Control code generation and collaboration using active machine learning
Abstract:
A control code collaboration system automatically generates control code for an industrial project based on text discovered within the design documents. The system allows a designer to highlight text within a text-based design document representing an interlock definition, step sequence definition, tag name, or other aspects of the design description. The system then allows the user to link annotations to the highlighted text, the annotations representing interlock programming, sequence programming, or controller tag names. The system then searches the document for similarly formatted text, which are assumed to represent descriptions of similar control aspects, and infers suitable control programming from these discovered pieces of text using the previously provided annotations as a guide. In this way, the system uses text pattern recognition generates suggestions as to how to program portions of the design description based on control logic examples provided by the user.
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