Generative AI Prompt Workflow for Industrial Control Code
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Solution Overview
Problem
Conventional industrial control programming requires specialized knowledge and extends development time due to the need for expert understanding of programming languages, device configuration, and industrial control processes, limiting it to skilled engineers.
Innovation Solution
An integrated development environment (IDE) using generative AI techniques generates control code and configures industrial controllers through natural language inputs, leveraging custom models and generative AI models to assist in programming and configuration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional control programming methods are used, then control code can be generated with high precision and reliability, but the development time increases and the system becomes accessible only to specialized engineers
Solution Approach 1:
The patent introduces an AI assistant as an intermediary between the natural language interface and the control programming system. This AI intermediary translates user requirements into proper control code, maintaining reliability while reducing development time. The AI assistant serves as a mediator that understands both natural language and industrial control programming requirements.
Solution Approach 2:
The patent replaces the mechanical process of manual control code writing with an AI-based automated system. Instead of engineers manually programming controllers using specialized languages, the system uses natural language processing and AI model prompting to generate control code automatically, significantly reducing development time while maintaining code quality.
2Reliability
If conventional control programming methods are used, then control code can be generated with high reliability, but the device complexity and difficulty of operation increase
Solution Approach 1:
The patent replaces complex manual programming operations with an AI-based automated system. The system substitutes the need for engineers to manually write and debug control code with an AI assistant that automatically generates reliable control code from natural language descriptions, thereby reducing programming complexity while maintaining code quality.
Solution Approach 2:
The AI assistant acts as an intermediary that handles the complexity of control programming. It translates simple natural language requirements into complex control code, shielding users from programming complexity while ensuring reliable code generation. The intermediary manages the transformation process automatically.
3Reliability
If conventional control programming methods are used, then control code can be generated with high reliability, but the ease of operation decreases and accessibility to specialized engineers is required
Solution Approach 1:
The patent replaces the specialized knowledge-based programming process with an AI-driven natural language interface. Users no longer need to learn complex control programming languages or understand detailed device configuration settings. The AI system handles the translation from natural language to reliable control code, making the system accessible to non-specialists while maintaining code quality.
Solution Approach 2:
The patent creates a universal interface that works across different control devices and programming paradigms. The AI assistant can handle various types of control code generation tasks through a single natural language interface, eliminating the need for users to learn device-specific programming languages and making the system universally accessible.
4Loss of time
If AI-based control code generation is implemented, then development time is reduced and accessibility is improved, but the extent of automation increases requiring new approaches
Solution Approach 1:
The patent introduces an AI assistant as an intermediary layer between the user and the automation system. This intermediary manages the automated code generation process, handling the complexity of AI model interaction while providing a simple natural language interface. The mediator enables high-level automation while maintaining user control and understanding.
Solution Approach 2:
The patent segments the control programming task into multiple stages: natural language input, AI analysis, code generation, and validation. This segmentation allows the system to implement automation in manageable steps, with the AI assistant handling specific subtasks while maintaining overall process control and enabling progressive automation.
Data Source
AI summary
An integrated development environment (IDE) leverages a generative AI model to generate industrial control code in accordance with specified functional requirements, which can be provided to the industrial IDE system as intuitive natural language spoken or written text. The industrial IDE can also analyze written code in response to natural language prompts submitted against the code, generate answers to user-submitted questions about the code, and offer recommendations for improving the code in response to specific questions or requests submitted by the user.