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WO2024149879A1 - Appareil et procédé de classification d'une poudre métallique - Google Patents

Appareil et procédé de classification d'une poudre métallique Download PDF

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Publication number
WO2024149879A1
WO2024149879A1 PCT/EP2024/050696 EP2024050696W WO2024149879A1 WO 2024149879 A1 WO2024149879 A1 WO 2024149879A1 EP 2024050696 W EP2024050696 W EP 2024050696W WO 2024149879 A1 WO2024149879 A1 WO 2024149879A1
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WO
WIPO (PCT)
Prior art keywords
metal powder
illumination
unit
different
image data
Prior art date
Application number
PCT/EP2024/050696
Other languages
German (de)
English (en)
Inventor
Clemens MAUCHER
Jonas GEROLD
Hans-Christian Möhring
Original Assignee
Universität Stuttgart
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Universität Stuttgart filed Critical Universität Stuttgart
Publication of WO2024149879A1 publication Critical patent/WO2024149879A1/fr

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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B22—CASTING; POWDER METALLURGY
    • B22F—WORKING METALLIC POWDER; MANUFACTURE OF ARTICLES FROM METALLIC POWDER; MAKING METALLIC POWDER; APPARATUS OR DEVICES SPECIALLY ADAPTED FOR METALLIC POWDER
    • B22F10/00—Additive manufacturing of workpieces or articles from metallic powder
    • B22F10/20—Direct sintering or melting
    • B22F10/28—Powder bed fusion, e.g. selective laser melting [SLM] or electron beam melting [EBM]
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B22—CASTING; POWDER METALLURGY
    • B22F—WORKING METALLIC POWDER; MANUFACTURE OF ARTICLES FROM METALLIC POWDER; MAKING METALLIC POWDER; APPARATUS OR DEVICES SPECIALLY ADAPTED FOR METALLIC POWDER
    • B22F1/00—Metallic powder; Treatment of metallic powder, e.g. to facilitate working or to improve properties
    • B22F1/05—Metallic powder characterised by the size or surface area of the particles
    • B22F1/052—Metallic powder characterised by the size or surface area of the particles characterised by a mixture of particles of different sizes or by the particle size distribution
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B22—CASTING; POWDER METALLURGY
    • B22F—WORKING METALLIC POWDER; MANUFACTURE OF ARTICLES FROM METALLIC POWDER; MAKING METALLIC POWDER; APPARATUS OR DEVICES SPECIALLY ADAPTED FOR METALLIC POWDER
    • B22F10/00—Additive manufacturing of workpieces or articles from metallic powder
    • B22F10/30—Process control
    • B22F10/34—Process control of powder characteristics, e.g. density, oxidation or flowability
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B22—CASTING; POWDER METALLURGY
    • B22F—WORKING METALLIC POWDER; MANUFACTURE OF ARTICLES FROM METALLIC POWDER; MAKING METALLIC POWDER; APPARATUS OR DEVICES SPECIALLY ADAPTED FOR METALLIC POWDER
    • B22F10/00—Additive manufacturing of workpieces or articles from metallic powder
    • B22F10/70—Recycling
    • B22F10/73—Recycling of powder
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B22—CASTING; POWDER METALLURGY
    • B22F—WORKING METALLIC POWDER; MANUFACTURE OF ARTICLES FROM METALLIC POWDER; MAKING METALLIC POWDER; APPARATUS OR DEVICES SPECIALLY ADAPTED FOR METALLIC POWDER
    • B22F10/00—Additive manufacturing of workpieces or articles from metallic powder
    • B22F10/80—Data acquisition or data processing
    • B22F10/85—Data acquisition or data processing for controlling or regulating additive manufacturing processes
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B22—CASTING; POWDER METALLURGY
    • B22F—WORKING METALLIC POWDER; MANUFACTURE OF ARTICLES FROM METALLIC POWDER; MAKING METALLIC POWDER; APPARATUS OR DEVICES SPECIALLY ADAPTED FOR METALLIC POWDER
    • B22F12/00—Apparatus or devices specially adapted for additive manufacturing; Auxiliary means for additive manufacturing; Combinations of additive manufacturing apparatus or devices with other processing apparatus or devices
    • B22F12/90—Means for process control, e.g. cameras or sensors
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B33—ADDITIVE MANUFACTURING TECHNOLOGY
    • B33Y—ADDITIVE MANUFACTURING, i.e. MANUFACTURING OF THREE-DIMENSIONAL [3-D] OBJECTS BY ADDITIVE DEPOSITION, ADDITIVE AGGLOMERATION OR ADDITIVE LAYERING, e.g. BY 3-D PRINTING, STEREOLITHOGRAPHY OR SELECTIVE LASER SINTERING
    • B33Y40/00—Auxiliary operations or equipment, e.g. for material handling
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B33—ADDITIVE MANUFACTURING TECHNOLOGY
    • B33Y—ADDITIVE MANUFACTURING, i.e. MANUFACTURING OF THREE-DIMENSIONAL [3-D] OBJECTS BY ADDITIVE DEPOSITION, ADDITIVE AGGLOMERATION OR ADDITIVE LAYERING, e.g. BY 3-D PRINTING, STEREOLITHOGRAPHY OR SELECTIVE LASER SINTERING
    • B33Y50/00—Data acquisition or data processing for additive manufacturing
    • B33Y50/02—Data acquisition or data processing for additive manufacturing for controlling or regulating additive manufacturing processes
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B33—ADDITIVE MANUFACTURING TECHNOLOGY
    • B33Y—ADDITIVE MANUFACTURING, i.e. MANUFACTURING OF THREE-DIMENSIONAL [3-D] OBJECTS BY ADDITIVE DEPOSITION, ADDITIVE AGGLOMERATION OR ADDITIVE LAYERING, e.g. BY 3-D PRINTING, STEREOLITHOGRAPHY OR SELECTIVE LASER SINTERING
    • B33Y70/00—Materials specially adapted for additive manufacturing
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    • G01N15/02—Investigating particle size or size distribution
    • G01N15/0205—Investigating particle size or size distribution by optical means
    • G01N15/0227—Investigating particle size or size distribution by optical means using imaging; using holography
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    • G01N15/1433—Signal processing using image recognition
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    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/47—Scattering, i.e. diffuse reflection
    • G01N21/4738—Diffuse reflection, e.g. also for testing fluids, fibrous materials
    • G01N21/474—Details of optical heads therefor, e.g. using optical fibres
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/85—Investigating moving fluids or granular solids
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
    • G01N15/10—Investigating individual particles
    • G01N15/14—Optical investigation techniques, e.g. flow cytometry
    • G01N2015/1493—Particle size
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
    • G01N21/314—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry with comparison of measurements at specific and non-specific wavelengths
    • G01N2021/3155—Measuring in two spectral ranges, e.g. UV and visible
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
    • G01N21/314—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry with comparison of measurements at specific and non-specific wavelengths
    • G01N2021/3181—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry with comparison of measurements at specific and non-specific wavelengths using LEDs
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/47—Scattering, i.e. diffuse reflection
    • G01N21/4738—Diffuse reflection, e.g. also for testing fluids, fibrous materials
    • G01N21/474—Details of optical heads therefor, e.g. using optical fibres
    • G01N2021/4752—Geometry
    • G01N2021/4759—Annular illumination
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/47—Scattering, i.e. diffuse reflection
    • G01N21/4738—Diffuse reflection, e.g. also for testing fluids, fibrous materials
    • G01N2021/4764—Special kinds of physical applications
    • G01N2021/4769—Fluid samples, e.g. slurries, granulates; Compressible powdery of fibrous samples
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/85—Investigating moving fluids or granular solids
    • G01N2021/8592—Grain or other flowing solid samples
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2201/00—Features of devices classified in G01N21/00
    • G01N2201/06—Illumination; Optics
    • G01N2201/062—LED's
    • G01N2201/0627—Use of several LED's for spectral resolution
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2201/00—Features of devices classified in G01N21/00
    • G01N2201/12—Circuits of general importance; Signal processing
    • G01N2201/129—Using chemometrical methods
    • G01N2201/1296—Using chemometrical methods using neural networks
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N25/00—Investigating or analyzing materials by the use of thermal means
    • G01N25/72—Investigating presence of flaws
    • G—PHYSICS
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    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/20—Metals

Definitions

  • the invention relates to a device and a method for classifying a metal powder.
  • Additive manufacturing processes include a variety of technologies in which components are built up layer by layer based on a pre-programmed 3D data model.
  • the advantage of these processes is that CAD data can be transferred into a component directly, quickly and without special tools.
  • the entire component is manufactured in one step, in contrast to conventional manufacturing processes, which usually require several consecutive manufacturing steps to produce the component.
  • the properties of the metal powder used play a decisive role in the properties and quality of the manufactured component.
  • the most important parameters of the metal powder include particle size distribution in a build chamber, flowability of the metal powder, specific surface area and solid density of the metal powder - especially when using metal powder that has already been used but not melted, it is crucial to know the quality of the metal powder.
  • So-called metal powder recycling is playing an increasingly important role in metal 3D printing, particularly due to increased costs for raw materials, supply bottlenecks and sustainability aspects.
  • Usually, during a metal 3D printing process only a certain amount of the metal powder in the build space is used to produce the manufactured component. A large amount of metal powder is therefore unused after the component has been completed and could be reused for another metal 3D printing process.
  • the problem here is that the metal powder to be recycled is affected in an unknown way and to varying degrees by the previous metal 3D printing process.
  • the energy input in and around a melting point of the metal powder during a metal 3D printing process is significantly higher than in areas further away from the pain point. Accordingly, the metal powder close to the component has to absorb more energy and heat than metal powder further away from the component.
  • a metal 3D printing process can result in a non-homogeneous mixture of the metal powder, meaning that it cannot be used without further processing of the metal powder.
  • WO 2020/229838 A1 discloses a method and apparatus for analyzing a metal powder for use in an additive manufacturing process.
  • US 2018/200957 A1 discloses a powder bed-based additive manufacturing of a component in a powder bed.
  • an apparatus for classifying a metal powder comprising:
  • the lighting unit has at least one lighting means, preferably a plurality of lighting means, which are arranged in particular around the metal powder, with which the metal powder can be illuminated from different lighting angles, preferably horizontal angles, and with different light wavelengths;
  • an image recording unit for recording image data of the metal powder illuminated by the illumination unit from the different illumination angles, preferably horizontal angles, and the different light wavelengths and
  • processing device for processing the image data, wherein the processing device is operatively connected to the image recording unit by means of signals, so that the processing device can process the metal powder based on the image data transmitted by the image acquisition unit.
  • Embodiments of the invention could have the advantage that metal powders can be characterized in a simple but reliable manner. Compared to common analysis methods for determining powder quality, such as determining an angle of repose, Hall flow meter measurements, determining the flowability of the metal powder, determining particle sizes of the metal powder or scanning electron microscopy measurements, the device in question could significantly simplify the determination. For example, in-situ characterization could be possible without having to rely on a special preparation of the powder for this purpose (such as, in particular, for carrying out scanning electron microscopy measurements).
  • Embodiments could further have the advantage that the large number of lighting devices arranged around the metal powder enables the metal powder to be illuminated from all possible horizontal angles between 0° and 360°. This could enable a particularly precise determination of the particle size and the degree of degradation, since metal powder particles are illuminated from a large number of horizontal directions regardless of the viewing angle and optimal, representative illumination of the metal powder particles is ensured.
  • illuminating the metal powder with different wavelengths of light from all possible horizontal angles between 0° and 360° could enable precise characterization of specific properties of the illuminated metal powder, in particular oxide layers of the metal powder as an indication of degradation or particle size distributions.
  • the device according to the invention is, for example, in an optical operative connection to a powder feed stream of the metal powder that supplies the device with metal powder, so that on the one hand the lighting unit can illuminate the powder feed stream of the metal powder, and on the other hand the image recording unit can record the image data from the powder feed stream of the metal powder thus illuminated.
  • the metal powder can be classified immediately before a metal 3D printing process or a powder metallurgical manufacturing process, whereby an unsuitable portion of the metal powder can be exchanged and disposed of before processing in the respective metal 3D printing process or manufacturing process; preliminary examinations of samples of the metal powder are therefore no longer absolutely necessary.
  • this aspect of the device according to the invention increases the degree of utilization of the metal powder used in a sustainable and efficient manner.
  • the lighting unit enables the metal powder to be illuminated from different vertical lighting angles. Different vertical lighting angles could further improve the shadows cast by the different particles of the metal powder and enable the creation of closed reflection points, which could enable improved detection of a particle size distribution of the metal powder in the image data recorded with the image recording unit.
  • the metal powder can be illuminated from the same horizontal angle with different monochromatic or non-monochromatic light wavelengths.
  • Examples could have the advantage that the metal powder illuminated with varying light spectra emits different light depending on its condition (degradation, particle size), which in turn can be detected by the camera used, thus enabling an easier and clearer characterization of the specific properties, such as the oxide layers as an indication of degradation or a particle size distribution, of the illuminated metal powder.
  • the lighting unit advantageously comprises a plurality of lighting means which are arranged in the vicinity of the metal powder and fixed to the lighting unit in such a way that the metal powder can be correctly illuminated at least in certain areas.
  • the metal powder usually consists of particles of different sizes; the particle size distribution describes the distribution of the different sized particles in the total amount of metal powder.
  • the metal powder comes into contact with oxygen, for example, during the metal 3D printing process.
  • the additional oxygen and the thermal energy for example from a laser beam, cause an oxidation layer to form on the particle surface, which increases the oxygen content after each printing process.
  • Titanium alloys Ti-5AI-5Mo-5V-1 Cr-1 Fe or Ti-6A1 -2Mo-1 ,5Cr-2Zr- 2Sn-2Nb form oxide layers of different colors at certain temperatures. For example, a yellowish/golden TiO layer forms at 500°C, and a bluish Ti2O3 layer forms at 600°C. Violet discoloration was also observed at 550°C. In terms of mechanical properties, it is known that blue-colored oxide layers should be considered a critical color between acceptable and unacceptable tensile properties.
  • the at least one light source of the lighting unit can illuminate the metal powder with different light wavelengths at the same time
  • the image recording unit is designed to record the image data of the metal powder illuminated by the light sources of the lighting unit from different illumination angles and with different light wavelengths.
  • the image data can be real-time recordings in the form of video data or images recorded at time intervals, which are each made available to the processing device as image data.
  • the image recording unit is designed to capture microscopic images and images, for example, so that resolutions in the pm range are possible in order to be able to capture a sufficient number of particles of the metal powder. Tests revealed advantageous resolutions of approximately 10pm to over 200pm.
  • the processing device processes the image data received from the image recording unit to such an extent that, for example, a comparison can be made between the image data recorded in an operating state and the training image data recorded in a training state. Based on the image data of the metal powder recorded from different illumination angles and with different light wavelengths, the processing device is able to draw conclusions about the properties of the metal powder and to classify the metal powder on which the image data is based.
  • the device according to the invention with the processing device can determine a particle size distribution of the metal powder from the image data and detect oxide layers of the metal powder, so that a classification of the metal powder is possible on the basis of training image data recorded in the training state - tests showed good classification results for metal powders such as tin bronze, stainless steel, iron, hot-work steel and titanium.
  • the advantage of the invention could be a cost-effective classification of the metal powder during the manufacturing process of a component from the metal powder, whereby each layer of the metal powder can be qualified separately before processing.
  • the device further comprises a control unit, wherein the control unit is designed to synchronously control the illumination unit and the image recording unit for illuminating the metal powder based on an illumination specification and recording the image data, wherein the illumination specification comprises the illumination from the different illumination angles and with the different light wavelengths.
  • the control unit is designed to synchronously control the illumination unit and the image recording unit for illuminating the metal powder based on an illumination specification and recording the image data, wherein the illumination specification comprises the illumination from the different illumination angles and with the different light wavelengths.
  • the lighting specification can be a temporal sequence, preferably a temporal sequence of the lighting with lighting steps from the different lighting angles and the different light wavelengths, and/or a combined use of the lighting means used in the lighting unit, whereby on the one hand the metal powder is illuminated simultaneously from a subset of the various possible lighting angles with various possible light wavelengths, and on the other hand these subsets themselves can be different and can vary over time during an illumination process.
  • Predetermined and advantageous lighting specifications can be identified in the training state for various metal powders and then used in the operating state to achieve an improved classification of the metal powder.
  • one embodiment of the invention can provide that the lighting means of the lighting unit are arranged symmetrically, preferably point-symmetrically, around the image recording unit.
  • several lighting means of the lighting unit can form a lighting ring, with several lighting rings with different ring diameters being arranged at a different distance from the metal powder.
  • the image recording unit is preferably arranged in a central region of the lighting rings and fixed to them, with the lighting rings being arranged concentrically around the image recording unit in this example.
  • the metal powder can be evenly illuminated in one area by the lighting unit and image data can be recorded by the image recording unit at the same time.
  • the lamps of the lighting unit can form one or more lighting rectangles or triangles, whereby a combination of lighting rings, rectangles and/or triangles is also conceivable.
  • the lighting unit and the image recording unit can consist of a microscope in which the (LED) lamps are integrated.
  • a computing unit has a computing unit, wherein a computing unit is designed to execute a trained classification algorithm for classification, which carries out the classification of the metal powder based on the recorded image files, wherein the results of the Classification includes information about a metal powder type.
  • the metal powder type includes a chemical composition of the metal powder and/or information about a degradation of the metal powder.
  • Executing the trained classification algorithm could have the advantage of providing an improved classification of a metal powder, which contains information about the chemical composition or chemical structure of the metal powder as well as information about the quality or degradation of the metal powder.
  • the classification algorithm could thus provide a simple, cost-effective, fast and automated way of obtaining important information about a metal powder (composition, quality) in order to decide, for example, whether and for what purpose the metal powder can be used in the future.
  • an assisting classification of the metal powder can be provided, which classifies the metal powder on the basis of a recorded particle size distribution of the metal powder and detected oxide layers of the metal powder, wherein the particle size distribution is determined by an analysis of the image data recorded with the image recording unit during illumination of the metal powder by the illumination unit with white light, and wherein the oxide layers are determined by an analysis of the image data recorded with the image recording unit during illumination of the metal powder by the illumination unit with colored light, in particular violet light.
  • the white light When the metal powder is illuminated by white light, the white light is scattered in different directions by the particles of the metal powder depending on the illumination angle of the white light, so that only a portion of the white light is scattered back in the direction of the image recording unit at a favorable scattering angle and can be recorded by the image recording unit.
  • the particle size of the metal powder and the illumination angle influence the amount of light that is scattered by the particles to the image recording device.
  • the image data have white areas of different sizes that directly correlate with the particle size of the particles, whereby Spaces between the white areas are dark.
  • the assisted classification includes an assignment of the particle size distribution recorded from the image data and detected oxide layers to a metal powder known from training.
  • the assignment could have the advantage of assisting in the assignment of the examined metal powder to a known metal powder by comparing the particle size distribution and the detected oxide layers.
  • the assisted classification thus provides a simple, cost-effective, fast and automated way of verifying the results of the classification.
  • the metal powder can be illuminated with the white light at a steeper illumination angle, preferably a steeper vertical illumination angle, than the illumination with the colored light.
  • the illumination angles can be in a lower range of 20° to 40° up to an upper range of 60° to 80° to the metal powder.
  • Colored light can correspond to monochromatic light with a limited light wavelength range, which is not necessarily limited to the light wavelength ranges visible to humans, but can also correspond to an infrared or ultraviolet light wavelength range - all types of LEDs and laser LEDs are therefore also included in colored light-emitting sources.
  • White light corresponds to a non-monochromatic light wavelength range, which therefore includes large light wavelength ranges visible to humans. Accordingly, white light can include a large light wavelength range, for example with a light wavelength of 300 nm to 800 nm.
  • the types of metal powder to be classified determine which light wavelength ranges in the image data recorded with the image recording unit allow conclusions to be drawn about the illuminated metal powder.
  • lighting resulting from the different light wavelengths comprises at least two or more of the following light spectra: white light, violet light, infrared light, UV light. It is therefore optionally possible for the lighting means to comprise LEDs and optionally a laser. In practice, laser LEDs with a light wavelength range of around 750 nm have proven to be effective.
  • the classification algorithm comprises an artificial neural network, in particular a convolutional neural network.
  • an artificial neural network in particular a convolutional neural network.
  • convolutional neural networks can advantageously be used according to the invention to classify the multispectrally illuminated metal powder.
  • the artificial neural network must be In the training state, the metal powders to be classified are taught and trained, which is usually done using test image data of known metal powders.
  • a VGG16 model for the artificial neural network proved to be sufficiently efficient.
  • a VGG19 model can also be used.
  • the lighting unit is designed to illuminate the metal powder in a lighting area
  • the image recording unit is designed to record the image data in the lighting area
  • the lighting unit has a plurality of illuminants arranged offset and spaced from one another, wherein in particular due to the offset and the spacing of the illuminants with respect to the lighting area, a smallest illumination angle, preferably a smallest vertical illumination angle, is at least 30° and a largest illumination angle, preferably a largest vertical illumination angle, is at most 70%.
  • the different lighting areas with the different illumination angles are an advantageous aspect of the invention, since this can improve the shadows cast by the particles of the metal powder and the image data can be better analyzed.
  • the device according to the invention can therefore comprise several of the lighting groups, each lighting group being designed to carry out the illumination with a different light wavelength, the lamps of at least some of the different lighting groups being arranged along different circular circumferences with different circular radii, with circular circumferences preferably having a different distance from a center of the illumination area.
  • the metal powder is not only evenly illuminated in a lighting area, the different lighting groups also do not significantly influence each other.
  • the device further comprises a movement unit, wherein the movement unit is designed to move the lighting unit and the image recording unit relative to the metal powder for illuminating and recording the image data of different areas of the metal powder and/or for achieving the different vertical illumination angles and/or for achieving the different horizontal angles, wherein the classification of the metal powder is carried out on the basis of the image data of the different areas as an overall classification.
  • the movement unit can comprise an electric motor, in particular a stepper motor, with which the lighting unit and the image recording unit can be moved precisely, evenly and quickly, wherein the movement unit is operatively connected to the control unit in terms of signaling and is controlled by the latter.
  • the device can further comprise a mixing unit, wherein the mixing unit is designed to mechanically change the mixing of the metal powder.
  • the mixing unit can ensure, both in the training state and in the operating state, that the metal powder is mixed between the recording of two image data. Mixing the metal powder could have the advantage of providing a particularly precise characterization of the metal powder, since illumination and recording of image data of the metal powder in several orientation states of the particles of the metal powder is made possible.
  • the mixing unit can comprise a doctor blade and a plate, in particular a rotary plate for receiving the metal powder, wherein the mixing unit is designed to effect the mixing at least partially by relative movement of the plate and the doctor blade to one another, in particular by rotation of the rotary plate.
  • the use of a doctor blade and a plate, in particular a rotary plate could have the advantage of providing a device that enables an automated mixing process of the metal powder. For example, it can be designed to control an energy source for sintering or melting the metal powder if the processing device has classified the metal powder as being of sufficient quality.
  • the metal powder is heated but not melted, so that the powdery basic shape of the metal powder particles is essentially retained, but shrinkage usually occurs during a sintering process and gaps between the metal powder particles disappear - a laser is often the energy source for sintering, as this can be controlled efficiently, effectively and precisely.
  • an additive manufacturing process of powder bed-based melting using an electron beam can also be used, with the energy source being the electron beam.
  • the electron beam preheats the metal powder in a larger area and then melts the metal powder in predetermined small areas so that the component can be manufactured layer by layer.
  • an arc can be used as an energy source.
  • the device is designed to control a feed device with which the metal powder is provided.
  • the feed device is designed as a nozzle device with which the metal powder is blown into the construction space layer by layer and at the same time the energy source sinters or melts the metal powder
  • the nozzle device has a dosing unit with the lighting unit and image recording unit, with which the amount of metal powder for blowing into the construction space is dosed, and wherein the processing device qualitatively classifies the metal powder before blowing it into the construction space.
  • the dosing unit can be a rotating disk, relative to which the lighting unit and the image recording unit are fixed, wherein a rotation speed of the disk influences the amount of metal powder for blowing into the construction space.
  • the feed device is designed as a coating device for coating the metal powder, with which a powder bed of the metal powder is produced layer by layer in a construction space, wherein both the component to be manufactured is produced layer by layer and the lighting unit and the image recording unit are introduced into the construction space, and wherein the powder bed is sintered or melted by means of the energy source after the qualitatively positive classification of the metal powder by the processing device or the powder bed is removed again after a qualitatively negative classification.
  • the device is designed to cause the metal powder to be removed and a new metal powder to be provided by the feed device if the processing device has classified the metal powder as not being of sufficient quality.
  • the negative and insufficiently qualified powder bed can therefore be blown off or removed, for example.
  • the lighting unit has at least one lighting means, preferably a plurality of lighting means, which are arranged in particular around the metal powder, with which the metal powder is illuminated from different lighting angles, preferably horizontal angles, and with different light wavelengths;
  • processing device is operatively connected to the image recording unit by means of signals, so that the processing device processes the metal powder classified based on the image data transmitted by the image acquisition unit.
  • a powder feed stream of the metal powder is in an optical operative connection with the lighting unit and the image recording unit, so that the metal powder can be illuminated at least in part by the lighting unit and the image recording unit can record image data from the metal powder.
  • the powder feed stream of the metal powder according to this aspect of the invention can therefore be qualitatively classified by the processing device before each metal 3D printing process, powder metallurgical manufacturing process or the like.
  • the method for illuminating the metal powder from different illumination angles ensures, for example, optimal illumination of the metal powder and optimal shadowing of the particles, so that a particle size distribution of the metal powder can be well analyzed and determined.
  • Illuminating the metal powder with different wavelengths of light in particular from different horizontal angles and/or vertical illumination angles, enables characterization of specific properties of the illuminated metal powder, in particular oxide layers of the metal powder as an indication of degradation can be identified with different wavelengths of light.
  • the image data of the metal powder illuminated by the illumination unit can be recorded by the image recording unit with a resolution in the pm range, for example from approximately 10pm to over 200pm, according to the method according to the invention, with the image data then being transmitted to the processing device.
  • the image recording unit advantageously comprises a microscope and a communication interface with which the image recording unit and the processing device can be brought into a signal-technical operative connection.
  • a trained classification algorithm is executed for classification, which carries out the classification of the metal powder based on the recorded image files, wherein the results of the classification include information about a type of metal powder.
  • the type of metal powder includes a chemical composition of the metal powder and/or information about a degradation of the metal powder.
  • a supporting classification of the metal powder can be provided, which classifies the metal powder on the basis of a recorded particle size distribution of the metal powder and detected oxide layers of the metal powder, wherein the particle size distribution is determined by an analysis of the image data which are recorded with the image recording unit during illumination of the metal powder by the illumination unit with white light, and wherein the oxide layers are determined by an analysis of the image data which are recorded with the image recording unit during illumination of the metal powder by the illumination unit with colored light, in particular violet light.
  • Illuminating the metal powder with white light enables the classification algorithm to better capture the particle size distribution of the metal powder, with the white light being partially scattered by the particles in the direction of the image capture unit, while gaps between the particles of the metal powder do not cause any scattering in the direction of the image capture unit.
  • image segmentation the dark and light areas captured in the image data can be recognized and particle sizes of the metal powder can be identified.
  • Illuminating the metal powder with colored light highlights oxide layers of the metal powder particles depending on the wavelength range of the colored light and the type of metal powder, so that the image data can be transformed into a color space, for example an HSV color space, and a A color value can be detected for each pixel of the image data, which can be used to identify degradation of the metal powder and its particles.
  • a color space for example an HSV color space
  • the classification algorithm Based on the particle size distribution and the detected oxide layers of the metal powder, the classification algorithm, after training with known image data of the various metal powders, can qualitatively classify the metal powder present and assign it to a metal powder type known to the classification algorithm.
  • the classification algorithm comprises an artificial neural network, in particular a convolutional neural network.
  • an artificial neural network in particular a convolutional neural network.
  • convolutional neural networks are excellently suited to being trained with known image data, so that the trained artificial neural network can correctly recognize and classify metal powders known to it.
  • a VGG16 model for the artificial neural network has proven to be sufficiently efficient.
  • a VGG19 model can also be used accordingly.
  • the method according to the invention can provide that the neural network is trained using image data, comprising:
  • the training is designed, for example, to compare the classification output of the neural network with the known classification output and to attribute an error between the classification output and the known classification output, where the error is usually quadratically proportional to the weightings of the neural network and adjusts the weightings of the neural network in such a way that the error is minimized after a certain amount of image data.
  • the error is usually quadratically proportional to the weightings of the neural network and adjusts the weightings of the neural network in such a way that the error is minimized after a certain amount of image data.
  • the invention relates to a neural network obtainable by the method described above.
  • the device and the method are not limited to use in the field of metal 3D printing, but are also applicable, for example, to powder metallurgical manufacturing processes such as metal powder injection molding or thermal spraying with metal powders.
  • Figure 1 shows a device for classifying a metal powder
  • Figure 2 shows a holding device of a lighting unit of the device
  • Figures 3 and 4 show the lighting unit and an image recording unit of the device from a lower perspective view
  • Figures 5 and 6 show an illumination of a particle of a metal powder from two illumination angles
  • Figures 7 and 8 show two images of the metal powder particles taken from two illumination angles
  • Figures 9 and 10 are images of two illuminated different metal powders from different illumination angles
  • Figure 11 an application of the algorithm for determining the particle size distribution
  • Figure 12 detected pixels in an image of titanium fumes taken under violet light
  • Figure 13 is a flowchart of an artificial neural network for classifying a metal powder.
  • Figure 1 shows a device 1 for classifying a metal powder 2, wherein the device 1 has an optional electric motor-driven rotary table 3, which is designed to provide a construction space 4 for the component to be produced.
  • a control unit 5 included in the device 1 can control a feed device by means of a signal connection 6, so that the feed device introduces a powder feed stream of the metal powder 2 into the construction space 4, wherein, for example, a doctor blade 7 in the construction space 4 distributes the metal powder 2 to form a powder bed through the rotating rotary table 3.
  • the device 1 also has an energy source in the form of, for example, a laser (not shown), with which the device 1 can heat and sinter the powder bed in certain areas according to the specifications of the control unit 5, so that with each application of a new powder layer of the metal powder 2, the component can be produced layer by layer.
  • an energy source in the form of, for example, a laser (not shown), with which the device 1 can heat and sinter the powder bed in certain areas according to the specifications of the control unit 5, so that with each application of a new powder layer of the metal powder 2, the component can be produced layer by layer.
  • Figure 1 also shows a lighting unit 8 and an image recording unit 9, wherein the metal powder 2 in the construction space 4 can be illuminated from different vertical illumination angles 11, horizontal angles and with different light wavelengths using the lighting unit 8 and a plurality of lighting means 10 comprised by the lighting unit 8.
  • the metal powder can be illuminated from the same horizontal angle with different light wavelengths, and from the same vertical illumination angle 11 with different light wavelengths.
  • the lighting unit 8 comprises an image recording unit 9 in a central region 12, which can record image data of the metal powder 2 illuminated by the lighting unit 8 from the different illumination angles 11 and the different light wavelengths.
  • the image recording unit 9 is a microscope that is operatively connected to the control unit 5 in terms of signal technology, whereby the microscope has a specific magnification characteristic and can record fewer pixels per 100pm with increasing magnification.
  • the image data recorded from the illuminated metal powder 2 can be transmitted from the image recording unit 9 to the control unit 5 via the signal connection 6, so that a processing unit 13 included in the control unit 5 can analyze the image data and classify the metal powder 2.
  • control unit 5 is also operatively connected to the lighting unit 8 via the signal connection 6 and can transmit a lighting specification to the lighting unit 8 according to which the metal powder 2 should be illuminated so that it can be adequately classified by illuminating the metal powder 2 from different illumination angles 11 and with different light waves.
  • the lighting specification can, for example, contain information that several image data of the metal powder are produced per minute, each at different light wavelengths, vertical illumination angles and horizontal angles. It is also conceivable, for example, that the metal powder is mixed or moved using the turntable and/or the squeegee in the meantime between the recording of two image data. In one example, several image data are produced each at different light wavelengths, vertical illumination angles and horizontal angles, then the metal powder is mixed or moved using the turntable and/or the squeegee and the process begins again.
  • a holding device 14 of the lighting unit 8 according to the invention from Figure 1 is shown, wherein the holding device 14 is circular and is designed to hold, position and fix several lighting means 10 in the form of LEDs arranged concentrically around an image recording opening 12.
  • An alternative arrangement of the lighting means 10 is possible.
  • the holding device 14 has at least two different Lighting groups of the lighting means 10 have positioning openings 16 along different circular circumference lines 15 with different circular radii, the circular circumference lines 15 being spaced apart from one another along an illumination direction 17, so that the lighting means 5 of the different lighting groups can illuminate the metal powder 2 in sections according to the illumination specification of the control unit 5.
  • the lighting means 10 have, for example, an illumination angle 11 of approximately 70° to a plane 18 of the powder bed above the upper circular circumference line 15, the lighting means 10 having an illumination angle 11 of approximately 30° below the upper circular circumference line 15 or above a lower circular circumference line 15.
  • Figure 2 also shows the image recording opening 12, which is arranged centrally in the holding device 14 by way of example, with the image recording unit 9 in Figure 1 being introduced into this and being fixed to the holding device 14. Accordingly, when the metal powder 2 is illuminated in sections with the lighting means 10, image data can be recorded simultaneously with the image recording unit 9 through the image recording opening 12.
  • the lighting unit 8 and the image recording unit 9 of the device 1 from Figure 1 are each shown enlarged from a lower perspective view. Shown are the different types of lighting means 10 arranged concentrically around the image recording unit 9 and fixed to the holding device 14 of the lighting unit 8, wherein the holding device 14 is introduced into the lighting unit 8 and fixed to it, so that the lighting unit 8 can illuminate the metal powder 2 in areas in the direction of the illumination direction 17, while the image recording unit 9 can record image data from the metal powder 2 illuminated from the different illumination angles 11 and the different light wavelengths.
  • the different illumination angles 11 result from the position of the lighting means 10 in the respective positioning openings 16, wherein the different light wavelengths are determined by the affiliation of the respective lighting means 10 to a lighting group and can be specified by the illumination specification of the control unit 5.
  • Figures 3 and 4 show a total of four optional laser LEDs as lighting means 10, which are fixed outside the holding device 14 directly on the lighting unit 8.
  • the laser LEDs 10 have, for example, a light wavelength of approximately 750 nm and a steeper illumination angle 11 than the other lighting means 10, so that the shadow cast by the particles 19 of the metal powder 2 can be improved.
  • Figures 5 and 6 each show a basic illumination of a particle 19 of a metal powder 2 from a different vertical illumination angle 11 - specifically, Figure 5 shows an illumination of the metal powder 2 from a vertical illumination angle 11 of 70° to a plane 18 of a powder bed of the metal powder 2, while Figure 6 shows a vertical illumination angle 11 of 30°.
  • a particle 19 of the metal powder 2 is shown, which is illuminated (only as an example) by a light source 10.
  • Light rays emitted by the light source 10 strike the particle 19 at various points and are scattered by it, with some of the light rays 20 radiating past an image recording unit 9 and not being shown in the image data of the image recording unit 9 or being shown as dark pixels.
  • Figures 7 and 8 show two images 23 of the particles 19 of the metal powder 2 recorded from the two vertical illumination angles 11;
  • Figure 7 shows the image 23 of the metal powder 2 with a vertical illumination angle 11 of 70° and
  • Figure 8 with a vertical illumination angle 11 of 30°.
  • both images 23 the same area is thus of the metal powder 2 are shown from different vertical illumination angles 11. If both images 23 are fused, an improved particle size distribution of the metal powder 2 can be determined, wherein the particle size distribution describes the distribution of the different sized particles 19 in the total powder quantity of the metal powder 2.
  • Figures 9 and 10 show two different metal powders 2, each with different lighting.
  • Figure 9 shows the lighting of titanium powder 2, with the left image 23 being taken at a vertical lighting angle 11 of 70° and the right image 23 being taken at a vertical lighting angle 11 of 30°.
  • Figure 10 shows the lighting of stainless steel powder 2, with the left image 23 being taken at a vertical lighting angle 11 of 70° and the right image 23 being taken at a vertical lighting angle 11 of 30°.
  • under lighting with steep lighting angles 11 for example 70°
  • closed reflection points are created on particles 19 of the respective metal powder 2, with larger particles 19 often not being closed at flatter lighting angles 11 (for example 30°).
  • FIG 11 an exemplary determination of a particle size distribution based on a stainless steel 316L metal powder 2 is shown in three image recordings 23.
  • the left image recording 23 shows an input recording image 24 of the metal powder 2 illuminated by the lighting unit 8 in an area, wherein the larger particles 19 are shown in a clear white and some areas between the particles 19 shown in clear white remain dark because no light rays 20 were reflected from there to the image recording unit 9.
  • a threshold image 25 shown in the middle is created.
  • the threshold image 25 now only shows pixels of the image 23 that are above a brightness threshold, so that faint white and gray areas of the Input image 24 is removed.
  • an output image 26 shown on the right is created in which only pixel regions are shown that were clearly identified as a particle 19, so that possible artifacts and image acquisition errors that can distort the particle size distribution are removed.
  • a particle size distribution of the input image 24 and thus of the metal powder 2 can be reproducibly and reliably identified from the particles 19 of the metal powder 2 clearly identified in the output image 26.
  • an exemplary determination of oxide layers (27, 28) based on a reused and degraded titanium metal powder 2 is shown in three image recordings 23.
  • a left input image recording 24 an area of the metal powder 2 is shown that was illuminated with colored - in particular violet - light from a lighting unit 8, so that an image recording device 9 could record image data.
  • Two regions can be determined in the input image recording 24: a lower reddish region 27 and an upper bluish region 28. Both reddish and bluish reflections or regions 27, 28 indicate a degradation of the metal powder 2.
  • An HSV color space is particularly well suited to the segmentation of certain colors from image data, so that the input image recording 24 is first transformed into HSV coordinates in an evaluation algorithm. The evaluation algorithm then searches the HSV coordinates to determine which pixels fall into defined HSV color ranges so that the average number of reddish or bluish pixels 27, 28 per input image 24 can be calculated.
  • the middle image 23 shows the detected regions 27, 28, which are represented in the input image 24 by red pixels 27, and the right image 23 shows the detected regions 27, 28, which are represented in the input image 24 by bluish pixels 28.
  • Both detected regions 27, 28 indicate a degree of degradation of the titanium metal powder 2, which can advantageously be used to classify the metal powder 2.
  • Figure 13 shows a method 29 for classifying a metal powder 2, wherein in an initial input step 30 image data of a metal powder 2 are recorded by an image recording unit 9, while the metal powder 2 is illuminated by an illumination unit 8 from different vertical illumination angles 11, horizontal angles and with different light wavelengths.
  • the image data serve as input values for a convolutional artificial neural network and are, for example, 244x224 pixels in size.
  • a subsequent convolution step 31 the image data created in the input step 30 are processed and propagated by a convolution layer of the neural network.
  • a filter matrix as a filter kernel is convolved section by section with the image data and then an information reduction is carried out.
  • the image data filtered several times in the convolution layer and reduced in information are used in a subsequent classification step 32 by a classification layer of the neural network to classify the metal powder 2.
  • a subsequent output step 33 as part of the supporting classification, the image data from the input step 30 are assigned to a metal powder 2 known from training based on the particle size distribution and the recognized oxide layers 27, 28.
  • the output step 33 verifies or validates the results of the classification step 32. If there is no agreement between the classification step 32 and the output step 33 within certain limits, the powder is classified as an unknown powder; otherwise, the type of metal powder in the sense of a chemical composition of the metal powder and an indication of the degradation of the metal powder are output. List of reference symbols for forming a metal powder

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Abstract

L'invention concerne un procédé (29) et un appareil (1) de classification d'une poudre métallique (2). Le but de l'invention visant à améliorer une caractérisation et une classification de la poudre métallique (2) est atteint au moyen d'un appareil (1) qui comprend : - une unité d'éclairage (8) pour éclairer la poudre métallique (2), l'unité d'éclairage (8) comportant une pluralité d'illuminants (10) situés autour de la poudre métallique (2) de telle sorte que la poudre métallique (2) peut être éclairée à partir de divers angles horizontaux et selon diverses longueurs d'onde lumineuse ; - une unité de capture d'image (9) pour capturer des données d'image relatives à la poudre métallique (2) éclairée par l'unité d'éclairage (8) à partir des divers angles horizontaux et diverses longueurs d'onde lumineuse ; et - un dispositif de traitement (13) pour traiter les données d'image, le dispositif de traitement (13) étant connecté fonctionnellement à l'unité de capture d'image (9) pour une communication de signal, de telle sorte que le dispositif de traitement (13) peut classifier la poudre métallique (2) sur la base des données d'image transmises par l'unité de capture d'image (9).
PCT/EP2024/050696 2023-01-12 2024-01-12 Appareil et procédé de classification d'une poudre métallique WO2024149879A1 (fr)

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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20180200957A1 (en) 2015-07-09 2018-07-19 Siemens Aktiengesellschaft Monitoring A Process For Powder-Bed Based Additive Manufacturing
DE102018127754A1 (de) * 2018-11-07 2020-05-07 Carl Zeiss Industrielle Messtechnik Gmbh Verfahren und Vorrichtung zum Inspizieren einer Objektoberfläche, insbesondere zum Inspizieren der Oberfläche eines Pulverbettes mit einer Vielzahl von Pulverpartikeln
WO2020229838A1 (fr) 2019-05-15 2020-11-19 Lpw Technology Ltd Procédé et appareil d'analyse de poudre métallique
DE102019134987A1 (de) * 2019-12-18 2021-06-24 Carl Zeiss Industrielle Messtechnik Gmbh Verfahren und Vorrichtung zur additiven Herstellung eines Werkstücks

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Publication number Priority date Publication date Assignee Title
US20180200957A1 (en) 2015-07-09 2018-07-19 Siemens Aktiengesellschaft Monitoring A Process For Powder-Bed Based Additive Manufacturing
DE102018127754A1 (de) * 2018-11-07 2020-05-07 Carl Zeiss Industrielle Messtechnik Gmbh Verfahren und Vorrichtung zum Inspizieren einer Objektoberfläche, insbesondere zum Inspizieren der Oberfläche eines Pulverbettes mit einer Vielzahl von Pulverpartikeln
WO2020229838A1 (fr) 2019-05-15 2020-11-19 Lpw Technology Ltd Procédé et appareil d'analyse de poudre métallique
DE102019134987A1 (de) * 2019-12-18 2021-06-24 Carl Zeiss Industrielle Messtechnik Gmbh Verfahren und Vorrichtung zur additiven Herstellung eines Werkstücks

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Title
JIAHUI ZHANG ET AL: "A Computer Vision Approach to Evaluate Powder Flowability for Metal Additive Manufacturing", INTEGRATING MATERIALS AND MANUFACTURING INNOVATION, BIOMED CENTRAL LTD, LONDON, UK, vol. 10, no. 3, 17 August 2021 (2021-08-17), pages 429 - 443, XP021296096, ISSN: 2193-9764, DOI: 10.1007/S40192-021-00226-3 *

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