AI Control Application Generation from Narratives, Logic, and P&IDs
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Solution Overview
Problem
Conventional manual processes for generating industrial control applications are time-consuming, resource-intensive, and prone to human error, requiring significant manual intervention and lacking standardization.
Innovation Solution
An automated system comprising a control narrative interpretation engine, a logic diagram interpretation engine, a piping and instrumentation diagram interpretation engine, a unified knowledge integrator, and a control application builder, which processes control narratives, logic diagrams, and P&IDs to generate a fully-functional industrial control application.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual processes are used to generate industrial control applications, then engineers can develop control applications with human judgment and adaptability, but the process becomes time-consuming and resource-intensive
Solution Approach 1:
An AI-based automatic control application generator serves as an intermediary between engineering requirements and control application output. The system includes a control narrative interpretation engine that processes natural language requirements, a diagram interpretation engine that handles P&ID and logic diagrams, and a control application builder that generates the final application, thereby automating the translation process while preserving engineering intent
Solution Approach 2:
The patent replaces the mechanical manual process of control application development with an AI-based automated system. The system uses machine learning models and natural language processing to interpret engineering requirements and automatically generate control applications, substituting human manual operations with intelligent automation while maintaining adaptability through the interpretation engines
2Adaptability or versatility
If manual processes are used to generate industrial control applications, then engineers can ensure flexibility in development approach, but human error and variability increase
Solution Approach 1:
The automatic control application generator incorporates feedback mechanisms where the system interprets engineering requirements, generates control applications, and can iterate based on validation results. The interpretation engines analyze input requirements and provide structured outputs that reduce variability, while the automated process ensures consistent application of control logic across different projects
Solution Approach 2:
The system transforms unstructured engineering requirements and diagrams into structured parameterized control applications. By converting natural language narratives and visual diagrams into standardized control logic parameters, the system maintains flexibility in input formats while ensuring consistent, error-reduced output through parameter standardization
3Productivity
If automation is introduced to generate industrial control applications, then development time is reduced, but significant manual intervention is still required
Solution Approach 1:
The automatic control application generator is divided into distinct functional modules: a control narrative interpretation engine for processing text requirements, a diagram interpretation engine for handling P&ID and logic diagrams, a unified knowledge integrator for combining multiple input sources, and a control application builder for generating the final application. This segmentation allows each module to handle specific tasks automatically, reducing the need for manual intervention across the entire development process
Data Source
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AI summary
A system for automatically generating an industrial control application includes an automatic control application generator having a control narrative interpretation engine, a logic diagram interpretation engine, and a P&ID interpretation engine that each receive inputs such as control narratives (22), logic diagrams (26), and P&IDs (24) for an industrial control system. The engines interpret and process the respective inputs to obtain and output information in data formats that can be integrated and interpreted by a unified knowledge integrator of the system. The unified knowledge integrator combines the inputs into an internal representation that is then used by a control application builder of the system to build the industrial control application. The control application builder uses the internal representation and engineering tool knowledge (36) to build the industrial control application to adhere to functional and design requirements and to be compatible with engineering tools being used with the industrial control system.