WO2023280508A1 - Verfahren zum betreiben einer presse, computerprogramm und elektronisch lesbarer datenträger - Google Patents
Verfahren zum betreiben einer presse, computerprogramm und elektronisch lesbarer datenträger Download PDFInfo
- Publication number
- WO2023280508A1 WO2023280508A1 PCT/EP2022/065829 EP2022065829W WO2023280508A1 WO 2023280508 A1 WO2023280508 A1 WO 2023280508A1 EP 2022065829 W EP2022065829 W EP 2022065829W WO 2023280508 A1 WO2023280508 A1 WO 2023280508A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- press
- determined
- serial number
- computing device
- recognition rate
- Prior art date
Links
- 238000000034 method Methods 0.000 title claims abstract description 63
- 238000004590 computer program Methods 0.000 title claims description 12
- 238000004519 manufacturing process Methods 0.000 claims description 37
- 238000001514 detection method Methods 0.000 claims description 24
- 238000010801 machine learning Methods 0.000 claims description 9
- 238000003780 insertion Methods 0.000 claims description 5
- 230000037431 insertion Effects 0.000 claims description 5
- 238000007619 statistical method Methods 0.000 claims description 4
- 239000000463 material Substances 0.000 description 21
- 238000012545 processing Methods 0.000 description 13
- 238000005520 cutting process Methods 0.000 description 9
- 238000012544 monitoring process Methods 0.000 description 7
- 239000011265 semifinished product Substances 0.000 description 7
- 238000010147 laser engraving Methods 0.000 description 6
- 238000013528 artificial neural network Methods 0.000 description 4
- 239000002184 metal Substances 0.000 description 4
- 229910052751 metal Inorganic materials 0.000 description 4
- 238000012360 testing method Methods 0.000 description 4
- 238000012423 maintenance Methods 0.000 description 3
- 238000004886 process control Methods 0.000 description 3
- HCHKCACWOHOZIP-UHFFFAOYSA-N Zinc Chemical compound [Zn] HCHKCACWOHOZIP-UHFFFAOYSA-N 0.000 description 2
- 230000006866 deterioration Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000003825 pressing Methods 0.000 description 2
- 239000000047 product Substances 0.000 description 2
- 238000004393 prognosis Methods 0.000 description 2
- 238000003860 storage Methods 0.000 description 2
- 230000009897 systematic effect Effects 0.000 description 2
- 229910052725 zinc Inorganic materials 0.000 description 2
- 239000011701 zinc Substances 0.000 description 2
- 230000006978 adaptation Effects 0.000 description 1
- 238000004140 cleaning Methods 0.000 description 1
- 230000007797 corrosion Effects 0.000 description 1
- 238000005260 corrosion Methods 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 239000003973 paint Substances 0.000 description 1
- 238000004321 preservation Methods 0.000 description 1
- 238000010972 statistical evaluation Methods 0.000 description 1
- 230000003746 surface roughness Effects 0.000 description 1
Classifications
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B30—PRESSES
- B30B—PRESSES IN GENERAL
- B30B15/00—Details of, or accessories for, presses; Auxiliary measures in connection with pressing
- B30B15/26—Programme control arrangements
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B21—MECHANICAL METAL-WORKING WITHOUT ESSENTIALLY REMOVING MATERIAL; PUNCHING METAL
- B21C—MANUFACTURE OF METAL SHEETS, WIRE, RODS, TUBES OR PROFILES, OTHERWISE THAN BY ROLLING; AUXILIARY OPERATIONS USED IN CONNECTION WITH METAL-WORKING WITHOUT ESSENTIALLY REMOVING MATERIAL
- B21C51/00—Measuring, gauging, indicating, counting, or marking devices specially adapted for use in the production or manipulation of material in accordance with subclasses B21B - B21F
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B30—PRESSES
- B30B—PRESSES IN GENERAL
- B30B15/00—Details of, or accessories for, presses; Auxiliary measures in connection with pressing
- B30B15/30—Feeding material to presses
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V30/00—Character recognition; Recognising digital ink; Document-oriented image-based pattern recognition
- G06V30/10—Character recognition
- G06V30/12—Detection or correction of errors, e.g. by rescanning the pattern
- G06V30/133—Evaluation of quality of the acquired characters
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V30/00—Character recognition; Recognising digital ink; Document-oriented image-based pattern recognition
- G06V30/10—Character recognition
- G06V30/19—Recognition using electronic means
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B21—MECHANICAL METAL-WORKING WITHOUT ESSENTIALLY REMOVING MATERIAL; PUNCHING METAL
- B21D—WORKING OR PROCESSING OF SHEET METAL OR METAL TUBES, RODS OR PROFILES WITHOUT ESSENTIALLY REMOVING MATERIAL; PUNCHING METAL
- B21D22/00—Shaping without cutting, by stamping, spinning, or deep-drawing
- B21D22/02—Stamping using rigid devices or tools
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
- G05B19/4183—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM] characterised by data acquisition, e.g. workpiece identification
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/20—Pc systems
- G05B2219/26—Pc applications
- G05B2219/2622—Press
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/37—Measurements
- G05B2219/37563—Ccd, tv camera
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V2201/00—Indexing scheme relating to image or video recognition or understanding
- G06V2201/06—Recognition of objects for industrial automation
Definitions
- the invention relates to a method for operating a press according to the preamble of patent claim 1.
- the invention also relates to a computer program according to patent claim 9.
- the invention relates to an electronically readable data carrier according to patent claim 10.
- DE 102015221 417 A1 shows several methods.
- One of the methods is used to provide individual material parts from a web-shaped semi-finished product, in which at least one part parameter of the web-shaped semi-finished product is determined with precision in an area, the material parts are separated from the web-shaped semi-finished product and are provided with an individual identifier and the individual identifiers of the isolated material parts are provided linked to the respectively determined at least one part parameter.
- Another method is used for processing isolated parts of material, in which individual identifiers of isolated parts of material linked to at least one part parameter are provided, a respective individual identifier of the parts of material is read, the isolated parts of material are processed into respective components and the individual Identifiers of the components linked to respective processing parameters are provided.
- a first aspect of the invention relates to a method for operating a press.
- the press is designed in particular as a forming press and/or cutting press.
- blanks in particular blanks that have been cut, are processed, in particular formed by pressing.
- Each circuit board has a unique serial number. This number is applied, for example, when cutting the blank from a coil in a coil system using a laser engraving process.
- measured values characterizing the respective serial number and thus the respective circuit board, such as a material thickness of the circuit board determined in the coil system are held available.
- the serial number can be a serial number and can be displayed alphanumerically and/or by means of a bar or QR code, for example.
- the method according to the invention provides for recordings to be made by means of a detection device, for example a camera, in an insertion area in which the blank is inserted into the press, in particular for processing, in particular forming of, in particular the entire, serial number.
- a detection device for example a camera
- a recognition unit for example the electronic computing device
- the electronic computing device initiates recognition or recognition of the serial number in the recordings.
- an attempt is made to identify or decipher the recorded serial number so that further parameters, in particular relating to process steps in the press, can be assigned to it in the electronic computing device, for example, in order to enable a particularly advantageous production process.
- the recognition by the recognition unit can be carried out, for example, using a machine vision algorithm, for example an OCR algorithm.
- a recognition rate is then determined for the method according to the invention based on the recognition, which in particular characterizes how many of the serial numbers recorded in particular by the recordings can be recognized.
- determining the recognition rate for example, a recommendation for action to maintain a particularly robust production process can be issued, as a result of which the press can be operated particularly advantageously. For example, an adjustment of the parameters for the laser engraving or the readout cameras and/or a cleaning order can be issued to maintenance as the recommended action.
- the invention is based on the finding that the cutting of the blanks and the subsequent processing in the press are independent process steps, for example in the production of vehicle components made from the blanks in motor vehicle production. Recorded data from the two process steps of cutting the blank and processing in the press are advantageously used to derive recommendations for action. In addition, data on a component quality can also be used to derive the recommended action. For example, process parameters of both process steps and the properties of the associated circuit board are recorded by the electronic computing device. For this purpose, in order to implement the assignment, the blanks are labeled with the serial number or the serial number, in particular during cutting, for example in the coil system.
- the blanks are cut from a so-called coil, i.e. a wound-up metal strip.
- the individual coil can in particular be oiled and thus the blank cut from it is also oiled. Therefore, in order to make the serial number or serial number durable, these are produced by means of laser engraving methods, in particular when cutting the circuit board from the coil. If the circuit board has a zinc layer, for example, this is only slightly roughened, so that if the circuit board is later used to create an outer skin component, the laser engraving could also be applied to a location that is visible from the outside without affecting any paint that may have been applied and with complete preservation the corrosion protection of the zinc layer.
- serial number Based on the serial number, all data associated with the respective circuit board can now be stored, for example, in a database of the electronic computing device.
- this serial number or serial number is read by the recognition device, in particular a camera.
- This camera or detection device is arranged in front of the first press, for example in a press line.
- the press can represent an individual press or an entire press line.
- serial number Based on the serial number, several data, for example process parameters, which arise during the processing of the blank in the press line or press, can also be stored in the database under the recorded and recognized serial number. Thus, the data from both process steps, cutting and subsequent processing in the press, can be linked using the described serial number.
- a crucial step in this context is recognizing the serial number in the insertion area of the press.
- the serial number recognition rate can depend on, for example, the texture, the type of material, the marking quality and the position of the board when reading the serial number in the insertion area. Furthermore, camera and/or lighting settings and the position of the circuit board can influence the recognition rate.
- a production order is, for example, a production cycle in the press, in which, for example, a B-pillar is created from a type of blank.
- the press can be equipped with new tools and thus, for example, produce B-pillars or other components of the vehicle from a different type of circuit board.
- the recognition rate per production process depending on the type of circuit board, and is, for example, 97 percent.
- circuit boards there can also be types of circuit boards in which, for example, due to the properties of the coil system or similar, not all circuit boards can be labeled, so that, for example, only two out of three circuit boards are labeled with the serial number, with a recognition rate of only 65 percent being required, for example .
- a manual random test naturally causes a significant effort.
- the disadvantage of the random test is that a drop in the detection rates, for example during a production cycle or for a type of circuit board, could go undetected, which entails a negative impact on the operation of the press.
- the method according to the invention is therefore based on the idea of automatically detecting and evaluating the recognition rate of all types of circuit boards and, in particular, also transmitting the recognition rate to a monitoring instance, be it human and/or machine-type, the press.
- the method thus enables an objective statistical evaluation.
- this evaluation is carried out adaptively by the method according to the invention, for example by comparing the currently determined recognition rate with recognition rates from the past.
- the monitoring instance can be people and/or systems, for example maintenance, plant personnel and/or a central office.
- the method can be designed in such a way that the current detection rate is determined in relation to a detection rate from the past, and if this falls, for example compared to the past, a warning is automatically issued to the monitoring entity, for example.
- a distribution of the detection rate in the past can be determined by continuous monitoring, for example also depending on the product, and based on this, for example, a lower limit or a lower first limit value and/or a lower further limit value, in particular based on statistical methods, automatically be derived. If the current detection rate falls below this lower limit value, a warning can be issued. The method can thus avoid manual maintenance of limit values, since the limit values are determined automatically.
- the recognition rate can fundamentally change in both directions, the statistically determined limit values are only used, for example, for a defined time window determined.
- the first or each further limit value of the recognition rate reflects a recognition rate of the recent past, for example.
- the lower limit should also increase in the near future. If, in particular, all available data from the past were used, a lower limit value would only increase after many more newly determined recognition rates in the case of the presence of many recognition rates determined in the past.
- the quality of the inscription or the serial number can also deteriorate due to a known change in the supplier of the semi-finished product, in particular the coil.
- the method is advantageously carried out in such a way that the detection rate for the respective detection device of the press is checked separately, in particular in the event that a plurality of detection devices are configured in a press designed as a press line.
- the recognition rate is advantageously determined, for example, by a method or an algorithm of machine learning. For example, the learning algorithm looks up what was determined in the past for the same component or circuit board, which means that the new recognition rate can be classified accordingly.
- the method has the advantage that manual effort for a random check of the recognition rate can be dispensed with. Another advantage is an objective assessment of the recognition rate. This results in further advantages, such as early detection of falling detection rates for individual types of circuit boards. As a further advantage, all types of circuit boards can be monitored for different production orders or production cycles.
- the method according to the invention thus enables an active warning in the event of a deterioration in the detection rate, as a result of which particularly advantageous operation of the press can be made possible.
- the method also offers the advantage of being able to identify systematic changes particularly quickly and objectively. A systematic change would be, for example, if the recognition rates for a supplier's semi-finished product and/or a specific texture changed.
- the recognition rate is determined by comparing the recognized serial numbers with the number of blanks introduced into the press.
- the recognition rate is determined in a particularly simple manner.
- the number of serial numbers correctly recognized by the recognition unit, which are stored in the electronic computing device, for example, is divided by the known number of blanks that are introduced into the press or processed there. This results in the advantage that the method can be carried out particularly simply and thus, for example, particularly efficiently.
- the recognition rate is determined continuously during a production cycle.
- the recognition rate is not only determined at the end of the production cycle, but for example per circuit board introduced. A continuous monitoring of the recognition rate can thus be implemented, as a result of which the press can be operated particularly advantageously.
- a warning signal or an information signal is output if the detection rate deviates from a first limit value, which, for example, as described above, can be defined by a distance from a limit value in the past.
- the warning signal can be output, for example, by the electronic computing device and/or on a display device.
- the first limit value can be specified automatically and/or manually, for example using the list, by the computing device and/or on the basis of earlier recognition rates.
- a warning signal or a warning notice is provided, in particular to a monitoring authority. This results in the advantage that the press can be operated in a particularly fail-safe manner.
- a change in the recognition rate over time is detected.
- the recognition rate is compared with at least one recognition rate from an earlier production cycle.
- a recognition rate determined in the past during a further production order, but in particular with the same type of circuit board, is compared with the currently recorded recognition rate.
- a further limit value is determined on the basis of the comparison of the recognition rates and/or the change in the recognition rate, in particular over time.
- the further limit value can be used as a basis for the following production cycle or cycles.
- the first limit value can, for example, be specified manually by a user of the press
- the further limit value can be determined or determined in particular by a self-learning algorithm or the like, which is carried out, for example, on an electronic computing device.
- a particularly quick detection of a change in the detection rate results as an advantage.
- a further advantage can lie in an automated adaptation of reading parameters, such as, for example, a change in lighting or a change in the position of the camera.
- the advantage can arise that the press can be operated with particularly little user intervention.
- the deviation of the recognition rate, in particular from the first limit value, the change and/or the comparison are determined by means of machine learning and/or by at least one statistical method.
- the first limit value can also be determined by means of machine learning and/or by at least one statistical method.
- the machine learning can be carried out using a self-learning algorithm, for example. Additionally or alternatively, the machine learning can be implemented by a neural network, for example. In addition, a combination of the self-learning algorithm with a neural network is conceivable. In this case, machine learning is implemented, in particular by a self-learning system which, for example, records the algorithm and/or the neural network.
- a second aspect of the invention includes a computer program.
- the computer program can be loaded into a memory of an electronic computing device of a press, for example, and includes program means to carry out the steps of the method when the program is executed in the electronic computing device or a control device of the conveyor system.
- the electronically readable data carrier includes electronically readable control information stored thereon, which includes at least one computer program as just presented or is designed such that it can execute a method presented here when using the data carrier in an electronic computing device of a press.
- FIG. 1 shows a schematic flowchart for a method for operating a press designed for forming blanks in combination with cutting the blanks in a coil system
- Fig. 2 is a schematic flowchart of the method for operating
- Press. 1 shows, in a schematic flowchart, a manufacturing method from the semi-finished product to a component of a motor vehicle.
- a coil system 10 is thus shown schematically, in which blanks are cut from a coil, a metal strip or semi-finished product.
- the individual circuit board is provided with a serial number or serial number in the coil system 10, for example by means of laser engraving, with each circuit board being given a unique serial number.
- the serial number is stored in an electronic computing device 12, for example.
- the measured values or material parameters and/or material properties characterizing the respective circuit board are also stored in a memory area of electronic computing device 12 for the serial number, such as mechanical properties, surface roughness, sheet thickness, oil layer thickness and/or additionally or alternatively process parameters of coil system 10.
- the data just mentioned or material parameters and/or material properties are thus linked to the serial number in the electronic computing device 12 .
- a press 14 is shown schematically, which can include, for example, one or more presses in a press line and is used for forming the blanks, in particular by means of presses.
- a component 16 of a motor vehicle which is embodied as a body component, for example, can be produced by forming or pressing the respective blank.
- a detection device 20 embodied in particular as a camera can be arranged in a loading area 18 of the press 14 , which is embodied to detect the serial numbers of the blanks. Alternatively, multiple cameras or detection devices 20 can also be provided.
- the cutting of the blanks by means of the coil system 10 can be a first process step in the production of the component 16.
- further parameters, in particular process parameters can now be recorded for the serial number.
- These process parameters can be stored by or by means of the electronic computing device 12, for example in a memory area of the electronic computing device 12.
- the process parameters can be, for example, setting parameters for the press, the press table, ambient temperature, humidity, forces acting on the board from the press, etc.
- the component quality of the component 16 produced from the circuit board can also be recorded, with the data that arises also being able to be recorded or stored for the associated serial number by means of the electronic computing device 12 .
- the recording or storage of the material parameters and/or material properties, the process parameters and the component quality is illustrated in each case by the three arrows reaching the electronic computing device 12 in FIG. 1 .
- Process modeling for example, which is illustrated by diagram 22 , can be carried out by electronic computing device 12 .
- a prognosis quality 24 can be output, through which a process control 26 is made possible, which can have a direct influence on the component quality, with a respective influence being exerted by arrows in Fig.
- FIG. 2 shows a schematic flowchart of a method which comprises a number of steps. The method is used to operate the press 14, in which the blanks are formed, each of which has a unique serial number, with measured values characterizing the associated blank being stored in the electronic computing device 12 for the respective serial numbers, as already shown in particular in Fig. 1 was.
- a recording of the serial number is created by means of the detection device 20.
- a recognition unit which is for example a corresponding algorithm of the electronic computing device 12, recognizes the serial numbers in the recordings.
- a recognition rate is determined, which characterizes how many of the recorded serial numbers are actually recognized and are thus identifiable, for example, for further processing in the electronic computing device 12.
- the method for operating the press 14 can be carried out by means of the three steps S1 to S3 mentioned.
- a recommendation for action in particular, for example, for maintaining a robust production process, can be issued.
- a warning signal can be output in step S4 if the recognition rate deviates from a first limit value.
- the first limit value can, for example, also be specified manually, for example, by machine learning using the electronic computing device 12 and/or, for example, in a first production cycle and/or when the press 14 is put into operation again.
- a manual specification of 97 percent can be specified, in particular for the case in which each of the circuit boards has a serial number engraved in particular by laser engraving.
- the recognition rate can advantageously be determined by comparing the recognized serial numbers with the number of blanks introduced into the press 14 .
- the recognition rate is advantageously determined continuously, particularly additionally or alternatively, during a production cycle.
- the production cycle is, for example, a production order in which a type of blank is used, for example, to produce an A-pillar of a motor vehicle, with the press 14 being equipped with appropriate tools or forming tools in this case.
- a production cycle or production order can mean, for example, the manufacture of 1,000 A-pillars from 1,000 circuit boards.
- Another production cycle or production order can, for example, mean or describe the production of 2,000 B-pillars from a different type of blank using a further forming tool or tool set with which the press 14 is equipped.
- the detection rate is compared with at least one detection rate of an earlier production cycle, for example that possible quality losses to be expected in the finished component 16 can be detected at an early stage and the press 14 can therefore be operated particularly advantageously. It is therefore also particularly advantageous if a change in the recognition rate over time is detected or can advantageously be determined in order to be able to evaluate the course of the production process over time, in particular objectively and statistically.
- a further limit value can be determined, which can take place in particular on the basis of the comparison and/or the change over time, in particular by means of machine learning.
- the self-learning algorithm can be executed, for example, in the electronic computing device 12 and/or on a neural network specially designed for this purpose, which can likewise be a component of the electronic computing device 12 .
- Steps S1 to S3 and in particular S1 to S4 of the method can advantageously be carried out by a computer program which is stored directly in a memory of a storage device, for example the electronic computing device 12, the press 14, a separate IOT PC and/or in a central IT Architecture, such as a cloud-based solution, is loadable.
- program means can be suitable for executing steps S1 to S4 of the method if the program is executed in the computing device 12 or in a control device of the press 14 .
- an electronically readable data carrier with electronically readable control information stored on it can be kept if at least one computer program is included and designed such that when the data carrier is used in a control device of a press 14, a method presented here with steps S1 to S3 or S1 to Run S4.
- the method shown allows automatic and individual or product-related monitoring of the recognition rate of serial numbers on circuit boards in press lines in a particularly advantageous manner.
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- Engineering & Computer Science (AREA)
- Mechanical Engineering (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Multimedia (AREA)
- Theoretical Computer Science (AREA)
- Quality & Reliability (AREA)
- General Factory Administration (AREA)
- Numerical Control (AREA)
- Image Analysis (AREA)
Abstract
Description
Claims
Priority Applications (2)
Application Number | Priority Date | Filing Date | Title |
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CN202280027776.5A CN117222518A (zh) | 2021-07-06 | 2022-06-10 | 用于运行压力机的方法、计算机程序和电子可读数据载体 |
US18/558,774 US20240227340A1 (en) | 2021-07-06 | 2022-06-10 | Method for Operating a Press, Computer Program and Electronically Readable Data Carrier |
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
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DE102021117346.9 | 2021-07-06 | ||
DE102021117346.9A DE102021117346A1 (de) | 2021-07-06 | 2021-07-06 | Verfahren zum Betreiben einer Presse, Computerprogramm und elektronisch lesbarer Datenträger |
Publications (1)
Publication Number | Publication Date |
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WO2023280508A1 true WO2023280508A1 (de) | 2023-01-12 |
Family
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Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
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PCT/EP2022/065829 WO2023280508A1 (de) | 2021-07-06 | 2022-06-10 | Verfahren zum betreiben einer presse, computerprogramm und elektronisch lesbarer datenträger |
Country Status (4)
Country | Link |
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US (1) | US20240227340A1 (de) |
CN (1) | CN117222518A (de) |
DE (1) | DE102021117346A1 (de) |
WO (1) | WO2023280508A1 (de) |
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US20110133899A1 (en) * | 2006-01-20 | 2011-06-09 | Sanmina-Sci Corporation | Circuit Board with Radio Frequency Identification for Collecting Stage-by-Stage Manufacturing Metrics |
DE102015221417A1 (de) | 2015-11-02 | 2017-05-04 | Bayerische Motoren Werke Aktiengesellschaft | Bereitstellen von vereinzelten Materialteilen und Verarbeiten solcher Materialteile |
DE102018128498A1 (de) * | 2018-11-14 | 2020-05-14 | Bayerische Motoren Werke Aktiengesellschaft | Verfahren zur Bauteilverfolgung |
WO2020216524A1 (de) * | 2019-04-24 | 2020-10-29 | Bayerische Motoren Werke Aktiengesellschaft | Verfahren zum verfolgen eines bauteils in einer mehrere prozessanlagen umfassenden fertigungslinie sowie recheneinrichtung |
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2021
- 2021-07-06 DE DE102021117346.9A patent/DE102021117346A1/de active Pending
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2022
- 2022-06-10 CN CN202280027776.5A patent/CN117222518A/zh active Pending
- 2022-06-10 US US18/558,774 patent/US20240227340A1/en active Pending
- 2022-06-10 WO PCT/EP2022/065829 patent/WO2023280508A1/de active Application Filing
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US20030049881A1 (en) * | 2001-08-02 | 2003-03-13 | Takeshi Takada | Article to be processed having ID, and production method thereof |
US20110133899A1 (en) * | 2006-01-20 | 2011-06-09 | Sanmina-Sci Corporation | Circuit Board with Radio Frequency Identification for Collecting Stage-by-Stage Manufacturing Metrics |
DE102015221417A1 (de) | 2015-11-02 | 2017-05-04 | Bayerische Motoren Werke Aktiengesellschaft | Bereitstellen von vereinzelten Materialteilen und Verarbeiten solcher Materialteile |
CN107851221A (zh) * | 2015-11-02 | 2018-03-27 | 宝马股份公司 | 分离的材料部件的提供和这样的材料部件的加工 |
DE102018128498A1 (de) * | 2018-11-14 | 2020-05-14 | Bayerische Motoren Werke Aktiengesellschaft | Verfahren zur Bauteilverfolgung |
WO2020216524A1 (de) * | 2019-04-24 | 2020-10-29 | Bayerische Motoren Werke Aktiengesellschaft | Verfahren zum verfolgen eines bauteils in einer mehrere prozessanlagen umfassenden fertigungslinie sowie recheneinrichtung |
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US20240227340A1 (en) | 2024-07-11 |
CN117222518A (zh) | 2023-12-12 |
DE102021117346A1 (de) | 2023-01-12 |
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