Abstract: Methods, devices, and systems for production controls of process sequences in industrial processing of workpieces supported by indoor localization are provided. In one aspect, an indoor location system includes a plurality of mobile transceivers and an analyzer. At least one mobile transceiver is configured to determine a position of a selected mobile transceiver in a three-dimensional space. Each mobile transceiver is spatially assignable to a corresponding object from a group of objects within a framework of process sequences. Each object is movable in one or more dimensions in the three-dimensional space. The analyzer is configured to determine the position of the selected mobile transceiver based at least on run times of electromagnetic signals between the mobile transceivers in a position determination process and to perform tracking of a movement of a target object assigned to the selected mobile transceiver based on the position of the selected mobile transceiver.

Abstract: Embodiments of the present disclosure provide a method and an apparatus for processing a substrate. The apparatus has a ring assembly. The ring assembly has an edge ring and a shadow ring. The edge ring has a ring shaped body. The edge ring body has a top surface and a bottom surface. Pin holes extend through the edge ring body from the top surface to the bottom surface. The shadow ring has a ring shaped body. The shadow ring body has an upper surface and a lower surface. Sockets are formed on the lower surface, wherein the sockets in the shadow ring body align with the pin holes in the edge ring body.

Abstract: An indoor location system includes mobile transceiver units to support a manufacturing control of process courses in an industrial manufacturing of workpieces in a manufacturing plant. The indoor location system includes an analysis unit configured to determine a position of a mobile transceiver unit to be localized from runtimes of electromagnetic signals between transceiver units, and an energy consumption control unit configured to output a control signal for deactivating a localizing mode of a position signal module of at least one of the mobile transceiver units if participation of the at least one mobile transceiver unit in position determination operations is not required and to output a control signal for activating the localizing mode of the position signal module of the at least one of the mobile transceiver units from a deactivated state when participation of the at least one mobile transceiver unit in a position determination operation is required.

Abstract: Implementations described herein provide a chamber lid assembly. In one embodiment, a chamber lid assembly includes a heater embedded in a dielectric body forming a boundary of a processing chamber, wherein the heater has one or more heating zones that are independently controlled.

Abstract: A method includes providing attributes of a manufacturing process and an image of a product associated with the manufacturing process to a trained machine learning model. The method further includes obtaining, from the trained machine learning model, predictive data. The method further includes determining, based on the predictive data, image measurements of the image of the product associated with the manufacturing process. Manufacturing parameters of the manufacturing process are to be updated based on the image measurements.

Abstract: Embodiments may also include a residual chemical reaction diagnostic device. The residual chemical reaction diagnostic device may include a substrate and a residual chemical reaction sensor formed on the substrate. In an embodiment, the residual chemical reaction sensor provides electrical outputs in response to the presence of residual chemical reactions. In an embodiment, the substrate is a device substrate, and the sensor is formed in a scribe line of the device substrate. In an alternative embodiment, the substrate is a process development substrate. In some embodiments, the residual chemical reaction sensor includes, a first probe pad, wherein a plurality of first arms extend out from the first probe pad, and a second probe pad, wherein a plurality of second arms extend out from the second probe pad and are interdigitated with the first arms.

Abstract: A method visualizes manufacturing process information during manufacturing of workpieces with a flatbed machine tool. The workpieces are output as cut material on a pallet of the flatbed machine tool, a sorting table, or a conveyor belt. Workpiece image data is provided in a control system. The image data is associated with a workpiece and is for display on a display unit. Workpiece-specific manufacturing process information is provided in the manufacturing control system, and is acquired during manufacturing of the workpieces and includes features of cutting processes. A database of illustration options is provided in the manufacturing control system, the options are associated with a specific manufacturing feature and are applicable to the workpiece image data to cause an illustration of the respective workpiece image data on the display unit. The workpiece image data is displayed on the display unit, while taking into account illustration options in the workpiece-specific manner.

Abstract: A method includes providing attributes of a manufacturing process and an image of a product associated with the manufacturing process to a trained machine learning model. The method further includes obtaining, from the trained machine learning model, predictive data. The method further includes determining, based on the predictive data, image measurements of the image of the product associated with the manufacturing process. Manufacturing parameters of the manufacturing process are to be updated based on the image measurements.

Abstract: A method includes determining a plurality of features of a first original image of a first product that are expected to be different for one or more products to be produced via manufacturing parameters of a manufacturing process compared to the first product. The method further includes adjusting one or more of the plurality of features of the first original image to generate a first synthetic image. The method further includes providing a plurality of images including the first original image and the first synthetic image to train a machine learning model to generate a trained machine learning model configured to generate output associated with updating the manufacturing parameters of the manufacturing process.

Abstract: A method for supporting a sorting process of workpieces arranged on a sorting table that have been produced on a machine tool by a processing plan, comprising providing of a processing image data set of the processing plan based on the arrangement of at least one workpiece. The method further relates to an imaging-based capturing of the sorting table having a plurality of adjacent workpieces to each other and generating a first sorting image data set, and repeated image-based capturing of the sorting table and generating of a second sorting image data set once at least one workpiece has been removed from the sorting table. The method comprises comparing of the sorting image data sets, incorporating the processing image data set, wherein a sorting signal is generated which contains information that comprises the type, the position and/or the shape of the at least one removed workpiece.

Abstract: Methods, systems, and non-transitory computer readable medium are described for automated image measurement for process development and optimization. A method includes receiving an image of a product associated with a manufacturing process; determining, using a trained machine learning model, an image classification for the image; selecting, based on the image classification, one or more image processing algorithms for the image; pre-processing the image based on at least one of the one or more image processing algorithms to generate an enhanced image; measuring, using a first image processing algorithm of the one or more image processing algorithms, one or more attributes of the enhanced image to determine image measurements; and reporting the image measurements. The manufacturing parameters of the manufacturing process are to be updated based on the image measurements.

Abstract: Methods, systems, and non-transitory computer readable medium are described for automated image measurement for process development and optimization. A method includes receiving original images including a first original image. Each original image is of a corresponding product associated with a manufacturing process. The method further includes performing, based on process information about the manufacturing process, feature extraction to identify features of the first original image that are expected to change based on manufacturing parameters of the manufacturing process. The method further includes generating a first synthetic image of synthetic images by performing targeted deformation of one or more of the features of the first original image.

Abstract: The present disclosure relates to the field of imaging phantoms and their use in computed tomography (CT) and radiotherapy (RT). In particular, the present disclosure provides novel ink compositions conferring radiation absorbing properties mimicking biological tissue to imaging phantoms. Thus, these novel ink compositions are particularly useful for creating tissue equivalent imaging phantoms, which allow realistically simulating biological tissue over the whole range of photon energies relevant for applications in CT and RT. Accordingly, the present disclosure also provides novel imaging phantoms exhibiting radiation absorbing properties mimicking real biological tissue. The present disclosure further relates to methods of generating imaging phantoms built up of layers making use of the novel ink compositions disclosed herein.

Abstract: Methods, devices, and systems for production controls of process sequences in industrial processing of workpieces supported by indoor localization are provided. In one aspect, an indoor location system includes a plurality of mobile transceivers and an analyzer. At least one mobile transceiver is configured to determine a position of a selected mobile transceiver in a three-dimensional space. Each mobile transceiver is spatially assignable to a corresponding object from a group of objects within a framework of process sequences. Each object is movable in one or more dimensions in the three-dimensional space. The analyzer is configured to determine the position of the selected mobile transceiver based at least on run times of electromagnetic signals between the mobile transceivers in a position determination process and to perform tracking of a movement of a target object assigned to the selected mobile transceiver based on the position of the selected mobile transceiver.

Abstract: Electrostatic chucks with variable pixelated magnetic field are described. For example, an electrostatic chuck (ESC) includes a ceramic plate having a front surface and a back surface, the front surface for supporting a wafer or substrate. A base is coupled to the back surface of the ceramic plate. A plurality of electromagnets is disposed in the base, the plurality of electromagnets configured to provide pixelated magnetic field tuning capability for the ESC.

Abstract: Methods, systems, and non-transitory computer readable medium are described for automated image measurement for process development and optimization. A method includes receiving original images including a first original image. Each original image is of a corresponding product associated with a manufacturing process. The method further includes performing, based on process information about the manufacturing process, feature extraction to identify features of the first original image that are expected to change based on manufacturing parameters of the manufacturing process. The method further includes generating a first synthetic image of synthetic images by performing targeted deformation of one or more of the features of the first original image.

Abstract: Methods, systems, and non-transitory computer readable medium are described for automated image measurement for process development and optimization. A method includes receiving an image of a product associated with a manufacturing process; determining, using a trained machine learning model, an image classification for the image; selecting, based on the image classification, one or more image processing algorithms for the image; pre-processing the image based on at least one of the one or more image processing algorithms to generate an enhanced image; measuring, using a first image processing algorithm of the one or more image processing algorithms, one or more attributes of the enhanced image to determine image measurements; and reporting the image measurements. The manufacturing parameters of the manufacturing process are to be updated based on the image measurements.

Abstract: A method for assigning a workpiece to be processed to a mobile unit of an indoor location system used in a manufacturing hall in industrial processing of workpieces is provided.

Abstract: An indoor location system includes mobile transceiver units to support a manufacturing control of process courses in an industrial manufacturing of workpieces in a manufacturing plant. The indoor location system includes an analysis unit configured to determine a position of a mobile transceiver unit to be localized from runtimes of electromagnetic signals between transceiver units, and an energy consumption control unit configured to output a control signal for deactivating a localizing mode of a position signal module of at least one of the mobile transceiver units if participation of the at least one mobile transceiver unit in position determination operations is not required and to output a control signal for activating the localizing mode of the position signal module of the at least one of the mobile transceiver units from a deactivated state when participation of the at least one mobile transceiver unit in a position determination operation is required.