Abstract: Systems and methods for classifying and sorting of dark colored and/or black-colored plastic materials utilizing a vision system or one or more sensor systems implemented with one or more medium wavelength infrared cameras whereby the captured image data is process within a machine learning system in order to identify or classify each of the materials, which may then be sorted into separate groups based on such an identification or classification.

Abstract: A material sorting system sorts materials utilizing a vision system that implements a machine learning system in order to identify or classify each of the materials, which are then sorted into separate groups based on such an identification or classification. The material sorting system can sort material pieces containing contaminants, such as copper from steel.

Abstract: Systems and methods for classifying and sorting materials in order to produce a collection of materials that are composed of a particular chemical composition in the aggregate. The system may utilize a vision system and one or more sensor systems, which may implement a machine learning system in order to identify or classify each of the materials. The sorting is then performed as a function of the classifications.

Abstract: Systems and methods for classifying and sorting materials in order to produce a collection of materials that are composed of a particular chemical composition in the aggregate. The system may utilize a vision system and one or more sensor systems, which may implement a machine learning system in order to identify or classify each of the materials. The sorting is then performed as a function of the classifications.

Abstract: A material sorting system sorts materials utilizing multiple stages of classification and sorting, including a vision system that implements an artificial intelligence system in order to identify or classify each of the materials, and an x-ray fluorescence (“XRF”) system or Laser Induced Breakdown Spectroscopy to perform a subsequent classification and sorting of the remaining materials.

Abstract: A material sorting system sorts materials utilizing multiple stages of classification and sorting, including a vision system that implements an artificial intelligence system in order to identify or classify each of the materials, and an x-ray fluorescence (“XRF”) system or Laser Induced Breakdown Spectroscopy to perform a subsequent classification and sorting of the remaining materials.

Abstract: A material handling system sorts mixed materials utilizing a combination of x-ray fluorescence and/or a vision system that implements an artificial intelligence system in order to identify or classify each of the materials, which are then sorted into separate groups based on such an identification or classification. The system is capable of sorting between materials typically found within Zorba, Zebra, and Twitch.

Abstract: A material handling system sorts mixed materials utilizing a combination of a spectroscopic sensor, such as x-ray fluorescence, and a vision system that implements an artificial intelligence system in order to identify or classify each of the materials, which are then sorted into separate groups based on such an identification or classification. The system is capable of sorting between materials typically found within Zorba, such as wrought, cast, and extrusion aluminum alloys.

Abstract: When x-ray fluorescence (“XRF”) spectroscopy is utilized to classify materials transported on a moving conveyor belt, there is the possibility of the x-ray beam only partially irradiating the material piece, which can result in the capture of an inaccurate XRF spectrum needed to classify the material piece. This can lead to an improper (erroneous) classification and resultant sortation of material pieces (e.g., aluminum alloys). In a material handling system, the area of the intersections between the x-ray beam spots from an x-ray fluorescence system and the material pieces are measured and correspondingly used to correct the measured XRF spectrum associated with each material piece. The material pieces can then be sorted according to the corrected XRF spectrum.

Abstract: A sorting system conveys a heterogeneous mixture of material pieces past an XRF system and a vision system. A classification of a material piece is changed to a high copper content aluminum alloy when the XRF system classifies the material piece as a low copper content aluminum alloy and the vision system determines that the material piece is a thin strip material piece. The reclassified material piece is then sorted accordingly.

Abstract: A material sorting system sorts materials utilizing multiple stages of classification and sorting, including a vision system that implements a machine learning system in order to identify or classify each of the materials, and Laser Induced Breakdown Spectroscopy to perform a subsequent classification and sorting of the remaining materials.

Abstract: A material sorting system sorts materials utilizing an x-ray fluorescence and/or a vision system that implements a machine learning system in order to identify or classify each of the materials, which are then sorted into separate groups based on such an identification or classification determining that the materials are composed of either wrought aluminum, extruded aluminum, or cast aluminum. The system is capable of sorting between cast aluminum alloys and also between wrought aluminum alloys.

Abstract: Systems and methods for classifying and sorting materials in order to produce a collection of materials that are composed of a particular chemical composition in the aggregate. The system may utilize a vision system and one or more sensor systems, which may implement a machine learning system in order to identify or classify each of the materials. The sorting is then performed as a function of the classifications.

Abstract: A material sorting system sorts materials utilizing an x-ray fluorescence and/or a vision system that implements a machine learning system in order to identify or classify each of the materials, which are then sorted into separate groups based on such an identification or classification determining that the materials are composed of either wrought aluminum, extruded aluminum, or cast aluminum. The system is capable of sorting between cast aluminum alloys and also between wrought aluminum alloys.

Abstract: Systems and methods for classifying materials utilizing one or more sensor systems, which may implement a machine learning system in order to identify or classify each of the materials, which may then be sorted into separate groups based on such an identification or classification. The machine learning system may utilize a neural network, and be previously trained to recognize and classify certain types of materials.

Abstract: Systems and methods for classifying and sorting of plastic materials utilizing a vision system and one or more sensor systems, which may implement a machine learning system in order to identify or classify each of the materials, which may then be sorted into separate groups based on such an identification or classification.

Abstract: A sorting system conveys a heterogeneous mixture of material pieces past an XRF system and a vision system. A classification of a material piece is changed to a high copper content aluminum alloy when the XRF system classifies the material piece as a low copper content aluminum alloy and the vision system determines that the material piece is a thin strip material piece. The reclassified material piece is then sorted accordingly.

Abstract: When x-ray fluorescence (“XRF”) spectroscopy is utilized to classify materials transported on a moving conveyor belt, there is the possibility of the x-ray beam only partially irradiating the material piece, which can result in the capture of an inaccurate XRF spectrum needed to classify the material piece. This can lead to an improper (erroneous) classification and resultant sortation of material pieces (e.g., aluminum alloys). In a material handling system, the area of the intersections between the x-ray beam spots from an x-ray fluorescence system and the material pieces are measured and correspondingly used to correct the measured XRF spectrum associated with each material piece. The material pieces can then be sorted according to the corrected XRF spectrum.

Abstract: A material sorting system sorts materials utilizing an x-ray fluorescence and/or a vision system that implements a machine learning system in order to identify or classify each of the materials, which are then sorted into separate groups based on such an identification or classification determining that the materials are composed of either wrought aluminum, extruded aluminum, or cast aluminum. The system is capable of sorting between cast aluminum alloys and also between wrought aluminum alloys.

Abstract: Systems and methods for classifying and sorting of dark colored and/or black-colored plastic materials utilizing a vision system or one or more sensor systems implemented with one or more medium wavelength infrared cameras whereby the captured image data is process within a machine learning system in order to identify or classify each of the materials, which may then be sorted into separate groups based on such an identification or classification.