Industrial IDE AI Input Tools for Reliable Control Code Generation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional industrial control programming requires specialized knowledge, restricting development to experts and extending development time due to the need for programming language proficiency and understanding of industrial standards.
Innovation Solution
An integrated development environment (IDE) utilizing generative AI to generate industrial control programs and device configurations based on natural language inputs, leveraging custom models trained with industrial knowledge to assist in programming and code generation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional programming approaches are used, then programming precision and control reliability are improved, but ease of operation deteriorates and loss of time increases
Solution Approach 1:
The patent introduces an AI assistant as an intermediary between the user and the industrial controller programming interface. The AI assistant translates natural language user requirements into structured control program code, eliminating the need for users to directly learn programming languages while maintaining system reliability through validated code generation.
Solution Approach 2:
The patent replaces the mechanical process of manual code writing and syntax checking with an AI-based automated system. The AI assistant performs the mechanical task of translating high-level user intentions into executable control code, substituting the manual programming mechanism with an intelligent automation mechanism.
2Measurement precision
If conventional programming approaches are used, then programming precision is improved, but loss of time increases
Solution Approach 1:
The AI assistant performs preliminary actions by pre-processing user natural language inputs, automatically structuring them into valid control program syntax before execution. This preliminary code generation and validation step eliminates the need for users to manually write and debug code, significantly reducing development time while maintaining precision through AI-driven syntax verification.
3Reliability
If specialized knowledge requirements are maintained, then control reliability is improved, but ease of operation deteriorates
Solution Approach 1:
The AI assistant creates a simplified copy or abstraction layer between user intent and actual control code. Instead of requiring users to directly manipulate complex programming syntax, the AI generates equivalent control code from simplified natural language descriptions, allowing non-experts to access reliable control functionality without learning specialized programming knowledge.
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.