A manufacturing control system for an additive, subtractive, or hybrid machining system implements a morphic manufacturing approach that integrates in situ inspection and related decision-making into the manufacturing process. After execution of a machining or deposition operation, the system performs a sensor scan to collect sensor measurement data for the resulting part while the part remains in the manufacturing work cell. The measurement data is compared with an as-designed digital model of the part to determine whether further machining or deposition is necessary to bring the finished part into tolerance with the model. If necessary, the system performs another additive and/or subtractive manufacturing operation on the part based on analysis of the measurement data to bring the part into tolerance. The measured inspection data can be stored in association with each manufactured part for auditing purposes or for creation of part-specific digital twins.

A vision inspection system includes an imaging device that is configured to image parts being inspected. The vision inspection system includes a vision inspection controller that is configured to be communicatively coupled to a machine controller of the part manufacture machine by a communication network. The vision inspection controller communicates with the communication network using a first communication protocol. The vision inspection controller creates an absolute path directory at the machine controller. The vision inspection controller receives an image from the imaging device. The vision inspection controller communicates a first trigger to the absolute path directory upon receipt of the image from the imaging device. The vision inspection controller processes the image from the imaging device to determine inspection results for a first part of the parts. The vision inspection controller sends at least one of the image or the inspection results to the machine controller.

An initial inspection or critical dimension measurement can be made at various sites on a wafer. The location, design clips, process tool parameters, or other parameters can be used to train a deep learning model. The deep learning model can be validated and these results can be used to retrain the deep learning model. This process can be repeated until the predictions meet a detection accuracy threshold. The deep learning model can be used to predict new probable defect location or critical dimension failure sites.

A vision inspection system includes an imaging device that is configured to image parts being inspected. The vision inspection system includes a vision inspection controller that is configured to be communicatively coupled to a machine controller of the part manufacture machine by a communication network. The vision inspection controller communicates with the communication network using a first communication protocol. The vision inspection controller creates an absolute path directory at the machine controller. The vision inspection controller receives an image from the imaging device. The vision inspection controller communicates a first trigger to the absolute path directory upon receipt of the image from the imaging device. The vision inspection controller processes the image from the imaging device to determine inspection results for a first part of the parts. The vision inspection controller sends at least one of the image or the inspection results to the machine controller.

A control system (1) according to the present invention comprises: a control device (100) that monitors the operation of a plurality of moving parts for machining a workpiece (155), and controls the operation of the plurality of moving parts in each control cycle by issuing command values to the plurality of moving parts; and an inspection device (200) for inspecting the workpiece (155). The control device (100) comprises: an identification unit (160) for identifying, based on inspection results of the inspection device (200) and the command values issued to the plurality of moving parts, which moving part from among the plurality of moving parts has caused an abnormality in the inspection results; and a storage unit (170) for collecting and storing data on the moving part that has been identified by the identification unit (160) and caused the abnormality in the inspection results.

An image inspecting apparatus includes at least one image capturing part, a lighting part, a control part including a moving part, a searching part analyzing an image captured by the image capturing part under a first image capturing condition and searching for a defect candidate from an object under inspection, and a determining part. When the searching part finds the defect candidate from the object under inspection, the control part controls an image capturing condition such that a part where the defect candidate is found by the searching part is photographed under a second image capturing condition that is clearer than the first image capturing condition. The determining part analyzes an image captured by the image capturing part under the second image capturing condition and determines whether the defect of the object under inspection is present or absent.

The present disclosure relates to a surface inspection method using a mold surface inspection device, and more specifically, to a surface inspection method using a mold surface inspection device including a setting part in which an inspection object is set, a light source part configured to irradiate the inspection object with irradiated light so that a reflective highlight is generated on a surface of the inspection object, an imaging part configured to image the surface of the inspection object so that a highlight region where a reflective highlight is generated is included, and an image processing part configured to process an image imaged in the imaging part to provide the image to a worker so that the worker determines whether defects are generated on the surface of the inspection object on the basis of the image.

A manufacturing control system for an additive, subtractive, or hybrid machining system implements in situ part inspection to collect as-built metrology data for a manufactured part while the part remains in the work envelop, and uses the resulting measured inspection data to generate an as-built digital twin that accurately models the finished part. After execution of a subtractive and/or additive tooling operation, the system performs a sensor scan to collect three-dimensional imaging measurement data for the resulting manufactured part while the part remains in the work cell. The measurement data is then integrated with as-designed part metadata for the idealized part to yield the as-built digital twin. Since metrology measurements are integrated into the manufacturing process, customized as-built digital twins can be generated for each manufactured part without requiring manual inspections to be performed on each part.

Methods and systems for collaboration between two robotic vehicle systems to accurately determine a geometric model of the footprint of a loaded robotic vehicle are described herein. A scanning robot is employed to scan a robotic vehicle loaded with a payload. The scanning robot measures the geometric information required to determine a geometric model of the loaded robotic vehicle. The scanning robot traverses a trajectory around the payload robot, while one or more distance sensors repeatedly measure the distance between the scanning robot and the payload robot and one or more image capture devices repeatedly image the payload robot. A geometric model of the footprint of the payload robot is generated based on the collected image and distance information. In some examples, virtual boundaries are defined around the payload robot based on the geometric model to navigate with obstacle avoidance.

The invention relates to a device for managing the movements of a robot configured to treat a surface, said device including: acquisition means for acquiring a three-dimensional representation (Re) of said surface to be treated; and determination means for determining a sequence of movements on the basis of said three-dimensional representation (Re) of said surface to be treated; said determination means comprising at least one three-dimensional generic model (m1-m3) for which a plurality of sequences of movements (Tx) are known; said device including adjustment means for adjusting said generic model (m1-m3) with said three-dimensional representation (Re) of said surface to be treated that are able to deform said generic model (m1-m3) and known sequences of movements (Tx) so as to correspond to said three-dimensional representation (Re) of said surface to be treated.