In-process optical based monitoring and control of additive manufacturing processes

Abstract

Systems and methods are provided for optical-based monitoring of additive manufacturing processes. In one example, a method includes obtaining optical data representative of a layer of a structure manufactured using an additive manufacturing process, comparing the optical data to a standard optical representation associated with the structure, determining one or more non-conformance conditions between the optical data representative of the layer and the standard optical representation, and implementing a control action based at least in part on the one or more non-conformance conditions.

Description

Technical Field

[0001] This disclosure generally relates to the construction process for monitoring and controlling additive manufacturing processes. Background Technology

[0002] In contrast to subtractive manufacturing methods, additive manufacturing (AM) processes typically involve the stacking of one or more materials to create net-shape or near-net-shape (NNS) objects. While "additive manufacturing" is an industry-standard term (ISO / ASTM 52900), AM encompasses a wide range of manufacturing and prototyping techniques known by various names, including freeform manufacturing, 3D printing, rapid prototyping / mold making, and more. AM technologies enable the creation of complex parts using a variety of materials. Typically, freestanding objects can be manufactured from computer-aided design (CAD) models.

[0003] Certain types of AM processes use an energy source (such as a radiation emission guide) that directs an energy beam (such as an electron beam or laser beam) to sinter or melt powder material, forming a fused region in which the particles of the powder material are bonded together. AM processes can use different material systems or additive powders, such as engineering plastics, thermoplastic elastomers, metals, and / or ceramics. Laser sintering or melting is a prominent AM process for rapidly manufacturing functional prototypes and tooling. Applications include the direct fabrication of complex workpieces, investment casting patterns, metal molds for injection molding and die casting, and molds and cores for sand casting. Manufacturing prototype objects to enhance communication and testing of concepts throughout the design cycle is another common use of AM processes. Summary of the Invention

[0004] The aspects and advantages will be set forth in part in the description which follows, or may be apparent from the description, or may be learned by practice of the invention.

[0005] It generally provides methods and systems for monitoring the layered additive manufacturing process.

[0006] For example, the method may include: obtaining geometric measurement data captured by an image capture device, representing a layer of a structure manufactured using an additive manufacturing process, through a computing system including one or more computing devices; comparing the geometric measurement data with a standard optical representation associated with the structure through the computing system; determining one or more non-compliance conditions between the geometric measurement data of the representation layer and the standard optical representation through the computing system; and implementing control actions through the computing system based at least in part on the one or more non-compliance conditions.

[0007] In one embodiment, the system may include: a surface configured to hold one or more layers of a structure manufactured by a layer-by-layer additive manufacturing process; an image capturing device configured to acquire geometric measurement data of the structure during the layer-by-layer additive manufacturing process; one or more processors; and one or more memory devices storing computer-readable instructions that, when executed by the one or more processors, cause the one or more processors to perform operations including: acquiring geometric measurement data captured by an imaging system, the geometric measurement data representing layers in one or more layers of a structure manufactured using an additive manufacturing process; comparing the geometric measurement data with a standard optical representation associated with the structure; determining one or more non-compliance conditions between the geometric measurement data representing the layers and the standard optical representation; and implementing control actions based at least in part on the one or more non-compliance conditions.

[0008] Generally, methods for manufacturing parts via laser additive manufacturing are also provided. For example, the method may include: (a) irradiating a powder layer in a powder bed to form a fusion layer; (b) providing a subsequent powder layer on the powder bed by passing a recoating mechanism through the powder bed; (c) repeating steps (a) and (b) to form a part in the powder bed; (d) simultaneously with steps (a)-(c), acquiring geometric measurement data representing the fusion layer, captured by an image capture device; (e) comparing the geometric measurement data with a standard optical representation representing the fusion layer; (f) determining one or more non-compliance conditions between the geometric measurement data representing the fusion layer and the standard optical representation; and (g) implementing control actions based at least in part on one or more non-compliance conditions.

[0009] These and other features, aspects, and advantages will be better understood with reference to the following description and the appended claims. The accompanying drawings, which are included in and form part of this specification, illustrate embodiments of the invention and, together with the description, serve to explain certain principles of the invention. Attached Figure Description

[0010] The complete and practical disclosure of the invention, including its best mode, is set forth in the description with reference to the accompanying drawings for those skilled in the art.

[0011] Figure 1 A schematic diagram illustrating in-process optics-based monitoring and control of an additive manufacturing process according to an example embodiment of this subject matter is shown.

[0012] Figure 2 A flowchart is provided illustrating an example method for in-process optics-based monitoring and control of an additive manufacturing process, according to an example embodiment of this subject matter.

[0013] Figure 3A flowchart is provided illustrating an example method for in-process optics-based monitoring and control of an additive manufacturing process, according to an example embodiment of this subject matter.

[0014] Figure 4 An example of optical-based monitoring of layers in a layered additive manufacturing system according to an exemplary embodiment of the present disclosure is shown.

[0015] Figure 5 A flowchart is depicted illustrating an example method, according to an exemplary embodiment of this subject, for determining one or more non-compliance conditions between geometric measurement data of a representation layer and a standard optical representation.

[0016] Figure 6 A block diagram of a computing system according to an example embodiment of the present disclosure is shown.

[0017] The reference numerals used repeatedly in this specification and drawings are intended to indicate the same or similar features or elements of the invention. Detailed Implementation

[0018] Reference will now be made in detail to embodiments of the invention, one or more of which are illustrated in the accompanying drawings. Each example is provided to explain the invention and not to limit it. In fact, it will be apparent to those skilled in the art that various modifications and variations can be made to the invention without departing from its scope. For example, features shown or described as part of one embodiment may be used with another embodiment to produce yet another embodiment. Therefore, the invention is intended to cover such modifications and variations falling within the scope of the appended claims and their equivalents.

[0019] As used herein, the terms “first,” “second,” and “third” are used interchangeably to distinguish one component from another and are not intended to indicate the location or importance of individual components. Furthermore, as used herein, approximate terms such as “about,” “substantially,” or “approximately” refer to a margin of error of twenty percent.

[0020] Example embodiments of this disclosure relate to systems and methods for controlling additive manufacturing processes. While additive manufacturing processes enable the design of complex parts that would otherwise be impossible to manufacture, inspecting the manufactured parts is a significant challenge. Furthermore, the time and material costs of manufacturing non-compliant parts pose a substantial risk to manufacturers.

[0021] X-ray computed tomography (CT) can be used to analyze finished parts. However, the higher energy X-rays required for larger parts demonstrate insufficient resolution for proper analysis. Furthermore, the additive manufacturing system cannot be corrected or stopped within the manufacturing process itself simply by analyzing the finished part.

[0022] As a result, manufactured parts may not meet a certain quality metric. This non-compliance poses a risk because traditional imaging techniques may be insufficient to detect defects in the parts. The inability to detect defects can present challenges. Furthermore, even if defects are detected, completing the defective part represents time and material costs for the manufacturer.

[0023] Therefore, systems and methods for in-process optics-based monitoring and control of additive manufacturing processes would be useful. More specifically, a method for dynamically evaluating the quality of individual layers during layered additive manufacturing and implementing control actions based on the evaluation.

[0024] An exemplary aspect of this disclosure utilizes geometric measurement data to monitor and control an additive manufacturing process. The additive manufacturing process may deposit a layer of powder on a surface. This powder layer may be cured into a structural layer being manufactured. Geometric measurement data representing the layer can be obtained in various ways, including but not limited to infrared imaging, high-resolution cameras, etc. If necessary, the geometric measurement data may be preprocessed to facilitate layer evaluation. For example, the geometric measurement data may undergo contrast enhancement to depict the shape of the layer.

[0025] Geometric measurement data can be compared with a standard optical representation. A standard optical representation can represent an example layer of the structure. A standard optical representation can be, but is not limited to, a file, digital image, or binary geometric measurement data generated by computer-aided design software.

[0026] Digital images of a representative structure can be captured using an image capture device. For example, a digital image of the representative structure could be geometric measurement data depicting the layers in the representative structure. The digital image of the representative structure can be selected, at least in part, based on the accuracy associated with the best depiction of the layers of the representative structure. The digital image of the representative structure may have already been captured during a previous additive manufacturing build process, or it may have been prepared for capture outside of the additive manufacturing build process. For example, the additive manufacturing process can iteratively acquire multiple digital images of the representative structure and continuously determine the most accurate digital image as the standard optical representation.

[0027] By comparing geometric measurement data with a standard optical representation, it is possible to determine whether any non-compliance conditions exist. A non-compliance condition can be that the geometric measurement data does not conform to the standard optical representation. For example, geometric measurement data representing an edge of a layer that is 3 cm longer than the equivalent of the standard optical representation could be determined as a non-compliance condition. In another example, geometric measurement data representing an edge of a layer that is 0.5 cm longer than the equivalent of the standard optical representation might not be determined as a non-compliance condition.

[0028] Control actions can be implemented based on one or more non-compliance conditions. Control actions may include, but are not limited to, sending a warning signal, stopping the additive manufacturing process, and / or modifying one or more process parameters of the additive manufacturing process. For example, a control action could completely shut down the additive manufacturing process. In another example, a control action could modify the additive manufacturing process to resolve one or more non-compliance conditions. In yet another example, a control action could send a warning signal to the additive manufacturing process.

[0029] The aspects of this disclosure provide numerous technical effects and benefits. Compared to other representations of structural layers, geometric measurement data provides higher resolution data for more accurate evaluation of layer quality. At least in part due to its higher resolution, geometric measurement data allows for direct comparison with standard optical representations (e.g., computer-generated representations, CAD files, etc.). Another technical advantage derived from this disclosure is the ability to evaluate individual layers of a structure during the additive manufacturing process, allowing the system to modify and / or halt the additive manufacturing process before a defective structure is completed.

[0030] The examples provide improvements to computational techniques. The method for processing geometric measurement data described in this disclosure can provide a more efficient computational algorithm for detecting anomalies in the additive manufacturing process using geometric measurement data acquired using an image capture device. This more efficient computation allows processing resources of the additive manufacturing system to be reserved for more core functions.

[0031] As described in detail below, exemplary embodiments of this subject matter relate to the use of additive manufacturing machines or methods. As used herein, the term "additive manufacturing" or "additive manufacturing technology or process" generally refers to a manufacturing process in which consecutive layers of material are disposed on top of each other to "build" a three-dimensional part layer by layer. Consecutive layers are often fused together to form an integral part that may have multiple integral sub-parts.

[0032] Although additive manufacturing is described herein as a technique capable of creating complex objects by building them up point-by-point and layer-by-layer in a vertical direction, other manufacturing methods are possible and within the scope of this subject matter. For example, while the discussion herein involves adding material to form continuous layers, those skilled in the art will understand that the methods and structures disclosed herein can be practiced with any additive manufacturing technique or manufacturing method. For example, embodiments of the invention may use layer-adding processes, layer-subtracting processes, or hybrid processes.

[0033] Suitable additive manufacturing technologies according to this disclosure include, for example, fused deposition modeling (FDM), selective laser sintering (SLS), 3D printing such as by inkjet and laser jetting, stereolithography (SLA), direct selective laser sintering (DSLS), electron beam sintering (EBS), electron beam melting (EBM), laser engineered net-shape (LENS), laser net-shape manufacturing (LNSM), direct metal deposition (DMD), digital light processing (DLP), direct selective laser melting (DSLM), selective laser melting (SLM), direct metal laser melting (DMLM), photopolymerization-based additive processes, extrusion-based processes, directional energy deposition processes, and other known processes.

[0034] In addition to processes such as Direct Metal Laser Sintering (DMLS) or Direct Metal Laser Melting (DMLM), where an energy source is used to selectively sinter or melt a portion of a powder layer, it should be understood that, according to alternative embodiments, the additive manufacturing process can be a "binder jetting" process. In this respect, binder jetting involves the continuous deposition of additive powder layers in a manner similar to that described above. However, instead of using an energy source to generate an energy beam to selectively melt or fuse the additive powder, binder jetting involves the selective deposition of a liquid binder onto each powder layer. The liquid binder can be, for example, a photocurable polymer or another liquid binder. Other suitable additive manufacturing methods and variations are intended to be within the scope of this subject matter.

[0035] The additive manufacturing process described herein can be used to form parts using any suitable material. For example, the material can be plastic, metal, concrete, ceramic, polymer, epoxy resin, photopolymer resin, or any other suitable material in solid, liquid, powder, sheet, wire, or any other suitable form. More specifically, according to exemplary embodiments of this subject matter, the additively manufactured parts described herein can be partially, integrally, or in the form of, but not limited to, pure metals, nickel alloys, chromium alloys, titanium, titanium alloys, magnesium, magnesium alloys, aluminum, aluminum alloys, iron, ferroalloys, stainless steel, and nickel or cobalt-based superalloys (e.g., those available from Special Metals Corporation under the name...). These are combinations of materials (those that are used in the additive manufacturing process described herein) that are suitable for use in the additive manufacturing process described herein, and may generally be referred to as “additive materials”.

[0036] Furthermore, those skilled in the art will understand that a variety of materials and methods for bonding these materials can be used, and that such materials and methods are contemplated within the scope of this disclosure. As used herein, reference to “fusion” can refer to any suitable process used to produce a bonded layer of any of the aforementioned materials. For example, if the object is made of a polymer, fusion can refer to the formation of a thermosetting bond between polymeric materials. If the object is an epoxy resin, the bond can be formed by a crosslinking process. If the material is ceramic, the bond can be formed by a sintering process. If the material is powdered metal, the bond can be formed by a melting or sintering process. Those skilled in the art will understand that other methods of fusing materials to manufacture parts via additive manufacturing are also possible, and these methods can be used to practice the subject matter currently disclosed.

[0037] Furthermore, the additive manufacturing processes disclosed herein allow for the formation of a single part from multiple materials. Therefore, the parts described herein can be formed from any suitable mixture of the aforementioned materials. For example, a part may comprise multiple layers, segments, or parts formed using different materials, processes, and / or on different additive manufacturing machines. In this way, parts with different materials and material properties can be constructed to meet the needs of any particular application. Moreover, while the parts described herein are constructed entirely by additive manufacturing processes, it should be understood that in alternative embodiments, all or part of these parts may be formed by casting, machining, and / or any other suitable manufacturing process. In fact, any suitable combination of materials and manufacturing methods can be used to form these parts.

[0038] An example additive manufacturing process will now be described. The additive manufacturing process uses three-dimensional (3D) information about a part, such as a 3D computer model, to manufacture the part. Therefore, a 3D design model of the part can be defined before manufacturing. In this regard, a model or prototype of the part can be scanned to determine the part's 3D information. As another example, a suitable computer-aided design (CAD) program can be used to construct a model of the part to define its 3D design model.

[0039] The design model can include 3D digital coordinates of the entire construction of a component, including its outer and inner surfaces. For example, the design model can define a body, surfaces, and / or internal channels, such as openings, support structures, etc. In one example embodiment, the 3D design model is transformed into multiple slices or segments, for example, along a central (e.g., vertical) axis or any other suitable axis of the component. Each slice can define a thin cross-section of the component with respect to a predetermined height. Multiple consecutive cross-sectional slices together form the 3D component. The component is then “built” slice by slice or layer by layer until completion.

[0040] In this way, the components described herein can be manufactured using additive manufacturing processes, or more specifically, by continuously forming each layer, for example, through the use of laser energy or thermal fusion or polymerization of plastics, or by sintering or melting metal powders. For example, certain types of additive manufacturing processes can use energy beams, such as electron beams or electromagnetic radiation such as laser beams, to sinter or melt powder materials. Any suitable laser and laser parameters can be used, including considerations for power, laser beam spot size, and scanning speed. The building material can be formed from any suitable powder or material selected to enhance strength, durability, and service life, particularly at high temperatures.

[0041] Each continuous layer can be, for example, between about 10 μm and 200 μm, but according to alternative embodiments, the thickness can be selected based on any number of parameters and the thickness can be any suitable size. Therefore, using the additive forming method described above, the component described herein can have a cross-section as thin as one thickness (e.g., 10 μm) of the associated powder layer used in the additive forming process.

[0042] Furthermore, using additive manufacturing processes, the surface finish and characteristics of a part can be varied depending on the application requirements. For example, the surface finish can be adjusted (e.g., made smoother or rougher) by selecting appropriate laser scanning parameters (e.g., laser power, scanning speed, laser focal size, etc.) during the additive manufacturing process, especially around the periphery of cross-sectional layers corresponding to the part surface. For instance, a rougher finish can be obtained by increasing the laser scanning speed or decreasing the size of the formed molten pool, and a smoother finish can be obtained by decreasing the laser scanning speed or increasing the size of the formed molten pool. The scanning mode and / or laser power can also be changed to alter the surface finish of selected areas.

[0043] After the manufacturing of a component is completed, various post-processing procedures can be applied to it. For example, post-processing procedures may include removing excess powder by means such as air blowing or vacuuming. Other post-processing procedures may include stress relief processes. In addition, thermal, mechanical, and / or chemical post-processing procedures may be used to finish the parts to achieve the desired strength, surface finish, and other component properties or characteristics.

[0044] It is worth noting that, in the exemplary embodiments, certain aspects and features of this subject matter were previously impossible due to manufacturing constraints. However, the inventors have advantageously utilized current advances in additive manufacturing technology to improve various components and methods of additively manufacturing such components. While this disclosure is not limited to using additive manufacturing to form these components, additive manufacturing does offer a number of manufacturing advantages, including ease of manufacture, reduced costs, and higher precision.

[0045] Furthermore, the additive manufacturing methods described above offer the ability to form more complex and intricate shapes and contours of the components described herein with very high levels of precision. For example, such components may include thin additive manufacturing layers, cross-sectional features, and component contours. Moreover, the additive manufacturing process can produce individual components with different materials, allowing different parts of the component to exhibit different performance characteristics. The continuity and additivity of the manufacturing process enable the construction of these novel features. As a result, components formed using the methods described herein can exhibit improved performance and reliability.

[0046] Now for reference Figure 1 An example optical-based monitoring and control system will be described based on an example embodiment. The example embodiment utilizes an additive manufacturing system such as DMLS or DMLM system 100 to construct a structure 170 consisting of layers 172. It should be understood that structure 170 is merely an example component to be constructed and is primarily used to facilitate the description of the operation of the additive manufacturing system. This subject matter is not intended to be limited in this respect, but any suitable plurality of components can be constructed using an additive manufacturing system (e.g., DMLS or DMLM system 100).

[0047] As shown in the figure, system 100 includes a fixed housing 102 (or build area 102) that provides a contamination-free and controlled environment for performing additive manufacturing processes. In this respect, for example, housing 102 serves to isolate and protect other components of system 100. Furthermore, housing 102 may be provided with a suitable protective gas flow, such as nitrogen, argon, or another suitable gas or gas mixture. In this regard, housing 102 may define a gas inlet 104 and a gas outlet 106 for receiving gas flows to generate a static pressurized volume or a dynamic gas flow.

[0048] Housing 102 may typically contain some or all of the components of AM system 100. According to an exemplary embodiment, AM system 100 typically includes a worktable 110, a powder feeder 112, a doctor blade or recoat mechanism 114, an overflow container or reservoir 116, and a build platform 118 located within housing 102. Furthermore, energy source 120 generates an energy beam 122, and beam steering device 124 guides the energy beam 122 to facilitate the AM process, as described in more detail below. Each of these components will be described in more detail below.

[0049] According to the illustrated embodiment, the workbench 110 is a rigid structure defining a planar build surface 130. Furthermore, the planar build surface 130 defines a build opening 132 through which a build chamber 134 can be accessed. More specifically, according to the illustrated embodiment, the build chamber 134 is at least partially defined by a vertical wall 136 and a build platform 118. Additionally, the build surface 130 defines a supply opening 140 and a storage opening 144 through which additive powder 142 can be supplied from a powder supplier 112, and excess additive powder 142 can enter an overflow storage tank 116 through the storage opening 144. The build surface 130 includes a surface for holding particles as the additive powder levels across it. The collected additive powder may optionally be processed to sieve out loose, agglomerated particles before reuse.

[0050] The powder supply unit 112 typically includes an additive powder supply container 150, which typically contains an amount of additive powder 142 sufficient for some or all of the additive manufacturing processes for a particular part. Furthermore, the powder supply unit 112 includes a supply platform 152, which is a plate-like structure movable vertically within the powder supply container 150. More specifically, a supply actuator 154 vertically supports the supply platform 152 and selectively moves it up and down during the additive manufacturing process.

[0051] AM system 100 also includes a recoater mechanism 114, which is a rigid, laterally elongated structure located near the build surface 130. For example, the recoater mechanism 114 may be a hard scraper, a soft scraper, or a roller. The recoater mechanism 114 is operatively coupled to a recoater actuator 160, which is operable to selectively move the recoater mechanism 114 along the build surface 130. Furthermore, a platform actuator 164 is operatively coupled to a build platform 118 and is generally operable to move the build platform 118 vertically during the build process. While actuators 154, 160, and 164 are illustrated as hydraulic actuators, it should be understood that any other type and configuration of actuator may be used according to alternative embodiments, such as pneumatic actuators, hydraulic actuators, ball screw linear electric actuators, or any other suitable vertical support device. Other configurations are possible and are within the scope of this subject matter.

[0052] As used herein, "energy source" can refer to any device or device system constructed for directing an energy beam having suitable power and other operating characteristics to an additive powder layer during the fabrication process to sinter, melt, or otherwise fuse a portion of the additive powder layer. For example, energy source 120 can be a laser or any other suitable radiation emission guiding device or radiation device. In this respect, a radiation or laser source can generate photon or laser beam irradiation guided by a radiation emission guiding device or beam steering device.

[0053] According to an example embodiment, the beam steering device 124 includes one or more mirrors, prisms, lenses, and / or electromagnets operatively coupled to a suitable actuator and arranged to guide and focus an energy beam 122 (e.g., a laser beam). In this regard, for example, the beam steering device 124 may be a galvanometer scanner that moves or scans the focal point of the energy beam 122 emitted by the energy source 120 on the build surface 130 during the laser melting and sintering process. At this point, the energy beam 122 can be focused to a desired spot size and steered to a desired location in a plane coinciding with the build surface 130. Galvanometer scanners in powder bed fusion technology are typically in a fixed position, but the movable mirrors / lenses included allow for control and adjustment of various properties of the laser beam. According to an example embodiment, the beam steering device may also include one or more of the following: optical lenses, deflectors, mirrors, beam splitters, telecentric lenses, etc.

[0054] It should be understood that other types of energy sources 120 may be used, which may employ alternative beam steering devices 124. For example, an electron beam gun or other electron source may be used to generate an electron beam (e.g., an "e-beam"). The e-beam may be guided by any suitable radiation emission guiding device, preferably in a vacuum. When the radiation source is an electron source, the radiation emission guiding device may be, for example, an electronic control unit, which may include, for example, deflection coils, focusing coils, or similar elements. According to other embodiments, energy source 120 may include one or more of lasers, electron beams, plasma arcs, electric arcs, etc.

[0055] Prior to the additive manufacturing process, the recoater actuator 160 can be lowered to supply powder 142 containing the desired composition (e.g., metal, ceramic, and / or organic powders) into the supply container 150. Furthermore, the platform actuator 164 can move the build platform 118 to an initial high position, for example, so that it is substantially flush with or coplanar with the build surface 130. The build platform 118 is then lowered below the build surface 130 in selected layer increments. The layer increment affects the speed of the additive manufacturing process and the resolution of the part or component being manufactured (e.g., structure 170). For example, the layer increment can be approximately 10 to 100 micrometers (0.0004 to 0.004 inches).

[0056] The additive powder is then deposited on the build platform 118 before being fused by the energy source 120. Specifically, the supply actuator 154 can raise the supply platform 152 to push the powder through the supply opening 140, exposing it above the build surface 130. The recoater mechanism 114 can then be moved on the build surface 130 by the recoater actuator 160 to horizontally distribute the raised additive powder 142 onto the build platform 118 (e.g., in selected layer increments or thicknesses). As the recoater mechanism 114 moves from left to right (e.g., as...), the powder is deposited on the build platform 118. Figure 3 As shown, any excess additive powder 142 falls into the overflow reservoir 116 through the reservoir opening 144. The recoating mechanism 114 can then be moved back to the starting position.

[0057] Therefore, as explained in this article and Figure 1 As shown, the recoater mechanism 114, recoater actuator 160, supply platform 152, and supply actuator 154 are generally operable to continuously deposit layers of additive powder 142 or other additive materials to facilitate the printing process. Therefore, these components may be collectively referred to herein as powder dispensing equipment, systems, or assemblies. The leveled additive powder 142 may be referred to as “build layer” 172 (see [link to documentation]). Figure 4 The exposed upper surface of the additive manufacturing process may be referred to as build surface 130. As the additive powder levels across build surface 130, it includes a surface that holds the particles. When build platform 118 is lowered into build chamber 134 during the build process, build chamber 134 and build platform 118 together surround and support a large quantity of additive powder 142 and any component being built (e.g., structure 170). This large quantity of powder is commonly referred to as a "powder bed," and this particular type of additive manufacturing process may be called a "powder bed process."

[0058] In the additive manufacturing process, a directional energy source 120 is used to melt a two-dimensional cross-section or layer of the part being constructed (e.g., structure 170). More specifically, an energy beam 122 is emitted from the energy source 120, and a beam steering device 124 is used to direct the focus of the energy beam 122 onto the exposed powder surface in a suitable pattern (referred to herein as a “tool path”). A small portion of the exposed layer of additive powder 142 is heated by the energy beam 122 to a temperature that allows it to sinter or melt, flow, and solidify, forming a fused region. This step may be referred to as fusing additive powder 142.

[0059] Image data capture device 174 can acquire geometric measurement data 176. Geometric measurement data 176 may be data representing the fusion layer 172 of structure 170. According to some embodiments, geometric measurement data 176 may include one or more of high-resolution digital image data, X-ray data, line scanner data, infrared data, point-by-point molten pool data (e.g., point-by-point molten pool electromagnetic emission data or image data), etc. Geometric measurement data 176 is transmitted to computing system 180 via data connector 178. Data connector 176 may be a wired or wireless connection.

[0060] If needed, the computing system 180 can preprocess the geometric measurement data 176. Preprocessing may include enhancing the contrast of the geometric measurement data, converting the geometric measurement data to binary geometric measurement data, and / or correcting one or more of the following: For example, geometric measurement data 176 captured at an angle less than or greater than 90 degrees to the surface of layer 172 may be corrected to provide a more accurate comparison with standard optical representations, as will be referenced herein. Figure 4 Further description.

[0061] The computing system 180 can compare the geometric measurement data 176 with a standard optical representation. The standard optical representation represents the optimal layers of structure 170. The standard optical representation can be, but is not limited to, a representative file generated by computer-aided design software, a digital image of the representative structure, etc. A digital image of the representative structure can be captured using the geometric measurement data capture device 174. For example, the digital image of the representative structure can be captured geometric measurement data 176 depicting the layers in the representative structure. The digital image of the representative structure can be selected based at least in part on the accuracy associated with the optimal depiction of the layers of the representative structure.

[0062] As this article will refer to Figure 3 As further described, based at least in part on this comparison, the computing system 180 can determine one or more discrepancies between the geometric measurement data 176 and the standard optical representation. For example, a discrepancy could indicate that a single edge of layer 172 is misaligned by a certain percentage compared to the standard optical representation. Another example is that a discrepancy could indicate that layer 172 has a specific length, height, or width compared to the standard optical representation.

[0063] Based at least in part on one or more non-compliance conditions, the computing system can implement control action 182. Control action 182 may include, but is not limited to, sending a warning signal, stopping the additive manufacturing process, and / or modifying process parameters of the additive manufacturing process (e.g., laser power, laser scanning speed, beam offset, gain settings, binder spraying process, alignment settings, etc.). For example, control action 182 may stop the additive manufacturing build process due to defects in the current layer. As another example, control action 182 may modify process parameters of the build process to resolve one or more non-compliance conditions. In yet another example, control action 182 may send a warning signal to the additive manufacturing process.

[0064] After the geometric measurement data is captured and evaluated, the build platform 118 moves vertically downwards in layer increments and applies another layer of additive powder 142 with a similar thickness. The directional energy source 120 again emits an energy beam 122, and the beam steering device 124 is used to direct the focus of the energy beam 122 onto the exposed powder surface in an appropriate pattern. The exposed additive powder layer 142 is heated by the energy beam 122 to a temperature that allows it to sinter or melt, flow, and solidify within the top layer with the lower, previously fused regions. This cycle of moving the build platform 118, applying additive powder 142, guiding the energy beam 122 to melt the additive powder 142, and then acquiring and evaluating geometric measurement data representing the layers is repeated until the entire part (e.g., structure 170) is completed.

[0065] Figure 2 A flowchart depicts an example method 200 for in-process optics-based monitoring and control of an additive manufacturing process according to an exemplary embodiment of this disclosure. One or more portions of method 200 may be generated by one or more computing devices (e.g., Figure 6 The computational system described herein can be used to implement this method. Furthermore, one or more parts of method 200 can be implemented as described herein (e.g., as...). Figure 6 The algorithm on the hardware component of the device (in the example) is used to, for example, acquire and preprocess geometric measurement data. For illustrative and discussion purposes, Figure 2 The elements are described in a specific order. Those skilled in the art will understand using the disclosure provided herein that the elements of any method discussed herein can be adjusted, rearranged, performed concurrently, extended, omitted, combined, and / or modified in various ways without departing from the scope of this disclosure.

[0066] At (202), method 200 may include acquiring high-resolution camera images of the layer. For example, image capture device 174 may acquire geometric measurement data 176, which includes high-resolution camera images representing layers of a structure manufactured using an additive manufacturing process. Optical capture device may transmit the geometric measurement data to computing system 180.

[0067] At (204), method 200 may include correcting and / or preprocessing the image. For example, computing system 180 may receive geometric measurement data 176 comprising a high-resolution camera image from image capture device 174. Computing system 180 may then correct and / or preprocess the geometric measurement data 176. Preprocessing of the geometric measurement data 176 may include, but is not limited to, at least one of enhancing image contrast, converting the image to binary geometric measurement data, sharpening the image, pixel brightness transformation, interpolation, geometric transformation, detecting one or more edges of a layer of structure, etc. For example, computing system 180 may determine that the geometric measurement data 176 was captured by geometric measurement data capture device 174 at an angle less than or greater than 90 degrees, and therefore may correct the geometric measurement data 176 to account for perspective or other forms of distortion in the image to facilitate comparison with a standard optical representation. In another example, computing system 180 may determine that the fidelity of the geometric measurement data 176 is insufficient for comparison, and therefore may preprocess the geometric measurement data 176 by increasing its contrast. In yet another example, computing system 180 can determine that geometric measurement data 176 should be converted into binary geometric measurement data to facilitate comparison with standard optical representations.

[0068] At (206), method 200 may include comparing an image with a standard. For example, computing system 180 may compare geometric measurement data 176 with a standard optical representation. The standard optical representation may be, but is not limited to, a computer-generated representation of a structure under construction generated by computer-aided design (CAD) software, a digital image of a representative structure, etc. For example, geometric measurement data 176 may be spatially divided into spatial regions and compared with the standard optical representation to detect areas of difference between geometric measurement data 176 and the standard optical representation. In another example, geometric measurement data 176 may be converted to binary geometric measurement data and then subtracted from the standard optical representation. In yet another example, computing system 180 may measure areas of difference between geometric measurement data 176 and the standard optical representation.

[0069] At (208), method 200 may calculate a quality metric based at least in part on a comparison between geometric measurement data 176 and a standard optical representation. The quality metric may be, but is not limited to, detecting non-compliance. A non-compliance may be a location where geometric measurement data 176 differs from the standard optical representation. For example, a non-compliance may indicate that a single edge of layer 172 represented by geometric measurement data 176 is misaligned by a certain percentage compared to the standard optical representation. As another example, a non-compliance may indicate that layer 172 represented by geometric measurement data 176 has a certain length, height, or width compared to the standard optical representation.

[0070] At (210), method 200 can use a rule-based algorithm to evaluate the quality metric. The rule-based algorithm can be implemented in the hardware of computing system 180. The rule-based algorithm can determine whether a rule violation has occurred based on the quality metric. For example, a rule violation may occur if a certain number of non-compliance conditions are detected. As another example, a rule violation may occur if a certain number of non-compliance conditions, each with a certain severity, are detected. In yet another example, a rule violation may occur if a certain number of non-compliance conditions are detected, each with a certain severity.

[0071] At (212), method 200 may implement corrective actions at least in part based on rule violations. Corrective actions may include control action 182, which may be, but is not limited to, sending a warning signal, stopping the additive manufacturing process, and / or modifying the additive manufacturing process. For example, control action 182 may stop the additive manufacturing process due to a defect in the current layer 172. In another example, control action 182 may modify one or more process parameters of the additive manufacturing process to resolve one or more non-compliance conditions. In yet another example, control action 182 may include sending a warning to the additive manufacturing system that a rule violation has occurred.

[0072] Figure 3 A flowchart depicts an example method 300 for in-process optics-based monitoring and control of an additive manufacturing process according to an exemplary embodiment of this disclosure. One or more portions of method 300 may be provided by one or more computing devices (e.g., Figure 6 The method can be implemented using the computing system described herein. Furthermore, one or more portions of method 300 can be implemented using the apparatus described herein (e.g., such as...). Figure 6 Algorithms on hardware components (as described in the text) are used to, for example, acquire and preprocess geometric measurement data. For illustrative and discussion purposes, Figure 3 Elements executed in a specific order are described. Those skilled in the art will understand using the disclosure provided herein that, without departing from the scope of this disclosure, elements of any method discussed herein can be adapted, executed concurrently, rearranged, extended, omitted, combined, and / or modified in various ways.

[0073] At (302), method 300 may include acquiring geometric measurement data representing layers of a structure manufactured using an additive manufacturing process (e.g., powder bed fusion, photopolymerization-based additive manufacturing, binder jetting, extrusion-based processes, directional energy deposition, etc.). For example, geometric measurement data acquisition device 174 may acquire geometric measurement data 176, which includes high-resolution camera images representing layers of a structure manufactured using an additive manufacturing process. In some embodiments, geometric measurement data 176 may include one or more of high-resolution image data, X-ray data, infrared data, etc. The optical acquisition device may transmit geometric measurement data 176 to computing system 180.

[0074] At (304), method 300 may include preprocessing geometric measurement data. For example, computing system 180 may receive geometric measurement data 176 comprising a high-resolution camera image from image capture device 174. Computing system 180 may then preprocess geometric measurement data 176. Preprocessing geometric measurement data 176 may include, but is not limited to, at least one of the following: correcting data, enhancing the contrast of geometric measurement data, converting geometric measurement data to binary geometric measurement data, sharpening geometric measurement data, pixel brightness transformation, interpolation, geometric transformation, etc. For example, computing system 180 may determine that geometric measurement data 176 was captured by image capture device 174 at an angle less than or greater than 90 degrees, and therefore may correct geometric measurement data 176 to facilitate comparison with a standard optical representation. In another example, computing system 180 may determine that the fidelity of geometric measurement data 176 is insufficient for comparison with a standard optical representation and therefore may preprocess geometric measurement data 176 by increasing its contrast. In yet another example, computing system 180 may determine that geometric measurement data 176 should be converted to binary geometric measurement data to facilitate comparison with a standard optical representation.

[0075] At (306), method 300 may include comparing geometric measurement data with a standard optical representation associated with the structure. For example, computing system 180 may compare geometric measurement data 176 with a standard optical representation associated with structure 170. The standard optical representation may be, but is not limited to, a representative document generated by computer-aided design (CAD) software, a digital image of a representative structure, etc. In one example, geometric measurement data 176 may be spatially divided into one or more spatial regions and compared with the standard optical representation. In another example, geometric measurement data 176 may be converted to binary geometric measurement data and then subtracted from the standard optical representation. In yet another example, computing system 180 may measure the region of difference between geometric measurement data 176 and the standard optical representation.

[0076] At (308), method 300 may determine one or more non-compliance conditions between the geometric measurement data of layer 172 and the standard optical representation, at least in part, based on a comparison between the geometric measurement data and the standard optical representation. A non-compliance condition may be a location where the geometric measurement data 176 differs from the standard optical representation. For example, a non-compliance condition may indicate that a single edge of layer 172 represented by geometric measurement data 176 is misaligned by a certain percentage compared to the standard optical representation. As another example, a non-compliance condition may indicate that layer 172 represented by geometric measurement data 176 has a certain length, height, or width compared to the standard optical representation.

[0077] In some implementations, determining one or more non-compliance conditions may include dividing geometric measurement data into one or more spatial regions. For example, the geometric measurement data may be divided into four discrete regions, each of which includes specific features (e.g., layer edges or other features). In some implementations, determining one or more non-compliance conditions may further include comparing optical data with a standard optical representation and determining one or more non-compliance conditions for one or more spatial regions. The one or more non-compliance conditions may be based at least in part on the differences between the geometric measurement data and the standard optical representation of one or more spatial regions.

[0078] In some implementations, the difference between geometric measurement data and a standard optical representation of one or more spatial regions can include deviations between one or more specific features of the geometric measurement data and one or more specific features of the standard optical representation (e.g., univariate comparisons, etc.). The one or more specific features can be measurable and / or identifiable aspects of the geometric measurement data (e.g., one or more structural dimensions, one or more pixel grayscale values, image derivatives, the number of pixels exceeding an intensity threshold, etc.).

[0079] In some implementations, determining nonconformity conditions for one or more spatial regions may include combining multiple specific features of geometric measurement data into a nonconformity component. For example, each of the four spatial regions may be combined (e.g., combinations of specific features of each spatial region, combinations of indices of specific features of each spatial region, etc.) to generate a nonconformity component representing the relative nonconformity of the layer.

[0080] In some implementations, determining the non-compliance condition of one or more spatial regions may further include determining the non-compliance condition of one or more spatial regions based at least in part on the difference between the non-compliance component and a standard optical representation of the one or more spatial regions. As an example, the non-compliance component may indicate that the value of one or more grayscale pixels is outside a difference threshold compared to the standard optical representation. As another example, the non-compliance component may indicate that the alignment of one or more edges of a structure is outside a difference threshold compared to the standard optical representation.

[0081] At (310), method 300 may implement control action 182 at least in part based on one or more non-compliance conditions. Control action 182 may include, but is not limited to, sending a warning signal, stopping the additive manufacturing process, and / or modifying one or more process parameters of the additive manufacturing process. For example, control action 182 may completely shut down the additive manufacturing process. In another example, control action 182 may modify the additive manufacturing process to resolve one or more non-compliance conditions. In yet another example, control action 182 may send a warning signal to the additive manufacturing process.

[0082] Figure 4 This is an example of optical-based monitoring of layers in a layered additive manufacturing system according to an exemplary embodiment of the present disclosure. As shown in the figure, Figure 4 A comparison 400 is depicted performed by the computing system 180 between geometric measurement data 402 of representation layer 406 and standard optical representation 408 of optimal representation layer 410. Figure 4 The differential regions detected by the differential region assessment 412 are further depicted (e.g., 414, 416, and 418).

[0083] Comparison 400 depicts a comparison between geometric measurement data 402 and a standard optical representation 408. Comparison 400 may, but is not required to, be performed by computing system 180. Geometric measurement data 402 represents layer 406 (e.g., layer 172) of structure 170. Geometric measurement data 402 may be, but is not limited to, at least one of high-resolution image data, infrared data, etc. Geometric measurement data 402 may be preprocessed to facilitate comparison 400 with standard optical representation 408. Preprocessing may include, but is not limited to, at least one of enhancing geometric measurement data contrast, converting geometric measurement data to binary geometric measurement data, sharpening geometric measurement data, pixel brightness transformation, interpolation, geometric transformation, etc.

[0084] Comparison 400 can be performed in a variety of ways, including but not limited to dividing the geometric measurement data 402 into one or more spatial regions 404, converting the geometric measurement data 402 into binary geometric measurement data, and / or measuring the difference region between the geometric measurement data 402 and the standard optical representation 408.

[0085] For example, both geometric measurement data 402 and standard optical representation can be spatially divided into one or more spatial regions 404. (e.g.) Figure 4 As depicted, the spatial region can be divided into multiple spatial regions represented as a grid pattern. This division of spatial regions facilitates a comparison 400 between layer 406 and the optimal layer 410. For example, dividing into a grid pattern helps the computational system 180 to compare the regions of difference between layer 406 and the optimal layer 410, thus enabling the computational system 180 to measure these regions.

[0086] The computing system 180 can calculate the difference region by superimposing a standard optical representation 408 onto the geometric measurement data 402. For example, the difference region evaluation 412 depicts the standard optical representation 408 superimposed on the geometric measurement data 402. Difference regions (e.g., 414, 416, and 418) can be calculated to determine that spatial region 404 contains the difference between layer 406 and the optimal layer 410. For example, the computing system can calculate the difference region at 414, 416, and / or 418, since each region contains the difference between layer 406 and the optimal layer 410.

[0087] A non-compliance condition could be the location where a material difference is detected between layer 406 and the optimal layer 410. The calculation system 180 can determine the non-compliance condition based on calculated difference regions (e.g., 414, 416, and 418). For example, the calculation system 180 can determine that difference region 414 does not represent a non-compliance condition because the difference between layer 406 and the optimal layer 410 is not a material difference. As another example, the calculation system can therefore determine that difference region 416 does indeed represent a non-compliance condition because the difference between layer 406 and the optimal layer 410 constitutes a material difference.

[0088] Figure 5 A flowchart depicts an example method 500 for determining one or more discrepancies between geometric measurement data of a representation layer and a standard optical representation, according to an exemplary embodiment of this subject matter. One or more portions of method 500 may be generated by one or more computing devices (e.g., Figure 6 The computational system described herein can be used to implement this method. Furthermore, one or more portions of method 500 can be implemented as the apparatus described herein (e.g., such as...). Figure 6 Algorithms on hardware components (as described in the text) are used to, for example, acquire and preprocess geometric measurement data. For illustrative and discussion purposes, Figure 5 The elements are described in a specific order. Those skilled in the art will understand using the disclosure provided herein that the elements of any method discussed herein can be adapted, rearranged, expanded, omitted, combined, and / or modified in various ways without departing from the scope of this disclosure.

[0089] At (502), method 500 may include converting geometric measurement data into binary geometric measurement data. The binary geometric measurement data may be, but is not limited to, digital image data having two possible color values. For example, high-resolution image data may include multiple pixels, each pixel having one of multiple color values. When converted to binary data, the color of each pixel among the multiple pixels may be converted to one of two possible color values. In some embodiments, converting geometric measurement data into binary geometric measurement data may include one or more operations. For example, converting geometric measurement data into binary geometric measurement data may include converting the geometric measurement data into grayscale geometric measurement data, inverting the geometric measurement data, and / or calculating a threshold.

[0090] At (504), method 500 may subtract binary geometric measurement data from a standard optical representation associated with the structure to determine a computed difference. The standard optical representation associated with the structure may be, but is not limited to, binary geometric measurement data. In some embodiments, computed difference may include one or more operations. For example, one operation may include subtracting each pixel of the binary geometric measurement data from the corresponding pixel of the standard optical representation. In another example, an operation may include subtracting every other pixel of the binary geometric measurement data from the corresponding pixel of the standard optical representation. In yet another example, the operation may include subtracting one or more pixels in one or more defined regions of the binary geometric measurement data from corresponding one or more pixels in one or more defined regions of the standard optical representation. The computed difference may be stored as a data structure (e.g., a graph, array, vector, database, etc.), a variable, an object, or any other suitable form.

[0091] At (506), method 500 may evaluate the computational difference between binary geometric measurement data and a standard optical representation associated with the structure. Evaluating the computational difference may be, but is not limited to, detecting one or more nonconformities. A nonconformity may be based at least in part on the computational difference. For example, a computational difference with a certain severity may represent a nonconformity. In another example, the computational difference may be determined to be low enough not to represent a nonconformity. In yet another example, the computational difference may be stored as a data structure representing one or more regions, and each region may be evaluated to determine a nonconformity.

[0092] Figure 6 It shows Figure 1A block diagram of a computing system 180, which may be used by a distributed control system or other system to implement methods and systems according to exemplary embodiments of the present disclosure. As shown, the computing system 180 may include one or more computing devices 602. The one or more computing devices 602 may include one or more processors 604 and one or more memory devices 606. The one or more processors 604 may include any suitable processing means, such as a microprocessor, microcontroller, integrated circuit, logic device, or other suitable processing means. The one or more memory devices 606 may include one or more computer-readable media, including but not limited to non-transitory computer-readable media, RAM, ROM, hard disk drives, flash drives, or other memory devices.

[0093] One or more memory devices 606 may store information accessible by one or more processors 604, including computer-readable instructions 608 executable by one or more processors 604. Instructions 608 may be any set of instructions that, when executed by one or more processors 604, cause one or more processors 604 to perform operations. Instructions 608 may be software written in any suitable programming language or may be implemented in hardware. In some embodiments, instructions 608 may be executed by one or more processors 604 to cause one or more processors 604 to perform operations, such as implementing one or more of the processes described above.

[0094] The memory device 604 may also store data 610 accessible by the processor 604. For example, data 610 may include geometric measurement data representing layers of a structure manufactured using an additive manufacturing process, as described herein. According to exemplary embodiments of this disclosure, data 610 may include one or more tables, functions, algorithms, models, equations, etc.

[0095] One or more computing devices 602 may also include a communication interface 612 for, for example, communicating with other components of the system. The communication interface 612 may include any suitable component for interfacing with one or more networks, including, for example, a transmitter, receiver, port, controller, antenna, or other suitable component.

[0096] The technologies discussed herein refer to computer-based systems and the actions taken by and from computer-based systems, as well as the information sent to and from computer-based systems. Those skilled in the art will recognize that the inherent flexibility of computer-based systems allows for a wide variety of possible configurations, combinations, and divisions of tasks and functions between and within components. For example, the processes discussed herein can be implemented using a single computing device or multiple computing devices working in combination. Databases, memory, instructions, and applications can be implemented on a single system or distributed across multiple systems. Distributed components can operate sequentially or in parallel.

[0097] Further aspects of the invention are provided by the subject matter of the following clauses:

[0098] 1. A method for monitoring a layered additive manufacturing process, the method comprising: obtaining geometric measurement data captured by an image capture device via a computing system including one or more computing devices, the geometric measurement data representing layers of a structure manufactured using an additive manufacturing process; comparing the geometric measurement data with a standard optical representation associated with the structure via the computing system; determining one or more non-compliance conditions between the geometric measurement data and the standard optical representation representing the layer via the computing system; and implementing control actions via the computing system based at least in part on the one or more non-compliance conditions.

[0099] 2. The method according to any of the preceding paragraph, wherein the method further comprises: preprocessing the geometric measurement data by the computing system, wherein preprocessing the geometric measurement data comprises at least one of converting the geometric measurement data into binary geometric measurement data, correcting the geometric measurement data, detecting one or more edges of the layer of the structure represented by the geometric measurement data, or enhancing the contrast of the geometric measurement data.

[0100] 3. According to any of the methods described in the preceding paragraph, the geometric measurement data may include at least one of digital image data, infrared data, line scanner data, or point-by-point molten pool electromagnetic emission or image data.

[0101] 4. According to any of the methods described in the preceding paragraph, wherein the standard optical representation associated with the structure comprises a computer-generated representation of the structure being manufactured or a digital image of a representative structure being manufactured.

[0102] 5. According to any of the methods described in the preceding paragraph, the computer-generated representation of the structure being manufactured includes files generated at least in part by computer-aided design (CAD) software.

[0103] 6. The method according to any of the preceding paragraph, wherein determining one or more non-compliance conditions comprises: dividing the geometric measurement data into one or more spatial regions by the computing system; comparing the optical data with the standard optical representation by the computing system; and determining one or more non-compliance conditions of the one or more spatial regions by the computing system based at least in part on the difference between the geometric measurement data and the standard optical representation of the one or more spatial regions.

[0104] 7. According to any method described in the preceding paragraph, the difference between the geometric measurement data and the standard optical representation of the one or more spatial regions includes deviations between one or more specific features of the geometric measurement data and one or more specific features of the standard optical representation.

[0105] 8. According to any method described in the preceding paragraph, the one or more specific features include one or more of the following: one or more structural dimensions; one or more pixel grayscale values; image derivative; and the number of pixels exceeding an intensity threshold.

[0106] 9. According to any method described in the preceding paragraph, determining one or more nonconformities of the one or more spatial regions by means of the computing system based at least in part on the difference between the geometric measurement data and the standard optical representation of the one or more spatial regions comprises: combining a plurality of specific features of the geometric measurement data into a nonconformity component by means of the computing system; and determining the nonconformity condition of the one or more spatial regions based at least in part on the difference between the nonconformity component and the standard optical representation of the one or more spatial regions by means of the computing system.

[0107] 10. The method according to any of the preceding paragraph, wherein determining one or more non-compliance conditions between the geometric measurement data representing the layer and the standard optical representation by the computing system comprises: converting the geometric measurement data into binary geometric measurement data by the computing system; subtracting the binary geometric measurement data from the standard optical representation associated with the structure by the computing system to determine a computational difference; and evaluating the computational difference between the binary geometric measurement data and the standard optical representation associated with the structure by the computing system.

[0108] 11. The method described in any of the preceding paragraph, wherein the control action includes sending a warning signal, stopping the layered additive manufacturing process, or modifying one or more process parameters of the layered additive manufacturing process.

[0109] 12. According to any method described in the preceding paragraph, the one or more process parameters include one or more of the following: laser power; laser scanning speed; beam offset; one or more gain settings; one or more adhesive spraying processes; and one or more alignment settings.

[0110] 13. A system for monitoring a layered additive manufacturing process, the system comprising: a surface configured to hold one or more layers of a structure manufactured by the layered additive manufacturing process; an image capturing device configured to acquire geometric measurement data of the structure during the layered additive manufacturing process; one or more processors; and one or more memory devices storing computer-readable instructions that, when executed by the one or more processors, cause the one or more processors to perform operations including: acquiring geometric measurement data captured by an imaging system, the geometric measurement data representing a layer of the one or more layers of the structure manufactured using the additive manufacturing process; comparing the geometric measurement data with a standard optical representation associated with the structure; determining one or more non-compliance conditions between the geometric measurement data representing the layer and the standard optical representation; and implementing control actions based at least in part on the one or more non-compliance conditions.

[0111] 14. According to any system described in the preceding paragraph, the layered additive manufacturing process includes: a powder bed fusion process; a photopolymerization-based additive process; a binder spraying process; an extrusion-based process; or a directional energy deposition process.

[0112] 15. According to any system described in the preceding paragraph, wherein the operation further comprises: preprocessing the geometric measurement data, wherein preprocessing the geometric measurement data includes at least one of converting the geometric measurement data into binary geometric measurement data, correcting the geometric measurement data, detecting one or more edges of the layer of the structure represented by the geometric measurement data, or enhancing the contrast of the geometric measurement data.

[0113] 16. According to any system described in the preceding paragraph, the operation of determining one or more non-compliance conditions comprises: dividing the geometric measurement data into one or more spatial regions; comparing the optical data with the standard optical representation; and determining the non-compliance conditions of the one or more spatial regions based at least in part on the difference between the geometric measurement data and the standard optical representation of the one or more spatial regions.

[0114] 17. According to any system described in the preceding paragraph, the operation of determining one or more non-compliance conditions between the geometric measurement data representing the layer and the standard optical representation comprises: converting the geometric measurement data into binary geometric measurement data; subtracting the binary geometric measurement data from the standard optical representation associated with the structure to determine a computational difference; and evaluating the computational difference between the binary geometric measurement data and the standard optical representation associated with the structure.

[0115] 18. According to any system described in the preceding paragraph, the control action includes sending a warning signal, stopping the layered additive manufacturing process, or modifying one or more process parameters of the layered additive manufacturing process.

[0116] 19. A method of manufacturing a part by laser additive manufacturing, comprising: (a) irradiating a powder layer in a powder bed to form a fusion layer; (b) providing a subsequent powder layer on the powder bed by passing a recoating mechanism through the powder bed; (c) repeating steps (a) and (b) to form the part in the powder bed; (d) simultaneously with steps (a)-(c) acquiring geometric measurement data captured by an image capturing device, the geometric measurement data representing the fusion layer; (e) comparing the geometric measurement data with a standard optical representation representing the fusion layer; (f) determining one or more non-compliance conditions between the geometric measurement data representing the fusion layer and the standard optical representation; and (g) implementing control actions based at least in part on the one or more non-compliance conditions.

[0117] 20. The method according to any of the preceding paragraph, wherein obtaining the geometric measurement data further comprises: preprocessing the geometric measurement data, wherein preprocessing the geometric measurement data comprises at least one of converting the geometric measurement data into binary geometric measurement data, correcting the geometric measurement data, detecting one or more edges of the fusion layer of the structure represented by the geometric measurement data, or enhancing the contrast of the geometric measurement data.

[0118] Aspects of this disclosure have been described with reference to its illustrative embodiments. Many other embodiments, modifications, and / or variations within the scope of the appended claims will be apparent to those skilled in the art upon reading this disclosure. Any and all features of the following claims may be combined and / or rearranged in any possible manner.

[0119] While the subject matter has been described in detail with respect to various specific example embodiments, each example is provided by way of explanation and not as a limitation of this disclosure. Those skilled in the art, upon gaining an understanding of the foregoing, will readily make changes, variations, and / or equivalents to these embodiments. Therefore, this disclosure does not exclude such modifications, variations, and / or additions to the subject matter that will be apparent to those of ordinary skill in the art. For example, features shown and / or described as part of an embodiment may be used with another embodiment to produce yet another embodiment. Therefore, this disclosure is intended to cover such changes, variations, and / or equivalents.

Claims

1. A method for monitoring a layered additive manufacturing process, characterized in that, The method includes: Geometric measurement data captured by an image capture device is obtained through a computing system including one or more computing devices, the geometric measurement data representing layers of a structure manufactured using an additive manufacturing process; The geometric measurement data is compared with a standard optical representation associated with the structure using the computing system; The computational system determines one or more discrepancies between the geometric measurement data representing the layer and the standard optical representation; and The computing system performs control actions at least in part based on one or more of the non-compliance conditions; Determining one or more non-compliant conditions includes: The calculation system divides the geometric measurement data into multiple spatial regions. The computing system compares the multiple spatial regions of the geometric measurement data with the standard optical representation; and The computing system determines one or more non-compliance conditions of the plurality of spatial regions based at least in part on the differences between the geometric measurement data and the standard optical representation of the plurality of spatial regions.

2. The method according to claim 1, characterized in that, The method further includes: The geometric measurement data is preprocessed by the computing system, wherein the preprocessing of the geometric measurement data includes at least one of converting the geometric measurement data into binary geometric measurement data, correcting the geometric measurement data, detecting one or more edges of the layer of the structure represented by the geometric measurement data, or enhancing the contrast of the geometric measurement data.

3. The method according to claim 1, characterized in that, The geometric measurement data may include at least one of digital image data, infrared data, line scanner data, or point-by-point molten pool electromagnetic emission or image data.

4. The method according to claim 1, characterized in that, The standard optical representation associated with the structure includes a computer-generated representation of the structure being manufactured or a digital image of a representative structure being manufactured.

5. The method according to claim 4, characterized in that, The computer-generated representation of the structure being manufactured includes files generated at least in part by computer-aided design (CAD) software.

6. The method according to claim 1, characterized in that, The difference between the geometric measurement data and the standard optical representation of the plurality of spatial regions includes deviations between one or more specific features of the geometric measurement data and one or more specific features of the standard optical representation.

7. The method according to claim 6, characterized in that, The one or more specific features mentioned above include one or more of the following: One or more structural dimensions; One or more pixel grayscale values; Image derivative; and The number of pixels that exceed the intensity threshold.

8. The method according to claim 1, characterized in that, The determination of one or more non-compliance conditions of the plurality of spatial regions by the computing system based at least in part on the difference between the geometric measurement data and the standard optical representation of the plurality of spatial regions includes: The computational system combines multiple specific features of the geometric measurement data into non-conforming components; and The computational system determines the non-compliance conditions of the plurality of spatial regions based at least in part on the difference between the non-compliance components and the standard optical representations of the plurality of spatial regions.

9. The method according to claim 1, characterized in that, The calculation system determines one or more discrepancies between the geometric measurement data representing the layer and the standard optical representation, including: The computing system converts the geometric measurement data into binary geometric measurement data. The computational system subtracts the binary geometric measurement data from the standard optical representation associated with the structure to determine the computational difference; and The computational system evaluates the computational differences between the binary geometric measurement data and the standard optical representation associated with the structure.

10. The method according to claim 1, characterized in that, The control actions include sending a warning signal, stopping the layered additive manufacturing process, or modifying one or more process parameters of the layered additive manufacturing process.

11. The method according to claim 10, characterized in that, The process parameters mentioned above include one or more of the following: Laser power; Laser scanning speed; Beam offset; One or more gain settings; One or more adhesive spraying processes; and One or more alignment settings.

12. A system for monitoring a layered additive manufacturing process, characterized in that, The system includes: A surface configured to hold one or more layers of a structure manufactured by the layered additive manufacturing process; An image capturing device configured to obtain geometric measurement data of the structure during the layered additive manufacturing process; One or more processors; and One or more memory devices storing computer-readable instructions that, when executed by the one or more processors, cause the one or more processors to perform operations, the operations including: Obtain geometric measurement data captured by an imaging system, the geometric measurement data representing a layer in one or more layers of the structure manufactured using an additive manufacturing process; The geometric measurement data are compared with a standard optical representation associated with the structure; Determine one or more non-compliance conditions between the geometric measurement data representing the layer and the standard optical representation; and Control actions are performed at least in part based on one or more of the aforementioned non-compliance conditions; The operation of determining one or more non-compliant conditions includes: The geometric measurement data is divided into multiple spatial regions. Compare the plurality of spatial regions of the geometric measurement data with the standard optical representation; and One or more non-compliance conditions of the plurality of spatial regions are determined at least in part based on the difference between the geometric measurement data and the standard optical representation of the plurality of spatial regions.

13. The system according to claim 12, characterized in that, The layered additive manufacturing process includes: Powder bed fusion process; Photopolymerization-based additive manufacturing processes; Adhesive spraying process; Based on the extrusion process; or Directional energy deposition process.

14. The system according to claim 12, characterized in that, The operation further includes: Preprocessing the geometric measurement data includes at least one of converting the geometric measurement data into binary geometric measurement data, correcting the geometric measurement data, detecting one or more edges of the layer of the structure represented by the geometric measurement data, or enhancing the contrast of the geometric measurement data.

15. The system according to claim 12, characterized in that, The operation of determining one or more non-compliance conditions between the geometric measurement data representing the layer and the standard optical representation includes: Convert the geometric measurement data into binary geometric measurement data; Subtract the binary geometric measurement data from the standard optical representation associated with the structure to determine the computational difference; and The computational differences between the binary geometric measurement data and the standard optical representation associated with the structure are evaluated.

16. The system according to claim 12, characterized in that, The control actions include sending a warning signal, stopping the layered additive manufacturing process, or modifying one or more process parameters of the layered additive manufacturing process.

17. A method for manufacturing parts by laser additive manufacturing, characterized in that, include: (a) Irradiating a powder layer in a powder bed to form a fused layer; (b) A subsequent powder layer is provided on the powder bed by passing the recoating mechanism through the powder bed; (c) Repeat steps (a) and (b) to form the part in the powder bed; (d) While performing steps (a)-(c), acquire geometric measurement data captured by an image capture device, the geometric measurement data representing the fusion layer; (e) Compare the geometric measurement data with a standard optical representation of the fusion layer; (f) Determine one or more discrepancies between the geometric measurement data representing the fusion layer and the standard optical representation; and (g) Implement control actions at least in part based on one or more of the aforementioned non-compliance conditions; Determining one or more non-compliant conditions includes: The geometric measurement data is divided into multiple spatial regions. Compare the plurality of spatial regions of the geometric measurement data with the standard optical representation; and One or more non-compliance conditions of the plurality of spatial regions are determined at least in part based on the difference between the geometric measurement data and the standard optical representation of the plurality of spatial regions.

18. The method according to claim 17, characterized in that, The acquisition of geometric measurement data further includes: The geometric measurement data is preprocessed, wherein the preprocessing of the geometric measurement data includes at least one of converting the geometric measurement data into binary geometric measurement data, correcting the geometric measurement data, detecting one or more edges of the fusion layer of the structure represented by the geometric measurement data, or enhancing the contrast of the geometric measurement data.

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