Methods and systems for batch analysis of bulk mixed scrap

Abstract

Methods and systems for batch analysis of bulk mixed scrap are provided. The method comprises obtaining image data of the bulk mixed scrap, recognizing discrete metallic objects within the bulk mixed scrap in the image data, and determining a plurality of locations of the discrete metallic objects within the area in the image data. The method comprises analyzing a chemical composition of the discrete metallic objects. Each analysis comprises moving an analyzer adjacent to a first location of the plurality of locations of a first discrete metallic object of the discrete metallic objects based on the image data and determining an analyzed chemical composition of the first discrete metallic object. The method comprises comparing the analyzed chemical compositions of the discrete metallic objects with the associated chemical composition, thereby generating a comparison and based on the comparison, marking at least one of the discrete metallic objects.

Description

TITLEMETHODS AND SYSTEMS FOR BATCH ANALYSIS OF BULK MIXED SCRAPCROSS-REFERENCE

[0001] The present application claims priority to U.S. Provisional Application No.63 / 753,478, filed February 4, 2025. The entire contents of which is hereby incorporated by reference into this specification.FIELD OF USE

[0002] The present disclosure relates to methods and systems for batch analysis of bulk mixed scrap.BACKGROUND

[0003] Some metals, such as aluminum, can be recycled in various manners. For example, aluminum scrap can be processed to form new products therefrom. Recycling aluminum scrap and forming desirable new products therefrom present challenges.SUMMARY

[0004] Certain non-limiting aspects according to the present disclosure are directed to a method for batch analysis of bulk mixed scrap. The method comprises positioning the bulk mixed scrap in an area adjacent to a machine vision system and an analyzer. The bulk mixed scrap comprises an associated chemical composition. The method comprises obtaining, by the machine vision system, image data of the bulk mixed scrap, recognizing discrete metallic objects within the bulk mixed scrap in the image data, and determining a plurality of locations of the discrete metallic objects within the area in the image data. The method comprises analyzing a chemical composition of the discrete metallic objects. Each analysis comprises moving, utilizing a positioning system, an analyzer adjacent to a first location of the plurality of locations of a first discrete metallic object of the discrete metallic objects based on the image data and determining, by the analyzer, an analyzed chemical composition of the first discrete metallic object. The method comprises comparing, by a control circuit, the analyzed chemical compositions of the discrete metallic objects with the associatedchemical composition, thereby generating a comparison and based on the comparison, marking at least one of the discrete metallic objects.

[0005] Various additional non-limiting aspects according to the present disclosure are directed to a system for batch analysis of bulk mixed scrap. The system comprises a machine vision system, an analyzer, a positioning system, and a control circuit. The machine vision system is configured to determine discrete metallic objects within the bulk mixed scrap in an area. The analyzer is configured to determine a chemical composition of discrete metallic objects. The positioning system is attached to the analyzer and configured to move the analyzer adjacent to the bulk mixed scrap. The control circuit is configured to recognize, utilizing the machine vision system, the discrete metallic objects within the bulk mixed scrap, determine, utilizing the machine vision system, a plurality of locations of the discrete metallic objects within the area and generate a 3D map of the bulk mixed scrap, and analyze a chemical composition of the discrete metallic objects. Each analysis comprises the control circuit configured to automatically move, utilizing the positioning system, the analyzer adjacent to a first location of the plurality of locations of a first discrete metallic object of the discrete metallic objects based on the 3D map and determine, utilizing the analyzer, an analyzed chemical composition of the first discrete metallic object. The analyzer is configured to compare the analyzed chemical compositions of the discrete metallic objects with an associated chemical composition and generate a comparison and based on the comparison, mark at least one of the discrete metallic objects.

[0006] It is understood that the inventions disclosed and described in this specification are not limited to the aspects summarized in this Summary. The reader will appreciate the foregoing details, as well as others, upon considering the following detailed description of various non-limiting and non-exhaustive aspects according to this specification.BRIEF DESCRIPTION OF THE DRAWINGS

[0007] The features and advantages of the examples, and the manner of attaining them, will become more apparent, and the examples will be better understood, by reference to the following description taken in conjunction with the accompanying drawing, wherein:

[0008] FIG. l is a schematic view of certain aspects of a non-limiting embodiment of a system for batch analysis of bulk mixed scrap according to the present disclosure; and

[0009] FIG. 2 is a flow chart illustrating certain aspects of a non-limiting embodiment of a method for batch analysis of bulk mixed scrap according to the present disclosure.

[0010] The exemplifications set out herein illustrate certain embodiments, in one or more forms, and such exemplifications are not to be construed as limiting the scope of the appended claims in any manner.DESCRIPTION OF NON-LIMITING EMBODIMENTS

[0011] Various embodiments are described and illustrated herein to provide an overall understanding of the structure, function, and use of the disclosed methods and systems. The various embodiments described and illustrated herein are non-limiting and non-exhaustive. Thus, an invention is not limited by the description of the various non-limiting and non-exhaustive embodiments disclosed herein. Rather, the invention is defined solely by the claims. The features and characteristics illustrated and / or described in connection with various embodiments may be combined with the features and characteristics of other embodiments. Such modifications and variations are intended to be included within the scope of this specification. As such, the claims may be amended to recite any features or characteristics expressly or inherently described in, or otherwise expressly or inherently supported by, this specification. Further, the applicant reserves the right to amend the claims to affirmatively disclaim features or characteristics that may be present in the prior art. The various embodiments disclosed and described in this specification can comprise, consist of, or consist essentially of the features and characteristics as variously described herein.

[0012] Including scrap in the feed materials from which products are manufactured can be desirable to reduce carbon footprint, reduce materials cost, and / or provide alternative uses for the scrap materials. For example, bulk mixed scrap from mills can sent back to cast houses for subsequent re-use as a feedstock for new castings.

[0013] Various scrap materials, such as, for example, scrap aluminum, may comprise various elements in addition to aluminum. For example, depending on the original application, aluminum scrap may comprise, for example, iron, silicon, manganese, magnesium, copper, lithium, and / or zinc in differing concentrations. Depending on the chemistry of the aluminum alloy desired for use as feed material for manufacturing into a new product, certain aluminum scrap may not be useful because levels of alloying elements in the scrap exceed desired limits.

[0014] While bulk scrap can be collected and labeled, scrap producers are not always effective at correctly labeling bulk scrap and / or may mix multiple alloys together on one pallet. While there may be manual process checks to attempt to identify mismarked mixed bulk scrap, there still may be certain portions of the mixed bulk scrap that do not have the desired chemistry and end up in a feed material. This may result in scrapping of the feedstock altogether.

[0015] The present inventor has determined that a need exists to automatically confirm chemistry of discrete metallic objects within bulk scrap and / or sort discrete metallic objects within bulk scrap in order to enhance control over alloying element concentrations in new alloys / products formed from feed materials including the bulk mixed scrap. The present disclosure provides a non-limiting example of a method for batch analysis of bulk mixed scrap. The method comprises positioning the bulk mixed scrap in an area adjacent to a machine vision system and an analyzer. The bulk mixed scrap comprises an associated chemical composition. The method comprises obtaining, by the machine vision system, image data of the bulk mixed scrap and recognizing discrete metallic objects within the bulk mixed scrap in the image data. The method comprises determining a plurality of locations of the discrete metallic objects within the area in the image data and analyzing a chemical composition of the discrete metallic objects. Each analysis comprises moving, utilizing a positioning system, an analyzer adjacent to a first location of the plurality of locations of a first discrete metallic object of the discrete metallic objects based on the image data and determining, by the analyzer, an analyzed chemical composition of the first discrete metallic object. The method comprises comparing, by a control circuit, the analyzed chemical compositions of the discrete metallic objects with the associated chemical composition, thereby generating a comparison. Based on the comparison, the discrete metallic objects are marked.

[0016] Aspects of a non-limiting embodiment of a system 100 for batch analysis of bulk mixed scrap 102 according to the present disclosure are schematically shown in FIG. 1. The system 100 can comprise a machine vision system 104, a positioning system 106, an analyzer 108, and a control circuit 110. The system 100 can substantially automate the process of analyzing chemistry of bulk scrap materials and / or sorting bulk scrap materials in order to enhance control over alloying element concentrations in new alloys / products formed from feed materials including the bulk mixed scrap 102.

[0017] The bulk mixed scrap 102 can comprise metallic objects 102a of varying shapes, sizes, and / or types depending on the source of the bulk mixed scrap 102. For example, the bulk mixed scrap can comprise a foil, a sheet, a plate, a wire, a billet, a slab, a coil, a casting, and / or other metallic object type. In various non-limiting embodiments, the metallic objects 102a can be discrete and separate from one another.

[0018] The metallic objects 102a within the bulk mixed scrap 102 can be wrapped, banded, on a pallet, in a tub, on a rack, and / or stored in a different manner. For example, the metallic objects 102a can be plates stacked on a pallet.

[0019] The bulk mixed scrap 102 may be subject to processing in batches. For example, the metallic objects 102a can be stationary (e.g., in a pile on the floor, in a stationary container) during chemical analysis and / or marking. The bulk mixed scrap 102 may be positioned by a forklift, a robot, a hand truck, and / or other device.

[0020] In various embodiments, the bulk mixed scrap can be substantially large. In certain non-limiting embodiments, each individual metallic object 102a can have a mass of at least 1 kilogram (kg), such as, for example, at least 5 kg, at least 10 kg, at least 50 kg, at least 100 kg, or at least 500 kg.

[0021] In various non-limiting embodiments, the metallic objects can comprise a metal or a metal alloy, such as, for example, aluminum, an aluminum alloy, iron, an iron alloy, zinc, a zinc alloy, magnesium, a magnesium alloy, copper, or a copper alloy. For example, the metallic objects can comprise an aluminum alloy comprising at least one element selected from the group consisting of iron, silicon, manganese, magnesium, copper, lithium, and zinc. In various embodiments, the balance of the aluminum alloy may comprise aluminum, incidental elements, and impurities. In various non-limiting embodiments, the metallic objects can comprise an alloy selected individually from the group consisting of a 2XXX series aluminum alloy, a 3XXX series aluminum alloy, a 5XXX series aluminum alloy, a 6XXX series aluminum alloy, and a 7XXX series aluminum alloy.

[0022] The bulk mixed scrap 102 can have an associated chemical composition. For example, the associated chemical composition can be physically marked on the bulk mixed scrap 102 and / or stored in a record in a memory 118 in signal communication with the control circuit 110. The associated chemical composition can be associated with the bulkmixed scrap 102 at a previous location (e.g., a mill). The associated chemical composition can refer to the entire bulk mixed scrap 102 and / or only portions thereof.

[0023] The record in memory 118 for the bulk mixed scrap 102 can comprise at least one parameter, such as, for example, an associated chemical composition, a weight of the bulk mixed scrap, a dimension of the bulk mixed scrap, and / or other parameter.

[0024] The machine vision system 104 can be configured to determine discrete metallic objects 102a within the bulk mixed scrap 102 in an area 112. The machine vision system 104 can comprise a camera, a 3D positioning sensor, and / or other vision device. The camera can comprise an ultraviolet (UV) camera, a visible light camera, and / or an infrared camera. The 3D positioning sensor can comprise a structured light sensor, a time of flight sensor (e.g., a light detection and ranging system (LiDAR)), and / or other 3D positioning sensor type.

[0025] The positioning system 106 can be capable to engage and move the machine vision system 104 and / or the analyzer 108 within the area 112 and / or adjacent to the bulk mixed scrap 102. For example, the positioning system 106 can comprise a movement tool 114 and / or an end effector 116. The positioning system 106 can be capable of three-dimensional movement including z-, x-, and y-axis movements to move the end effector relative to the bulk mixed scrap 102.

[0026] The movement tool 114 can comprise at least one component selected from the group consisting of an actuator, a gantry, and a robotic arm. The end effector 116 can be operatively coupled to the movement tool 114 which can move the end effector 116 and thereby the analyzer 108 in at least one degree of freedom, at least two degrees of freedom, or at least three degrees of freedom.

[0027] The end effector 116 can be mechanically connected to the movement tool 114 and capable of engaging the machine vision system 104 and / or analyzer 116. The end effector 116 can comprise a fastener, a mechanical clamp (e.g., jaw like device), a vacuum gripper, a suction cup, an electromagnet, an adhesive pad, and / or other device capable of engaging and securing the respective device to the end effector 116. The engagement between the end effector 116 and the device may be permanent or temporary as desired for the application.

[0028] The analyzer 108 can be attached to the positioning system 106. The analyzer 108 can be capable to determine a chemical composition of discrete metallic objects within the bulk mixed scrap 102. In various embodiments, the analyzer 108 can comprise a laserinduced breakdown spectroscopy (LIBS) device, an x-ray fluorescence (XRF) device, an x-ray transmittance (XRT) device, or a combination of two or more thereof.

[0029] In embodiments where the analyzer 108 is a LIBS device, the analyzer 108 can comprise an emitter capable to emit a laser beam and the laser beam can contact a surface of a discrete metallic object 102a. The laser beam can generate a plasma on the surface of the discrete metallic object 102a, and the plasma emits light based on the chemical composition of the discrete metallic object 102a. The analyzer 108 can receive light from the plasma generated on the surface of the discrete metallic object 102a and transmit the light to a spectrometer in the analyzer 108 capable to analyze the wavelengths of light emitted by the plasma and determine chemical characteristics of the discrete metallic object 102a.

[0030] The control circuit 110 can be capable to control the functionality of the system 100. For example, the control circuit 110 can be in signal communication with the machine vision system 104, the positioning system 106, the analyzer 108, and, optionally, other components as desired for the application, such as, for example, a scale 120.

[0031] The control circuit 110 can be capable to instruct the machine vision system 104 to obtain image data of the bulk mixed scrap 102. The image data can be a single image and / or multiple images (e.g., a video). The image data can be stored in a memory 118 in signal communication with the control circuit 110.

[0032] In various non-limiting embodiments, the control circuit 110 can be capable to recognize the discrete metallic objects within the bulk mixed scrap 102 utilizing the machine vision system 104. For example, the control circuit 110 can use an image segmentation algorithm to determine discrete metallic objects within the bulk mixed scrap 102. In various non-limiting embodiments, the control circuit 110 can separate image data into discrete groups of pixels based on determination of boundaries of metallic objects 102a within the image data.

[0033] The control circuit 110 can be capable to determine a plurality of locations of the discrete metallic objects in the bulk mixed scrap 102 in the area 112 utilizing the machine vision system 104. For example, the control circuit 110 can use various positioning algorithms to determine the location of each discrete metallic object relative to one another within the image data, a standard reference point, the machine vision system 104, the analyzer 108, and / or other reference. The control circuit 110 can generate a 3D map of thebulk mixed scrap 102 that includes segmentation determinations and locations for the discrete metallic objects 102a. The 3D map can be stored in memory 118.

[0034] The control circuit 110 can be capable to instruct the positioning system 106 to move the analyzer 108 about the area 112 and / or adjacent to the bulk mixed scrap 102. For example, the control circuit 110 can automatically move the analyzer 108 adjacent to a location of a discrete metallic object 102a to be analyzed based on the image data. The control circuit 110 can be capable to instruct the analyzer 108 to determine the chemical composition of the discrete metallic object 102a.

[0035] The control circuit 110 can be capable to compare the analyzed chemical composition of the discrete metallic object 102a with the associated chemical composition of the bulk mixed scrap 102. Based on the comparison and the 3D map, the control circuit 110 can be capable to mark the discrete metallic object 102a within the bulk mixed scrap 102. For example, marking the discrete metallic object 102a can comprise physically marking the discrete metallic object 102a, marking the discrete metallic object 102a in image data, and / or marking a record associated with the discrete metallic object 102a.

[0036] As used herein, the term “control circuit” may refer to, for example, hardwired circuitry, programmable circuitry (e.g., a computer processor comprising one or more individual instruction processing cores, processing unit, processor, microcontroller, microcontroller unit, controller, digital signal processor (DSP), programmable logic device (PLD), programmable logic array (PLA), or FPGA), state machine circuitry, firmware that stores instructions executed by programmable circuitry, and any combination thereof. The control circuit 110 may, be embodied, collectively or individually, as circuitry that forms part of a larger system, for example, an IC, an ASIC, a SoC, a desktop computer, a laptop computer, a tablet computer, a server, a smart phone, etc. Accordingly, as used herein, a “control circuit” can comprise electrical circuitry having at least one discrete electrical circuit, electrical circuitry having at least one IC, electrical circuitry having at least one application-specific IC, electrical circuitry forming a general-purpose computing device configured by a computer program (e.g., a general-purpose computer configured by a computer program that at least partially carries out processes and / or devices described herein or a microprocessor configured by a computer program that at least partially carries out processes and / or devices described herein), electrical circuitry forming a memory device (e.g., forms of RAM), and / or electrical circuitry forming a communications device (e.g., a modem, communications switch, or optical-electrical equipment). The subject matterdescribed herein may be implemented in an analog or digital fashion, or some combination thereof.

[0037] The system 100 can comprise various other components. For example, the system 100 can comprise scale 120 to weight the bulk mixed scrap 102. The weight of the bulk mixed scrap 102 can be stored in the associated record in memory 118 for the bulk mixed scrap 102.

[0038] FIG. 2 illustrates a non-limiting embodiment of a method for batch analysis of bulk mixed scrap in accordance with the present disclosure. The method may be executed with, for example, the system 100 described hereinabove.

[0039] The method comprises positioning the bulk mixed scrap 102 in the area 112 adjacent to the machine vision system 104 and the analyzer 108 at step 202. Positioning the bulk mixed scrap 102 in the area 112 can be performed by, for example, a forklift, a robot, a hand truck, and / or other device.

[0040] At step 204, image data of the bulk mixed scrap 102 is obtained by the machine vision system 104. For example, the machine vision system 104 can capture an image and / or a video of the bulk mixed scrap 102.

[0041] At step 206, discrete metallic objects 102a within the bulk mixed scrap 102 in the image data can be recognized. The recognition can be performed by an operator analyzing the image and / or automatically by the control circuit 110. The recognition at step 206 may occur in post processing and / or in real time. In various non-limiting embodiments, the recognition results can be stored in memory 118 and associated with image data.

[0042] At step 208, a plurality of locations of the discrete metallic objects 102a within the bulk mixed scrap 102 within the area 112 in the image data can be determined. For example, a respective location of at least two different discrete metallic objects 102a can be determined. The locations can be determined by an operator and / or automatically by the control circuit 110. The plurality of locations can be stored in memory 118 and associated with image data. The determination at step 208 may occur in post processing and / or in real time. The determination at step 208 can be based on a single image, multiple images, and / or a video.

[0043] Optionally, a 3D map of the discrete metallic objects 102a can be generated. For example, the recognition results, the locations, and, optionally, the image data can be combined to generate a 3D map.

[0044] At step 210, a chemical composition of the discrete metallic objects 102a can be analyzed. For example, each analysis can comprise moving the analyzer 108 adjacent to a location of a discrete metallic object based on the image data and / or 3D map utilizing the positioning system 106 at step 210a. Moving the analyzer 108 may be automatically performed by the control circuit 110 based on the 3D map and / or by an operator utilizing the image data (e.g., via control panel for the positioning system 106).

[0045] The analysis can comprise determining an analyzed chemical composition of a discrete metallic object 102a with the analyzer 108 at step 210b. The chemical composition can be, for example, a general chemical composition or an elemental analysis of the discrete metallic object 102a. For example, the analyzer 108 can be capable to determine if the discrete metallic object is aluminum, an aluminum alloy, iron, an iron alloy, zinc, a zinc alloy, magnesium, a magnesium alloy, copper, or a copper alloy. In various non-limiting embodiments where the discrete metallic article comprises aluminum, the analyzer 108 can determine the weight percentage concentration of iron, silicon, manganese, magnesium, copper, zinc, lithium, and / or aluminum within the discrete metallic object.

[0046] Steps 204, 206, 208, 210, 210a, and 210b may occur in various orders, such as, for example, sequentially, concurrently, and / or they may overlap. For example, in various nonlimiting embodiments, the method can comprise obtaining first image data at step 204, recognizing at least one discrete metallic object 102a at step 206, and determining a location of the discrete metallic object 102a at step 208. Then, the chemical composition of the discrete metallic object 102a can be analyzed at step 210. The method can then return to step 204 to capture additional image data, recognize a second, different discrete metallic object at step 206, and determine the location of the second discrete metallic object 102a at step 208. Then, the chemical composition of the second discrete metallic object 102a can be analyzed at step 210. The method can repeat the steps as desired to determine a chemical composition of a desired quantity, if not all of, the discrete metallic objects 102a.

[0047] In certain non-limiting embodiments, the method can comprise obtaining a first image data at step 204, recognizing a desired quantity of discrete metallic objects 102a at step 206, and determining a location of each of the desired quantity of discrete metallic objects 102a at step 208. Then, the chemical composition of each of the discrete metallic objects 102a can be analyzed at step 210. The method may not have to repeat step 204 for the bulk mixed scrap

[0048] In various non-limiting embodiments, the bulk mixed scrap 102 can be weighed while analyzing the chemical composition of the discrete metallic objects at step 222. The weight of the bulk mixed scrap 102 can be measured by the scale 120.

[0049] At step 212, the control circuit 110 can compare the analyzed chemical compositions of the discrete metallic objects 102a with the associated chemical composition, and thereby generate a comparison. Based on the comparison, the discrete metallic objects 102a can individually, or as a whole, be marked at step 214 or step 216.

[0050] If the comparison at step 212 includes determining at least one analyzed chemical composition is substantially the same as the associated chemical composition, a matched discrete metallic object can be identified at step 214. If the comparison at step 212 includes determining at least one analyzed chemical composition is not substantially the same as the associated chemical composition, a mismatched discrete metallic object can be identified at step 216. At step 218, the discrete metallic object can be marked by the control circuit 110 to indicate the comparison.

[0051] Marking the mismatched and / or matched discrete metallic object can comprise physically marking the discrete metallic object 102a, marking the mismatched discrete metallic object 102a in an image, marking a record associated with the mismatched discrete metallic object 102a, and / or other marking method. For example, the discrete metallic object 102a can be physically labeled with a paint, ink, label, and / or other marking.

[0052] In various non-limiting embodiments, at step 218, a mismatched discrete metallic object 102a can be removed from the bulk mixed scrap 102. The removal can be performed manually by an operator and / or automatically with a robot.

[0053] Those skilled in the art will appreciate that recited steps herein may generally be performed in any order. Also, although various operational flows are presented in a sequence(s), it should be understood that the various operations may be performed in other orders than those that are illustrated or may be performed concurrently. Examples of such alternate orderings may include overlapping, interleaved, interrupted, reordered, incremental, preparatory, supplemental, simultaneous, reverse, or other variant orderings, unless context dictates otherwise. Furthermore, terms like “based on” or other past-tense adjectives are generally not intended to exclude such variants, unless context dictates otherwise.

[0054] The following numbered clauses are directed to various non-limiting embodiments and aspects according to the present disclosure.

[0055] Clause 1. A method for batch analysis of bulk mixed scrap, the method comprising: positioning the bulk mixed scrap in an area adjacent to a machine vision system and an analyzer, wherein the bulk mixed scrap comprises an associated chemical composition; obtaining, by the machine vision system, image data of the bulk mixed scrap; recognizing discrete metallic objects within the bulk mixed scrap in the image data; determining a plurality of locations of the discrete metallic objects within the area in the image data; analyzing a chemical composition of the discrete metallic objects, wherein each analysis comprises: moving, utilizing a positioning system, an analyzer adjacent to a first location of the plurality of locations of a first discrete metallic object of the discrete metallic objects based on the image data; and determining, by the analyzer, an analyzed chemical composition of the first discrete metallic object; comparing, by a control circuit, the analyzed chemical compositions of the discrete metallic objects with the associated chemical composition, thereby generating a comparison; and based on the comparison, marking at least one of the discrete metallic objects.

[0056] Clause 2. The method of clause 1, wherein positioning the bulk mixed scrap in the area is performed by at least one of a forklift, a robot, and a hand truck.

[0057] Clause 3. The method of any of clauses 1-2, wherein the machine vision system comprises a camera.

[0058] Clause 4. The method of clause 3, wherein the camera comprises at least one of a UV camera, a visible light camera, and an infrared camera.

[0059] Clause 5. The method of any of clauses 1-4, wherein the positioning system comprises at least one movement tool selecting from the group consisting of an actuator, a gantry, and a robotic arm.

[0060] Clause 6. The method of any of clauses 1-5, wherein the analyzer comprises at least one of a laser induced breakdown spectroscopy (LIBS) device, an x-ray fluorescence (XRF) device, and an x-ray transmittance (XRT) device.

[0061] Clause 7. The method of any of clauses 1-6, wherein comparing the analyzed chemical compositions of the discrete metallic objects with the associated chemical composition comprises determining at least one analyzed chemical composition is not substantially the same as the associated chemical composition, thereby identifying a mismatched discrete metallic object and marking the mismatched discrete metallic object to include at least one mark.

[0062] Clause 8. The method of clause 7, wherein marking the mismatched discrete metallic object comprises at least one of physically marking the discrete metallic object, marking the mismatched discrete metallic object in an image, and marking a record associated with the mismatched discrete metallic object.

[0063] Clause 9. The method of clause 7, further comprising removing the mismatched discrete metallic object from the bulk mixed scrap.

[0064] Clause 10. The method of any of clauses 1-9, wherein comparing the analyzed chemical compositions of the discrete metallic objects with the associated chemical composition comprises determining at least one analyzed chemical composition is substantially the same at the associated chemical composition, thereby identifying a matched discrete metallic object, and marking a record associated with the matched discrete metallic object, by the control circuit, to indicate the comparison.

[0065] Clause 11. The method of clause 10, wherein the record is stored in memory in signal communication with the control circuit.

[0066] Clause 12. The method of clause 11, wherein the record further comprises at least one parameter selected from the group consisting of a weight of the bulk mixed scrap and a dimension of the bulk mixed scrap.

[0067] Clause 13. The method of any of clauses 1-12, wherein the bulk mixed scrap comprises at least one of a foil, a sheet, a plate, a wire, a billet, a slab, a coil, and a casting.

[0068] Clause 14. The method of any of clauses 1-13, wherein the bulk mixed scrap is at least one of wrapped, banded, on a pallet, in a tub, and on a rack.

[0069] Clause 15. The method of any of clauses 1-14, wherein the bulked mixed scrap is weighed while analyzing the chemical composition of the discrete metallic objects.

[0070] Clause 16. The method of any of clauses 1-15, wherein the discrete metallic objects comprise aluminum, an aluminum alloy, iron, an iron alloy, zinc, a zinc alloy, magnesium, a magnesium alloy, copper, or a copper alloy.

[0071] Clause 17. The method of any of clauses 1-16, wherein the discrete metallic objects comprise an aluminum alloy comprising at least one element selected from the group consisting of iron, silicon, manganese, magnesium, copper, lithium, and zinc.

[0072] Clause 18. The method of any of clauses 1-17, wherein the recognizing the discrete metallic objects within the bulk mixed scrap and determining the plurality of locations of the discrete metallic objects within the area is performed by the control circuit and further comprises generating a 3D map of the discrete metallic objects, wherein moving the analyzer adjacent to the first location is automatically performed by the control circuit based on the 3D map.

[0073] Clause 19. A system for batch analysis of bulk mixed scrap, the system comprising: a machine vision system configured to determine discrete metallic objects within the bulk mixed scrap in an area; an analyzer configured to determine a chemical composition of discrete metallic objects; a positioning system attached to the analyzer and configured to move the analyzer adjacent to the bulk mixed scrap; and a control circuit configured to: recognize, utilizing the machine vision system, the discrete metallic objects within the bulk mixed scrap; determine, utilizing the machine vision system, a plurality of locations of the discrete metallic objects within the area and generate a 3D map of the bulk mixed scrap; and analyze a chemical composition of the discrete metallic objects, wherein each analysis comprises the control circuit configured to: automatically move, utilizing the positioning system, the analyzer adjacent to a first location of the plurality of locations of a first discrete metallic object of the discrete metallic objects based on the 3D map; and determine, utilizing the analyzer, an analyzed chemical composition of the first discrete metallic object; compare the analyzed chemical compositions of the discrete metallic objects with an associated chemical composition and generate a comparison; and based on the comparison, mark at least one of the discrete metallic objects.

[0074] Clause 20. The system of clause 19, wherein: the machine vision system comprises at least one camera selected from the group consisting of a UV camera, a visible light camera, and an infrared camera; and the analyzer comprises a laser induced breakdown spectroscopy(LIBS) device, an x-ray fluorescence (XRF) device, an x-ray transmittance (XRT) device, or a combination thereof.

[0075] As used herein, “at least one of’ a list of elements or other items means one of the elements / items or any combination of two or more of the listed elements / items. As an example “at least one of A, B, and C” means any of A only; B only; C only; A and B; A and C; B and C; or A, B, and C.

[0076] As used herein, a referenced element or region that is “intermediate” two other elements or regions means that the referenced element / region is disposed between, but is not necessarily in contact with, the two other elements / regions. Accordingly, for example, a referenced element that is “intermediate” a first element and a second element may or may not be immediately adjacent to or in contact with the first and / or second elements, and other elements may be disposed between the referenced element and the first and / or second elements.

[0077] Any references herein to “various embodiments”, “some embodiments”, “one embodiment”, “an embodiment”, “a non-limiting embodiment”, or like phrases mean that a particular feature, structure, step, or characteristic described in connection with the example is included in at least one embodiment. Thus, appearances of the phrases “various embodiments”, “some embodiments”, “one embodiment”, “an embodiment”, “a non-limiting embodiment”, or like phrases in the specification do not necessarily refer to the same embodiment. Furthermore, the particular described features, structures, steps, or characteristics may be combined in any suitable manner in one or more embodiments. Thus, the particular features, structures, steps, or characteristics illustrated or described in connection with one embodiment may be combined, in whole or in part, with the features, structures, steps, or characteristics of one or more other embodiments, without limitation. Such modifications and variations are intended to be included within the scope of the present embodiments.

[0078] In this specification, unless otherwise indicated, all numerical parameters are to be understood as being prefaced and modified in all instances by the term “about,” in which the numerical parameters possess the inherent variability characteristic of the underlying measurement techniques used to determine the numerical value of the parameter. At the very least, and not as an attempt to limit the application of the doctrine of equivalents to the scopeof the claims, each numerical parameter described herein should at least be construed in light of the number of reported significant digits and by applying ordinary rounding techniques.

[0079] Also, any numerical range recited herein includes all sub-ranges subsumed within the recited range. For example, a range of “1 to 10” includes all sub-ranges between (and including) the recited minimum value of 1 and the recited maximum value of 10, that is, having a minimum value equal to or greater than 1 and a maximum value equal to or less than 10. Also, all ranges recited herein are inclusive of the end points of the recited ranges. For example, a range of “1 to 10” includes the end points 1 and 10. Any maximum numerical limitation recited in this specification is intended to include all lower numerical limitations subsumed therein, and any minimum numerical limitation recited in this specification is intended to include all higher numerical limitations subsumed therein. Accordingly, Applicant reserves the right to amend this specification, including the claims, to expressly recite any sub-range subsumed within the ranges expressly recited. All such ranges are inherently described in this specification.

[0080] The grammatical articles “a”, “an”, and “the”, as used herein, are intended to include “at least one” or “one or more”, unless otherwise indicated, even if “at least one” or “one or more” is expressly used in certain instances. Thus, the foregoing grammatical articles are used herein to refer to one or more than one (i.e., to “at least one”) of the particular identified elements. Further, the use of a singular noun includes the plural and the use of a plural noun includes the singular, unless the context of the usage requires otherwise.

[0081] One skilled in the art will recognize that the herein described articles and methods, and the discussion accompanying them, are used as examples for the sake of conceptual clarity and that various configuration modifications are contemplated. Consequently, as used herein, the specific examples / embodiments set forth and the accompanying discussions are intended to be representative of their more general classes. In general, use of any specific exemplar is intended to be representative of its class, and the non-inclusion of specific components, devices, operations / actions, and objects should not be taken to be limiting. While the present disclosure provides descriptions of various specific aspects for the purpose of illustrating various aspects of the present disclosure and / or its potential applications, it is understood that variations and modifications will occur to those skilled in the art.Accordingly, the invention or inventions described herein should be understood to be at leastas broad as they are claimed and not as more narrowly defined by particular illustrative aspects provided herein.

Claims

CLAIMSWhat is claimed is:

1. A method for batch analysis of bulk mixed scrap, the method comprising:positioning the bulk mixed scrap in an area adjacent to a machine vision system and an analyzer, wherein the bulk mixed scrap comprises an associated chemical composition;obtaining, by the machine vision system, image data of the bulk mixed scrap;recognizing discrete metallic objects within the bulk mixed scrap in the image data;determining a plurality of locations of the discrete metallic objects within the area in the image data;analyzing a chemical composition of the discrete metallic objects, wherein each analysis comprises:moving, utilizing a positioning system, an analyzer adjacent to a first location of the plurality of locations of a first discrete metallic object of the discrete metallic objects based on the image data; anddetermining, by the analyzer, an analyzed chemical composition of the first discrete metallic object;comparing, by a control circuit, the analyzed chemical compositions of the discrete metallic objects with the associated chemical composition, thereby generating a comparison; andbased on the comparison, marking at least one of the discrete metallic objects.

2. The method of claim 1, wherein positioning the bulk mixed scrap in the area is performed by at least one of a forklift, a robot, and a hand truck.

3. The method of claim 1, wherein the machine vision system comprises a camera.

4. The method of claim 3, wherein the camera comprises at least one of a UV camera, a visible light camera, and an infrared camera.

5. The method of claim 1, wherein the positioning system comprises at least one movement tool selecting from the group consisting of an actuator, a gantry, and a robotic arm.

6. The method of claim 1, wherein the analyzer comprises at least one of a laser induced breakdown spectroscopy (LIBS) device, an x-ray fluorescence (XRF) device, and an x-ray transmittance (XRT) device.

7. The method of claim 1, wherein comparing the analyzed chemical compositions of the discrete metallic objects with the associated chemical composition comprises determining at least one analyzed chemical composition is not substantially the same as the associated chemical composition, thereby identifying a mismatched discrete metallic object and marking the mismatched discrete metallic object to include at least one mark.

8. The method of claim 7, wherein marking the mismatched discrete metallic object comprises at least one of physically marking the discrete metallic object, marking the mismatched discrete metallic object in an image, and marking a record associated with the mismatched discrete metallic object.

9. The method of claim 7, further comprising removing the mismatched discrete metallic object from the bulk mixed scrap.

10. The method of claim 1, wherein comparing the analyzed chemical compositions of the discrete metallic objects with the associated chemical composition comprises determining at least one analyzed chemical composition is substantially the same at the associated chemical composition, thereby identifying a matched discrete metallic object, and marking a record associated with the matched discrete metallic object, by the control circuit, to indicate the comparison.

11. The method of claim 10, wherein the record is stored in memory in signal communication with the control circuit.

12. The method of claim 11, wherein the record further comprises at least one parameter selected from the group consisting of a weight of the bulk mixed scrap and a dimension of the bulk mixed scrap.

13. The method of claim 1, wherein the bulk mixed scrap comprises at least one of a foil, a sheet, a plate, a wire, a billet, a slab, a coil, and a casting.

14. The method of claim 1, wherein the bulk mixed scrap is at least one of wrapped, banded, on a pallet, in a tub, and on a rack.

15. The method of claim 1, wherein the bulked mixed scrap is weighed while analyzing the chemical composition of the discrete metallic objects.

16. The method of claim 1, wherein the discrete metallic objects comprise aluminum, an aluminum alloy, iron, an iron alloy, zinc, a zinc alloy, magnesium, a magnesium alloy, copper, or a copper alloy.

17. The method of claim 1, wherein the discrete metallic objects comprise an aluminum alloy comprising at least one element selected from the group consisting of iron, silicon, manganese, magnesium, copper, lithium, and zinc.

18. The method of claim 1, wherein the recognizing the discrete metallic objects within the bulk mixed scrap and determining the plurality of locations of the discrete metallic objects within the area is performed by the control circuit and further comprises generating a 3D map of the discrete metallic objects, wherein moving the analyzer adjacent to the first location is automatically performed by the control circuit based on the 3D map.

19. A system for batch analysis of bulk mixed scrap, the system comprising:a machine vision system configured to determine discrete metallic objects within the bulk mixed scrap in an area;an analyzer configured to determine a chemical composition of discrete metallic objects;a positioning system attached to the analyzer and configured to move the analyzer adjacent to the bulk mixed scrap; anda control circuit configured to:recognize, utilizing the machine vision system, the discrete metallic objects within the bulk mixed scrap;determine, utilizing the machine vision system, a plurality of locations of the discrete metallic objects within the area and generate a 3D map of the bulk mixed scrap; andanalyze a chemical composition of the discrete metallic objects, wherein each analysis comprises the control circuit configured to:automatically move, utilizing the positioning system, the analyzer adjacent to a first location of the plurality of locations of a first discrete metallic object of the discrete metallic objects based on the 3D map; anddetermine, utilizing the analyzer, an analyzed chemical composition of the first discrete metallic object;compare the analyzed chemical compositions of the discrete metallic objects with an associated chemical composition and generate a comparison; andbased on the comparison, mark at least one of the discrete metallic objects.

20. The system of claim 19, wherein:the machine vision system comprises at least one camera selected from the group consisting of a UV camera, a visible light camera, and an infrared camera; andthe analyzer comprises a laser induced breakdown spectroscopy (LIBS) device, an x-ray fluorescence (XRF) device, an x-ray transmittance (XRT) device, or a combination thereof.

Images