EP4413168A1 - Verfahren zur herstellung eines walzproduktes unter optimiertem einsatz von einsatzstoffen - Google Patents
Verfahren zur herstellung eines walzproduktes unter optimiertem einsatz von einsatzstoffenInfo
- Publication number
- EP4413168A1 EP4413168A1 EP22801064.1A EP22801064A EP4413168A1 EP 4413168 A1 EP4413168 A1 EP 4413168A1 EP 22801064 A EP22801064 A EP 22801064A EP 4413168 A1 EP4413168 A1 EP 4413168A1
- Authority
- EP
- European Patent Office
- Prior art keywords
- production
- target
- penalty
- production orders
- costs
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000004519 manufacturing process Methods 0.000 title claims abstract description 104
- 239000004615 ingredient Substances 0.000 title 1
- 238000000034 method Methods 0.000 claims abstract description 55
- XEEYBQQBJWHFJM-UHFFFAOYSA-N Iron Chemical compound [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 claims abstract description 18
- 239000010959 steel Substances 0.000 claims abstract description 10
- 229910000851 Alloy steel Inorganic materials 0.000 claims abstract description 7
- 229910000640 Fe alloy Inorganic materials 0.000 claims abstract description 7
- 229910000838 Al alloy Inorganic materials 0.000 claims abstract description 6
- 230000001276 controlling effect Effects 0.000 claims abstract description 6
- 230000001105 regulatory effect Effects 0.000 claims abstract description 6
- 238000004590 computer program Methods 0.000 claims abstract description 4
- 239000000203 mixture Substances 0.000 claims description 66
- 239000000126 substance Substances 0.000 claims description 40
- 239000000463 material Substances 0.000 claims description 9
- 229910045601 alloy Inorganic materials 0.000 claims description 4
- 239000000956 alloy Substances 0.000 claims description 4
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 claims description 3
- 229910052799 carbon Inorganic materials 0.000 claims description 3
- 239000011248 coating agent Substances 0.000 claims description 3
- 238000000576 coating method Methods 0.000 claims description 3
- 229910052742 iron Inorganic materials 0.000 claims description 3
- 230000005540 biological transmission Effects 0.000 claims 1
- 239000000047 product Substances 0.000 description 38
- 238000005096 rolling process Methods 0.000 description 10
- 238000001816 cooling Methods 0.000 description 7
- CURLTUGMZLYLDI-UHFFFAOYSA-N Carbon dioxide Chemical compound O=C=O CURLTUGMZLYLDI-UHFFFAOYSA-N 0.000 description 6
- 238000010438 heat treatment Methods 0.000 description 6
- 238000009749 continuous casting Methods 0.000 description 4
- 239000011572 manganese Substances 0.000 description 4
- PXHVJJICTQNCMI-UHFFFAOYSA-N Nickel Chemical compound [Ni] PXHVJJICTQNCMI-UHFFFAOYSA-N 0.000 description 3
- 229910000831 Steel Inorganic materials 0.000 description 3
- 229910002092 carbon dioxide Inorganic materials 0.000 description 3
- 238000005266 casting Methods 0.000 description 3
- 230000007547 defect Effects 0.000 description 3
- IJGRMHOSHXDMSA-UHFFFAOYSA-N Atomic nitrogen Chemical compound N#N IJGRMHOSHXDMSA-UHFFFAOYSA-N 0.000 description 2
- PWHULOQIROXLJO-UHFFFAOYSA-N Manganese Chemical compound [Mn] PWHULOQIROXLJO-UHFFFAOYSA-N 0.000 description 2
- 229910000805 Pig iron Inorganic materials 0.000 description 2
- 239000000654 additive Substances 0.000 description 2
- 238000005275 alloying Methods 0.000 description 2
- 239000001569 carbon dioxide Substances 0.000 description 2
- 239000011651 chromium Substances 0.000 description 2
- 239000000109 continuous material Substances 0.000 description 2
- 239000010949 copper Substances 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000005265 energy consumption Methods 0.000 description 2
- 230000001965 increasing effect Effects 0.000 description 2
- 229910052748 manganese Inorganic materials 0.000 description 2
- 239000010955 niobium Substances 0.000 description 2
- 239000002994 raw material Substances 0.000 description 2
- 239000010936 titanium Substances 0.000 description 2
- 101150079616 ARL6IP5 gene Proteins 0.000 description 1
- 101100030586 Arabidopsis thaliana PRA1B3 gene Proteins 0.000 description 1
- ZOXJGFHDIHLPTG-UHFFFAOYSA-N Boron Chemical compound [B] ZOXJGFHDIHLPTG-UHFFFAOYSA-N 0.000 description 1
- VYZAMTAEIAYCRO-UHFFFAOYSA-N Chromium Chemical compound [Cr] VYZAMTAEIAYCRO-UHFFFAOYSA-N 0.000 description 1
- RYGMFSIKBFXOCR-UHFFFAOYSA-N Copper Chemical compound [Cu] RYGMFSIKBFXOCR-UHFFFAOYSA-N 0.000 description 1
- ZOKXTWBITQBERF-UHFFFAOYSA-N Molybdenum Chemical compound [Mo] ZOKXTWBITQBERF-UHFFFAOYSA-N 0.000 description 1
- 102100038660 PRA1 family protein 3 Human genes 0.000 description 1
- OAICVXFJPJFONN-UHFFFAOYSA-N Phosphorus Chemical compound [P] OAICVXFJPJFONN-UHFFFAOYSA-N 0.000 description 1
- 101150093701 SAP2 gene Proteins 0.000 description 1
- XUIMIQQOPSSXEZ-UHFFFAOYSA-N Silicon Chemical compound [Si] XUIMIQQOPSSXEZ-UHFFFAOYSA-N 0.000 description 1
- NINIDFKCEFEMDL-UHFFFAOYSA-N Sulfur Chemical compound [S] NINIDFKCEFEMDL-UHFFFAOYSA-N 0.000 description 1
- ATJFFYVFTNAWJD-UHFFFAOYSA-N Tin Chemical compound [Sn] ATJFFYVFTNAWJD-UHFFFAOYSA-N 0.000 description 1
- RTAQQCXQSZGOHL-UHFFFAOYSA-N Titanium Chemical compound [Ti] RTAQQCXQSZGOHL-UHFFFAOYSA-N 0.000 description 1
- 101100298479 Ustilago maydis PRA2 gene Proteins 0.000 description 1
- 230000002411 adverse Effects 0.000 description 1
- 229910052796 boron Inorganic materials 0.000 description 1
- 238000004422 calculation algorithm Methods 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 229910052804 chromium Inorganic materials 0.000 description 1
- 229910052802 copper Inorganic materials 0.000 description 1
- 238000005520 cutting process Methods 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000005098 hot rolling Methods 0.000 description 1
- 230000001939 inductive effect Effects 0.000 description 1
- 239000000155 melt Substances 0.000 description 1
- 229910052750 molybdenum Inorganic materials 0.000 description 1
- 239000011733 molybdenum Substances 0.000 description 1
- 229910052759 nickel Inorganic materials 0.000 description 1
- 229910052758 niobium Inorganic materials 0.000 description 1
- GUCVJGMIXFAOAE-UHFFFAOYSA-N niobium atom Chemical compound [Nb] GUCVJGMIXFAOAE-UHFFFAOYSA-N 0.000 description 1
- 229910052757 nitrogen Inorganic materials 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 229910052698 phosphorus Inorganic materials 0.000 description 1
- 239000011574 phosphorus Substances 0.000 description 1
- 238000005293 physical law Methods 0.000 description 1
- 238000000053 physical method Methods 0.000 description 1
- 238000005554 pickling Methods 0.000 description 1
- 238000004886 process control Methods 0.000 description 1
- 229910052710 silicon Inorganic materials 0.000 description 1
- 239000010703 silicon Substances 0.000 description 1
- 238000003892 spreading Methods 0.000 description 1
- 229910052717 sulfur Inorganic materials 0.000 description 1
- 239000011593 sulfur Substances 0.000 description 1
- 239000013589 supplement Substances 0.000 description 1
- 229910052719 titanium Inorganic materials 0.000 description 1
- LEONUFNNVUYDNQ-UHFFFAOYSA-N vanadium atom Chemical compound [V] LEONUFNNVUYDNQ-UHFFFAOYSA-N 0.000 description 1
Classifications
-
- C—CHEMISTRY; METALLURGY
- C21—METALLURGY OF IRON
- C21C—PROCESSING OF PIG-IRON, e.g. REFINING, MANUFACTURE OF WROUGHT-IRON OR STEEL; TREATMENT IN MOLTEN STATE OF FERROUS ALLOYS
- C21C5/00—Manufacture of carbon-steel, e.g. plain mild steel, medium carbon steel or cast steel or stainless steel
- C21C5/28—Manufacture of steel in the converter
- C21C5/30—Regulating or controlling the blowing
-
- C—CHEMISTRY; METALLURGY
- C21—METALLURGY OF IRON
- C21C—PROCESSING OF PIG-IRON, e.g. REFINING, MANUFACTURE OF WROUGHT-IRON OR STEEL; TREATMENT IN MOLTEN STATE OF FERROUS ALLOYS
- C21C2300/00—Process aspects
- C21C2300/06—Modeling of the process, e.g. for control purposes; CII
Definitions
- the present invention relates to a method for controlling and/or regulating a metallurgical production plant for producing a rolled product from a metallic steel, iron and/or aluminum alloy, and a computer program product with which the method according to the invention can be carried out.
- Such a process can be, for example, a method for producing a rolled product from a molten steel composition, which is cast in a casting-rolling plant to form a billet and rolled to form the rolled product, with the manufacturing process being controlled by a central control point on the basis of setpoint specifications and/or or is regulated.
- hot rolling includes various consecutive process steps, each of which can influence the mechanical product properties such as yield point, elongation at break or low-temperature behavior.
- the chemical composition of the rolled product or the temperature control during the rolling process also influence the process result. Deviations from the process target values lead to increased energy consumption in the system due to corrective measures to be taken, which has a negative effect on profitability. Furthermore, such deviations can cause expensive complaints.
- European patent EP 3 096 896 B1 discloses a method for controlling a metallurgical production plant using a microstructure model, which includes a program that calculates at least one mechanical strength property of a product that is produced and that calculates the strength property on the basis of calculated metallurgical phase components in the structure of the product that is produced Product calculated, wherein the metallurgical plant includes a final cooling section and operating parameters of the metallurgical plant go into the calculation of the mechanical strength property with at least partially previously set, adjustable output values.
- a solution is created that enables an advantageous adjustment of operating parameters to achieve desired mechanical strength properties of a product made of a metallic steel and/or iron alloy.
- the present invention is therefore based on the object of providing a method for controlling and/or regulating a metallurgical production plant which, in addition to more flexible production planning, enables the utilization and linking of available process data, measured values and the consideration of prices for the raw materials to be used in each case .
- the object is achieved by a method having the features of claim 1.
- the method according to the invention for controlling and/or regulating a metallurgical production plant for producing a rolled product from a metallic steel, iron and/or aluminum alloy comprises the following steps: First, a list of production orders for the production of rolled products, such as different coils, is provided. In such a production plant, these can preferably be managed by a control point or a higher level of production planning. Each of the production orders includes at least specific target values for material, surface and/or geometric properties, each of these specific target values having a minimum specific target value and a maximum specific target value. As a result, a range is thus defined in which the respective specific target setpoint values can move in order to achieve the product properties specified for the respective rolled product.
- specific target values is understood to mean product specification data that ultimately characterizes the respective rolled product that is produced and that this should then have.
- the specific target values are therefore advantageously selected from the series comprising the length, the width, the thickness, the yield point, the tensile strength, the elongation, the toughness properties, the layer thickness of a coating, the magnetic properties and/or a combination thereof.
- each of the production orders is defined via a series of chemical compositions, the respective components of which each include a minimum target potential value and a maximum target potential value.
- these differ and can, for example, be selected from the series comprising the elements carbon (C), manganese (Mn), silicon (Si), phosphorus (P), sulfur (S), nitrogen (N), chromium (Cr ), molybdenum (Mo), nickel (Ni), copper (Cu), lead (Pb), boron (B), tin (Zn), niobium (Nb), titanium (Ti), vanadium (V) and/or combinations of this.
- a selection of chemical compositions is then determined from each of the production orders, the respective compositions of which lie within an approved quality window across all production orders and could therefore in principle be melted in one batch.
- predictive specific target actual values for at least one of the material, surface and/or geometric properties are determined for each of the chemical compositions of each production order with the aid of one or more process models.
- process model is understood to mean a mathematical algorithm with which a value, in this case the predictive specific actual target value, is calculated on the basis of the chemical composition and, if applicable, other process parameters that can influence the respective rolled product and can therefore be predicted .
- the other process parameters that can influence the respective rolled product during production include, for example, the temperatures and/or dimensions of the rolled product in the individual process steps, the temperatures in the heating, heating and/or cooling devices of the plant, and/or qualitative parameters , such as in particular surface defects on the rolled product. All of these parameters can be measured at several measuring points within the course of the process or the system and can therefore be calculated in advance from each of these measuring points using a corresponding process model.
- the process models are therefore advantageously selected from the group comprising temperature models, structural models, deformation process models,
- Plant stability models prediction models for the number and/or area and/or strength of scale defects and/or cracks, spreading models, prediction models for mechanical properties, such as in particular for the yield point, tensile strength, elongation and/or toughness properties.
- the respective process models can be formed from individual models, so that each of the individual models describes a specific part of the plant. Additionally and/or alternatively, the process models or the individual models can also be part of an integrated, unit-spanning model that describes the entire system.
- the determined predictive specific actual target values are then compared with the specific target values of the respective production orders, with those chemical compositions being selected and forming the selection for which the condition is met that the predictive specific actual target values are in the specific target value range.
- a Penalty point and/or a penalty function determined for each of the allowed chemical compositions, ie for each chemical composition of the selection of each production order.
- the penalty point and/or the penalty function can additionally include at least one process parameter.
- the term “penalty point and/or penalty function” is understood to be a dimensionless variable that represents a measure of the production costs of the respective permitted chemical composition.
- Such a penalty point and/or such a penalty function consists of at least one of the cost parameters selected from the series including alloy costs, scrap costs, energy costs, iron costs, costs for additives, carbon dioxide costs and/or a combination thereof.
- the production costs are determined for each of the permitted chemical compositions of each production order. Since several production orders can usually be melted in a common batch, for example a ladle, a target composition for a selection of production orders that are to be melted in the common batch is then determined on the basis of this finding.
- an intersection of chemical compositions is determined from the selection of those chemical compositions of each production order that forms the combination, with the penalty points and/or the penalty function of the chemical compositions of each intersection are added, and that chemical composition forms the target composition whose total penalty points have the smallest value.
- the target composition then obtained for the combination of production orders is then transmitted to a control point and/or a production planning level, whereupon the batch is melted in a steelworks and then made available to the plant.
- the present invention thus enables an optimized use of raw materials in the production of rolled products from a metallic steel, iron and/or aluminum alloy by optimizing the chemical composition as a function of a cost function and taking qualitative specifications into account.
- Further advantageous refinements of the invention are specified in the dependently formulated claims.
- the features listed individually in the dependent claims can be combined with one another in a technologically meaningful manner and can define further refinements of the invention.
- the features specified in the claims are specified and explained in more detail in the description, with further preferred configurations of the invention being presented.
- variants can be formed from the respective target compositions of the possible combinations of production orders, with that variant then being selected and processed whose total penalty points have the lowest value.
- the order of the individual batches or the individual variants can be coordinated with one another in terms of their target composition.
- each of the production orders for each of the rolled products to be produced can also include product information data.
- product information data is understood to be primary data that is sent from a production planning level to the control point, which in turn controls and/or regulates the entire manufacturing process.
- the product information data therefore advantageously includes set value sets for the regulation and/or control of the individual system components, in particular their hydraulic and/or electronic control systems. This can be done either table-oriented and/or using mathematical-physical process models.
- the present invention also relates to a computer program product, comprising software code sections and/or instructions which, when the program is executed by a computer, cause the latter to carry out the steps according to the method according to the invention.
- FIG. 2 shows a diagram of the process sequence based on an exemplary embodiment which can be carried out using a metallurgical production plant according to FIG.
- FIG. 1 shows an embodiment variant of a metallurgical production plant 1 with which the method according to the invention can be carried out.
- the production plant 1 comprises a steelworks 2 and a casting and rolling plant 3, which is in the form of a CSP® plant in the present case.
- the system 3 comprises a continuous casting machine 4, preferably a CSP® thin slab casting machine, with which a continuous material 5 with a thickness in the range of 30-150 mm, preferably with a thickness in the range of 50 to 90 mm, and a width in the range of 500 to 2500 mm, preferably with a width of 850 to 1950 mm.
- a separating device 6 is arranged downstream of the continuous casting machine 4 in the direction of strip travel, with which the continuous material 5 is separated into individual slabs 7 before it is fed to the rolling mill.
- the separating device 6 can consist, for example, of pendulum shears.
- the system 3 also includes a heating device 8, which can be designed as a tunnel furnace, and a finishing rolling train 9 with a specific number of roll stands 10, three of which are shown in FIG. 1 purely as an example. In a CSP® plant, the finishing train 9 can preferably also have 4 to 8 roll stands.
- the system 3 first includes a cooling device 11, by means of which a the desired final strip thickness of rolled hot strip 12 is cooled, a coiling device 13, and a second cutting device 14 arranged between the cooling device 11 and the coiling device 13.
- the system 3 can also have a roughing train 15 with preferably up to three roll stands, a transfer bar cooling device, a further heating device, a heating device, which can preferably be inductive, and/or an upsetting device with at least one, preferably several upsetting stands , include.
- the production plant 1 also includes a production planning level 17 that is higher than the control point 16 and in which the production orders P intended for production are managed, in this case the production orders 18, 19, 20, 21.
- each of the production orders 18, 19, 20, 21 includes specific target values 181, 191, 201, 211 for the respective rolled product to be produced, product information data 182, 192, 202, 212, and is also a series of chemical compositions 183, 193, 203, 213 defined.
- the specific target values 181, 191, 201, 211 are each described by a minimum specific target value and a maximum specific target value and can have geometric properties such as length, width and/or thickness; Material properties, such as yield point, tensile strength, elongation, toughness properties and/or other mechanical properties; and/or surface properties, such as surface defects and/or coating systems, of the rolled product 12.
- the series of chemical compositions 183, 193, 203, 213 also includes a minimum and a maximum target value for each of the chemical components, as shown in FIG.
- the series of chemical compositions 183, 193, 203, 213 of each production order 18, 19, 20, 21 from the two chemical Components manganese (Mn) and carbon (C) formed, each in different amounts (in wt %) can form the respective composition a to y.
- the product information data 182, 192, 202, 212 include for the respective rolled product 12 sets of setpoints for the regulations and / or control of the individual system components, such as the temperature that must be maintained after each of the individual units and / or after each of the process steps within the manufacturing process .
- a specific melt is usually first melted in the steel works 2 and is then made available to the plant 3 .
- Such melts are usually composed of pig iron 22, scrap 23 and alloying elements 24, which are subject to market price fluctuations.
- deviations from the process target values due to the corrective measures then to be taken can increase the energy consumption of the plant 1 and have an adverse effect in terms of its economic efficiency, for example by the width of the slab 7 produced being often adjusted within the production process or in downstream lines, such as in a pickling line, must be trimmed.
- a target composition 25 is first determined from the entire list of production orders 18, 19, 20, 21 for a selection of production orders whose total penalty points have the lowest value and those in the common Charge 26, which can have the volume of a ladle, for example, melted and then the system 3 can be provided.
- a selection of chemical compositions 27, 28, 29, 30 (FIG. 2; step b)) of each of the production orders 18, 19, 20, 21 is first determined by a ...y of each production order 18, 19, 20, 21 with the aid of a process model 31 predictive specific actual target values 184, 194, 204, 214 are determined for at least one of the material, surface and/or geometric properties.
- This at least one property can be the tensile strength, for example.
- the present process model 31 is presently designed as a unit-wide model, which in addition to the prediction model for mechanical properties 32, in particular the tensile strength, additionally includes a temperature model 33 and a forming process model 34.
- the temperature model 33 takes into account the temperatures in the plant components 8 and 11
- the forming process model 34 takes into account the rolling forces for the rolling train 9 and possibly for the roughing rolling train 15.
- the predictive specific target actual values 184, 194, 204, 214 determined by the control point 16 are then transmitted to the production planning level 17 and compared with the specific target setpoints 181, 191, 201, 211 of the respective production orders 18, 19, 20, 21, with those chemical Compositions are selected, and form the selection 27, 28, 29, 30 for which the condition is met that the predictive specific actual target values 184, 194, 204, 214 are in the specific target setpoint range.
- a penalty point and/or a penalty function is then determined for each of the permitted chemical composition of the selection 27, 28, 29, 30, which consists of at least one of the cost parameters selected from the series comprising alloy costs, scrap costs, energy costs, iron costs, costs for additives, carbon dioxide costs and/or a combination thereof (Fig. 2; step c)).
- the composition g1 for the production order 18 forms the smallest penalty point.
- the composition h2 forms the smallest penalty point.
- the compositions s3 and v4 have the smallest penalty point.
- an intersection 35, 36 , 37, 38, 39, 40 are determined from the selection of those chemical compositions 27, 28, 29, 30 of each production order 18, 19, 20, 21 forming the combination, with the penalty points and/or the penalty function of these chemical compositions being one each intersection 35, 36, 37, 38, 39, 40 are then added.
- the combination K1 is made up of the two
- That chemical composition whose total penalty points has the lowest value then forms the target composition 25, 25.1, which can be transmitted to the production planning level 17, whereupon the batch 26 is melted in the steelworks 2 and the plant 3 is made available.
- variants V1, V2 , V3 are formed for the same or similar chemical compositions (see step e1)).
- the variant V1, V2, V3 is selected and processed whose total penalty points have the lowest value.
- variant 1 consisting of K1 and K6
- variant 1 consisting of K1 and K6
- the production planning level 17 whereupon the charge 26 is melted in the steelworks 2 and then made available to the plant 3, for example by feeding it to the mold of the continuous casting machine 4 and closing it the strand material 5 is cast.
Landscapes
- Engineering & Computer Science (AREA)
- Chemical & Material Sciences (AREA)
- Manufacturing & Machinery (AREA)
- Materials Engineering (AREA)
- Metallurgy (AREA)
- Organic Chemistry (AREA)
- General Factory Administration (AREA)
Abstract
Description
Claims
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| DE102021211320.6A DE102021211320A1 (de) | 2021-10-07 | 2021-10-07 | Verfahren zur Herstellung eines Walzproduktes unter optimiertem Einsatz von Einsatzstoffen |
| PCT/EP2022/077916 WO2023057614A1 (de) | 2021-10-07 | 2022-10-07 | Verfahren zur herstellung eines walzproduktes unter optimiertem einsatz von einsatzstoffen |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| EP4413168A1 true EP4413168A1 (de) | 2024-08-14 |
Family
ID=84329836
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| EP22801064.1A Pending EP4413168A1 (de) | 2021-10-07 | 2022-10-07 | Verfahren zur herstellung eines walzproduktes unter optimiertem einsatz von einsatzstoffen |
Country Status (3)
| Country | Link |
|---|---|
| EP (1) | EP4413168A1 (de) |
| DE (1) | DE102021211320A1 (de) |
| WO (1) | WO2023057614A1 (de) |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE102014224461A1 (de) | 2014-01-22 | 2015-07-23 | Sms Siemag Ag | Verfahren zur optimierten Herstellung von metallischen Stahl- und Eisenlegierungen in Warmwalz- und Grobblechwerken mittels eines Gefügesimulators, -monitors und/oder -modells |
-
2021
- 2021-10-07 DE DE102021211320.6A patent/DE102021211320A1/de active Pending
-
2022
- 2022-10-07 WO PCT/EP2022/077916 patent/WO2023057614A1/de not_active Ceased
- 2022-10-07 EP EP22801064.1A patent/EP4413168A1/de active Pending
Also Published As
| Publication number | Publication date |
|---|---|
| DE102021211320A1 (de) | 2023-04-13 |
| WO2023057614A1 (de) | 2023-04-13 |
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