recipient may, for example, be a computer, a mobile device, a storage device, or the like. The device or system may, for example, comprise a file server for transmitting the computer program to the recipient. In some embodiments, a programmable logic device (e.g., a field-programmable gate array, FPGA) may be used to perform some or all of the functionalities of the methods described herein. In some embodiments, a field-programmable gate array may cooperate with a microprocessor to perform any of the methods described herein.In general, the procedures are preferably performed by each hardware device.

[0329] In addition to the described embodiments and exemplary embodiments, further embodiments are possible, in particular of a constructive nature, without departing from the scope of protection defined by the patent claims.

[0330] LIST OF REFERENCE SYMBOLS

[0331] 100 production system according to the invention

[0332] 130 data processing device according to the invention

[0333] 140 Data storage (computer-readable storage medium according to the invention)

[0334] 10 CAD workstations

[0335] 20 CAM workstations

[0336] 30 CAQ workstations

[0337] 35 Production planning, especially product-specific

[0338] 40 Production planning and control, especially order-related

[0339] 50 Product Master Planning Workstations

[0340] 60 Quantity Planning Workstations

[0341] 70 scheduling and capacity planning workstations

[0342] 80 order monitoring workstations

[0343] 90 order initiation workstation

[0344] 101 Component

[0345] 101 is actual component

[0346] 101 target component

[0347] 102 Data communication connection for data transmission

[0348] 103 Data communication connection for data transmission

[0349] 104 Data communication connection for data transmission

[0350] 105 Data communication connection for data transmission

[0351] 106 first feature group “geometric form element hole”

[0352] 107 Feature group data category “Components / Year”

[0353] 108 Feature group data category “Number / Type of feature groups”

[0354] 109 second feature group “geometric form element cuboid”

[0355] 110 Cloud

[0356] 111 M erkm al sg ru ppendaten- Category “Material 1

[0357] 112 Feature group data category “Key performance indicators (KPIs)”

[0358] 113 Feature group data main category “Testing and manufacturing process”

[0359] 114 Feature group data subcategory “Production resources and production aids”

[0360] 115 Feature group data subcategory “Strategy / Manufacturing organization”

[0361] 116 Feature group data subcategory “Test and manufacturing parameters” 120 Production data management system (PDMS)

[0362] DRef component reference data

[0363] S1..S8 Method steps of a first embodiment of a method according to the invention

[0364] S1A..S4A Process steps of a further advantageous process

[0365] TRef Feature Group Reference Template (Feature Group Reference Dataset)

Claims

PATENT CLAIMS 1. A computer-implemented method for use in a computer-aided production system (100) for component processing, in particular for controlling an operation of a computer-aided production system (100) for component processing, wherein the method comprises at least the following steps: a1) providing (S1) component data associated with one or more components (101) that can be manufactured and / or processed by the computer-aided production system (100), wherein the component data contain information on two or more Feature groups (106, 109) that are assigned to one or more components (101), wherein each component (101) for which data is provided is assigned at least one feature group (106, 109), wherein a feature group (106, 109) comprises a group of features that at least partially define the component (101) to which the feature group (106, 109) is assigned, and wherein each feature group (106, 109) is assigned feature group data (107, 108, 111, ... , 116), a2) acquiring operating data of the production system (100) and assigning the acquired operating data of the production system (100) to at least one feature group (106, 109), whereby the acquired operating data of the production system (100) are assigned to feature group data (107, 108, 111, ... , 116), b) selection (S2) of at least one feature group (106), c) provision (S3) of at least part of the feature group data (107, 108, 111, ..., 116) which are assigned to the at least one selected feature group (106), wherein the provided feature group data (107, 108, 111, ... , 116) contain at least a part of the operating data of the production system (100) recorded in step a2) and assigned to the feature group (106), d) evaluating (S4) the provided feature group data (107, 108, 111, ... , 116) and determining a value of at least one variable characteristic of the selected feature group (106), and e) storing, outputting and / or further processing (S5) the at least one value determined in step d). Method according to claim 1, wherein in step e) at least one determined value is output, and wherein the at least one determined and output value is used in a further step of the method, in particular for controlling the production system (100). Method according to claim 1 or 2, wherein at least one feature group, in particular each feature group, has at least one geometric shape element and / or at least one feature dependent on a geometric shape element, wherein the associated feature group data contains in particular operating data, preferably geometry and / or production data, for the at least one geometric shape element. Method according to one of claims 1 to 3, wherein the selection of the at least one feature group takes place depending on a frequency distribution of at least one of the parts of the feature groups.Method according to one of claims 1 to 4, wherein the selection of the feature group is carried out using Zipf's law based on the determined frequency distribution, wherein the feature groups are assigned a rank depending on their frequency according to Zipf's law, and the feature group is selected depending on their rank. Method according to one of claims 1 to 5, wherein in a further step, it is checked whether the value determined in step d) lies within a predefined, permissible value range.Method according to one of claims 1 to 6, wherein in a further step, in particular in a step f), preferably as a function of the value of the at least one characteristic variable determined in step d), at least one measure is initiated, wherein preferably at least one parameter value, in particular of at least one parameter of the feature group data of the at least one selected feature group, is changed and / or one or more parameters and their associated values ​​are added to the data, in particular to the feature group data of the at least one selected feature group, wherein in particular a value of at least one control parameter. for controlling the production system and / or at least one value of another parameter of the production system, in particular a component parameter, is changed or added or removed.

8. The method according to any one of claims 1 to 7, wherein the changed parameter value and / or one or more parameters to be added or removed and their parameter values ​​as well as information about the associated change(s) are stored centrally in a production data management system (120) or directly in a production planning and control system (40) of the production system (100).

9. Method according to one of claims 1 to 8, wherein the parameter value and / or one or more parameters to be added and their parameter values ​​as well as information about the associated change(s) are changed across all components to which the at least one selected feature group is assigned.

10. The method according to one of claims 1 to 9, wherein, in particular during operation of the production system, before starting a work process at a workstation (10, 20, 30, 50, ...90) of the production system for processing a component, the data provided locally at or in the workstation for processing the component are at least partially compared with data stored centrally in the production data management system (120) or with data stored in the production planning and control system (40), wherein in the event of a data inconsistency, in particular the work process for processing the component is at least temporarily blocked and / or stopped and / or ended.

11. Computer-aided production system (100), characterized in that the production system (100) is designed to carry out a method according to one of claims 1 to 10.

12. Production system (100) according to claim 11, wherein the production system is further configured, before starting a work process at a workstation of the production system for processing a component, to compare the data provided locally at or in the workstation for processing the component with data stored centrally in the production data management system (120) or with data stored in the Production planning and control system (40) to at least partially compare the data stored, wherein the production system is further configured, in particular, to at least temporarily block and / or halt and / or terminate the work process for machining the component in the event of a data inconsistency. Computer program, wherein the computer program comprises instructions which, when the program is executed by a computer, cause the computer to carry out a method according to one of claims 1 to 10. Computer-readable storage medium, wherein a computer program according to claim 13 is stored on the computer-readable storage medium, which comprises instructions which, when the program is executed by a computer, cause the computer to carry out a method according to one of claims 1 to 10.Data processing device, in particular a computer or a control device for a production system according to claim 11, comprising means for carrying out the method according to one of claims 1 to 10.

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