A method for factory analysis and/or maintenance, preferably including receiving factory information and/or associating defects with factory components, and optionally including acting based on defect associations and/or operating factory machines. The method is preferably associated with one or more manufacturing systems and/or elements thereof.

A method for factory analysis and/or maintenance, preferably including receiving factory information and/or associating defects with factory components, and optionally including acting based on defect associations and/or operating factory machines. The method is preferably associated with one or more manufacturing systems and/or elements thereof.

Provided is a method for computer-aided processing of quality information of an object manufactured by stacked printed layers in an additive manufacturing system, including the steps of: receiving a quality indicator for each printed layer of the object from the manufacturing system, assigning a color out of a predefined set of colors to each quality indicator depending on the value of the quality indicator, visualizing the quality indicators of the received manufactured layers as a sequence of colored bars ordered according to the sequence of the manufactured layers the color of each bar indicating the value of the quality indicator of the respective printed layer on a graphical user interface.

A method, system and computer program product for a heuristic determination of in-process damage class control to manage expected output product category. The heuristic technique determines the predicted damages and their ranges while keeping the initial expected defects, the respective classes and range of defect and mitigation. The method dynamically computes a damage mitigation range of operation while being within the overall constraints and completes the computation in smaller number of loops being run at the edge computers so that the manufacturing equipment can operate at a higher velocity for higher quality of the output. The method includes a step of reducing error of the co-efficient and damage counts. An Internet of Things (IoT) based robot is used to mitigate the damages in the manufacturing steps to ensure that the output class of the product remains what was expected at the start despite damages and mitigation measures.

A method includes applying a defect rule to engineering configurations in an industrial process control and automation system. This includes extracting query logic from the defect rule defining a defect. This also includes executing the extracted query logic on the engineering configurations. This further includes storing results of the executed query logic as an identified defect. The method could also include reconciling the identified defect by comparing the results of the executed query logic for a current iteration with results of the executed query logic from previous iterations and determining a current state of the identified defect based on the comparison.

An information processing apparatus acquires detection information of a physical quantity that changes according to an operation state of a target device, transmits an acquisition request to the target device at predetermined time, to acquire context information relating to an operation status of the target device in response to the acquisition request, specifies a processing period in which the target device is in the middle of processing of the target object based on the predetermined time and the context information, extracts processing period detection information of the specified processing period from the detection information, and determines an occurrence of a defect relating to processing by the target device during the processing period based on the processing period detection information and the context information used for specifying the processing period.

An approach alerting users based on a detected defect during manufacturing quality inspection based on graphical images is disclosed. The approach initiates a device inspection, wherein a model controller collects metadata about a product to be inspected and select a first model with a highest score to identify defects in the device. The approach utilizes an API to obtain results from the inspection and after determining that another model is available, initiating the second model run via an edge device performing the inspection of the device. And the algorithm awaits a response in detecting a defect during either the first model run or the second model run, providing an alert detailing the defect detected in the device.

In a component mounting system, recovery processing is repeated until a recovery count number Nr is larger than or equal to a defined count number Nth in a case where a pickup defect of a component occurs, an elapsed time is measured from error stoppage of a component mounting machine to canceling of the error stoppage in which the component mounting machine is error-stopped when the recovery count number Nr is larger than or equal to the defined count number Nth, the defined count number Nth is increased within a range in which the defined count number does not exceed the upper limit value Nmax in a case where the elapsed time is shorter than a defined time Tth, and the defined count number Nth returns to an initial value in a case where the elapsed time is longer than or equal to the defined time Tth.

A process for detecting foreign particle defects and scratch defects on semiconductor products including detecting foreign particle and scratch defects on the semiconductor products; placing the semiconductor products in a first wafer carrier and docking to a first load port of a semiconductor processing tool; opening a door of the first wafer carrier; transferring the semiconductor products from the first wafer carrier through the first load port to and through an interior of the semiconductor processing tool to a second load port of the semiconductor processing tool; transferring the semiconductor products from the second load port to a second wafer carrier; closing a door of the second wafer carrier and undocking from the second load port; and detecting foreign particle and scratch defects on the semiconductor products and comparing to the foreign particle defects on the semiconductor products prior to placing the semiconductor products in the first wafer carrier.

A defect pattern grouping method is disclosed. The defect pattern grouping method comprises obtaining a first polygon that represents a first defect from an image of a sample, comparing the first polygon with a set of one or more representative polygons of a defect-pattern collection, and grouping the first polygon with any one or more representative polygons identified based on the comparison.