AI Control Application Builder Using 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 processor configured to execute an automatic control application generator, which includes a control narrative interpretation engine, a diagram interpretation engine, and a unified knowledge integrator to process control narratives, diagrams, and integrate knowledge to generate an industrial control application.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If manual processes are used to generate industrial control applications, then engineers can exercise judgment and adaptability, but the process becomes time-consuming and resource-intensive

Engineering Contradiction:

Improveengineer judgment and adaptabilityVSAvoidapplication generation speed

Core Design Contradiction:

Adaptability or versatilityVSProductivity

Solution Approach 1:

An AI-based intermediary system (control application generator) is introduced between the engineer's requirements and the final control application. The system includes a control narrative interpretation engine, diagram interpretation engine, and control application builder that work together to automatically generate applications while allowing engineers to provide high-level guidance through control narratives and diagrams, thus maintaining adaptability while dramatically improving productivity

Inventive Principle:

Principle #24Intermediary (Mediator)

2Adaptability or versatility

If manual processes are used to generate industrial control applications, then flexibility in handling complex requirements is maintained, but human error and variability increase

Engineering Contradiction:

Improveflexibility in handling requirementsVSAvoidconsistency and error reduction

Core Design Contradiction:

Adaptability or versatilityVSReliability

Solution Approach 1:

The system incorporates feedback mechanisms where the AI-based generator continuously refines its understanding of requirements through iterative processing of control narratives and diagrams. The system provides feedback to engineers about generated applications and allows for corrections, while internally using feedback loops to improve accuracy and consistency, thereby reducing human error while maintaining flexibility

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The patent replaces the mechanical human cognitive process with an AI-based system that processes control narratives and diagrams through machine learning models. This substitution eliminates human variability and error while maintaining the ability to handle complex requirements through advanced algorithms and pattern recognition

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Productivity

If automated systems are introduced to generate control applications, then productivity increases, but the system complexity increases

Engineering Contradiction:

Improveapplication generation speedVSAvoidsystem architecture complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The automated system is segmented into distinct functional modules: a control narrative interpretation engine for processing text requirements, a diagram interpretation engine for processing visual diagrams, and a control application builder for generating the final application. This segmentation manages system complexity by creating independent, manageable components that can be developed and maintained separately while working together to achieve high productivity

Inventive Principle:

Principle #1Segmentation

4Loss of time

If fully automated generation is implemented, then time consumption is reduced, but the need for manual intervention increases initially

Engineering Contradiction:

Improveapplication development timeVSAvoidmanual setup and training requirements

Core Design Contradiction:

Loss of timeVSDevice complexity

Solution Approach 1:

The system requires preliminary actions in the form of control narratives and diagrams that capture requirements upfront. These preliminary inputs are processed by the AI system to generate the control application, reducing iterative manual work later. The preliminary action phase establishes a structured foundation that enables rapid automated generation while minimizing the need for subsequent manual interventions

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS20250155871A1Ai-based automatic control application generation

Publication Date: 2025.05.15 SCHNEIDER ELECTRIC SYSTEMS USA INC

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, logic diagrams, and P&IDs 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 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.