Abstract: A hot gas path component assembly includes a first component portion that includes a first set of interlocking features and a second component portion that includes a second set of interlocking features mechanically coupled to the first set of interlocking features. A fill material is disposed at an interface between at least one surface of the first set of interlocking features and at least one surface of the second set of interlocking features. The fill material is disposed during a joining process. The second component portion is joined to the first component portion via both the fill material and the first and second sets of interlocking features.

Abstract: There are provided a system and a method of use thereof for executing a manufacturing process. For example, a method can include executing, by a system configured to drive the manufacturing process, a set of manufacturing functions based on a digital model of a first part. The method can include fetching, by the system, from an in-field scoring system, performance data relating to a second part. The method can further include constructing the digital model based on the performance data relating to the second part. The method can further include generating, based on the digital model, a forecast representative of a performance of the first part and generating the set of manufacturing functions based on the digital model and the forecast. The method further includes manufacturing the first part according to the set of manufacturing functions.

Abstract: A hot gas path component assembly includes a first component portion that includes a first set of interlocking features and a second component portion that includes a second set of interlocking features mechanically coupled to the first set of interlocking features. A fill material is disposed at an interface between at least one surface of the first set of interlocking features and at least one surface of the second set of interlocking features. The fill material is disposed during a joining process. The second component portion is joined to the first component portion via both the fill material and the first and second sets of interlocking features.

Abstract: There is provided a method for optimizing a manufacturing process of a new part. The method includes executing, by a system configured to drive the manufacturing process, a set of manufacturing functions. Executing these functions include receiving data associated with one or more field parts similar to the new part, and generating, based on the data, a forecast representative of a longevity of the one or more parts. The method further includes generating a digital thread forming a surrogate model for the new part, based on the forecast. Further, the method includes creating the set of manufacturing functions based on the surrogate model and manufacturing the new part according to the set of manufacturing functions.

Abstract: There are provided methods and systems for optimizing a manufacturing process. For example, there is provided a method for generating a model for driving a decision of a manufacturing process. The method includes simultaneously receiving data from a plurality of sources and executing a machine learning-based procedure on the data. The method further includes updating a physics-based model corresponding to the model in real time based on a result of the machine learning-based procedure.

Abstract: There are provided methods and systems for optimizing a manufacturing process. For example, there is provided a method for optimizing a manufacturing process of a new part. The method includes executing, by a system configured to drive the manufacturing process, a set of manufacturing. The method includes receiving data associated with one or more fielded parts. The method further includes generating a first model associated with the one or more fielded parts and updating a second model associated with the new part based on the first model. The method further includes manufacturing the new part according to the updated second model.

Abstract: There is provided a method for optimizing a manufacturing process of a new part. The method includes executing, by a system configured to drive the manufacturing process, a set of manufacturing functions. Executing these functions include receiving data associated with one or more field parts similar to the new part, and generating, based on the data, a forecast representative of a longevity of the one or more parts. The method further includes generating a digital thread forming a surrogate model for the new part, based on the forecast. Further, the method includes creating the set of manufacturing functions based on the surrogate model and manufacturing the new part according to the set of manufacturing functions.

Abstract: There are provided a system and a method of use thereof for executing a manufacturing process. For example, a method can include executing, by a system configured to drive the manufacturing process, a set of manufacturing functions based on a digital model of a first part. The method can include fetching, by the system, from an in-field scoring system, performance data relating to a second part. The method can further include constructing the digital model based on the performance data relating to the second part. The method can further include generating, based on the digital model, a forecast representative of a performance of the first part and generating the set of manufacturing functions based on the digital model and the forecast. The method further includes manufacturing the first part according to the set of manufacturing functions.

Abstract: There are provided methods and systems for optimizing a manufacturing process. For example, there is provided a method for generating a model for driving a decision of a manufacturing process. The method includes simultaneously receiving data from a plurality of sources and executing a machine learning-based procedure on the data. The method further includes updating a physics-based model corresponding to the model in real time based on a result of the machine learning-based procedure.

Abstract: A method of software clamping a video signal for waveform display on a general purpose oscilloscope where the video signal is a.c. coupled to an input of the oscilloscope includes acquiring samples of the video signal in response to a trigger signal derived from the video signal, which samples are then stored. Then samples relative to the trigger signal that are at a nominally known voltage are retrieved, averaged and compared to a reference value. The reference value may be a value determined from a first acquisition of the video signal or a value corresponding to the nominally known voltage. The difference between the averaged samples and the reference value is then used to adjust the sample values when retrieved for display by the oscilloscope.