Abstract: A method collects and presents hierarchical data. The method includes receiving objective user inputs applied to a set of objective objects of a set of objects, receiving topic user inputs applied to a set of topic objects of the set of objects, and receiving settlement user inputs applied to a set of settlement objects of the set of objects. The method further includes applying a guidance categorization model to a guidance object of the set of topic objects to a generate a guidance label for the guidance object, applying a blocker categorization model to a blocker object of the set of topic objects to generate a blocker label for the blocker object, and applying a diagram metrics model to the set of objects to generate diagram metrics data. The method further includes presenting a topic diagram using the guidance label, the blocker label, and the diagram metrics data.

Abstract: Methods and systems for inspecting a product, such as a wire harness, including product features for inspection. A camera of an inspection station may capture a product image. A machine learning (ML) model may detect one or more objects in the captured product image and provide, for each detected object, an identification of a class of the detected object and an identification of a region of the detected object in the captured product image. The class of the detected object may be either an acceptable product feature class or an unacceptable product feature class. The inspection station may display an enhanced product image that includes the captured product image to which the identification of the class of the detected object and the identification of the region of the detected object in the captured product image for each detected object have been added.

Abstract: Methods and systems for inspecting a product, such as a wire harness, including product features for inspection. A camera of an inspection station may capture a product image. A machine learning (ML) model may detect one or more objects in the captured product image and provide, for each detected object, an identification of a class of the detected object and an identification of a region of the detected object in the captured product image. The class of the detected object may be either an acceptable product feature class or an unacceptable product feature class. The inspection station may display an enhanced product image that includes the captured product image to which the identification of the class of the detected object and the identification of the region of the detected object in the captured product image for each detected object have been added.

Abstract: A software component, is constructed on the basis of a set of predetermined rules, and by utilizing a source object, a token value and a parameter, wherein the source object is stored in a source object repository, and wherein the source object comprises a component value and/or a token value, wherein the component value may be associated with the token value. For constructing the software component, the token value is processed and a token result, obtained by processing the token value, is utilized for constructing the software component, wherein the parameter may also be utilized for the processing of the token value and/or constructing the software component.

Abstract: A software component, is constructed on the basis of a set of predetermined rules, and by utilizing a source object, a token value and a parameter, wherein the source object is stored in a source object repository, and wherein the source object comprises a component value and/or a token value, wherein the component value may be associated with the token value. For constructing the software component, the token value is processed and a token result, obtained by processing the token value, is utilized for constructing the software component, wherein the parameter may also be utilized for the processing of the token value and/or constructing the software component.