Industrial IDE AI Code Conversion From Plain Language
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Solution Overview
Problem
Conventional industrial control systems require specialized knowledge and extended time for programming and configuration, limiting development to skilled engineers due to the need for programming languages, device configuration settings, and understanding of industrial control processes and standards.
Innovation Solution
An integrated development environment (IDE) system utilizing generative artificial intelligence (AI) to interpret plain language inputs and generate industrial control code in a desired format, supported by a generative AI model trained on industrial control code samples, standards, and protocols, facilitating user-friendly development across the automation lifecycle.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional programming approaches are used with specialized programming languages and device configuration settings, then control functionality and reliability are achieved, but the complexity of operation and time required for development increase significantly
Solution Approach 1:
The patent introduces an intermediary translation layer that converts natural language user input into standardized control code. This mediator component bridges the gap between user-friendly input and complex control functionality, allowing non-specialists to program industrial controllers without directly writing complex control code, thereby maintaining reliability while reducing operational complexity
Solution Approach 2:
The patent replaces the mechanical process of manually writing and configuring control code with an automated natural language processing system. Instead of requiring users to manually construct control logic using specialized programming languages, the system automatically generates control code from natural language descriptions, substituting the manual mechanical process with an intelligent automated system
2Manufacturing precision
If conventional programming approaches are used with specialized knowledge requirements, then control precision and adherence to industrial standards are maintained, but the time required for development and the need for expert engineers increase
Solution Approach 1:
The patent implements preliminary action by pre-configuring standardized control templates and industrial standard compliance rules within the natural language processing system. The system is pre-loaded with knowledge of industrial standards and best practices, allowing it to automatically generate compliant control code without requiring users to have expert knowledge or spend time learning standards, thereby maintaining precision while reducing development time
Solution Approach 2:
The system enables self-service by automatically generating compliant control code from natural language input without requiring expert intervention. The automated system serves itself by incorporating industrial standard compliance checks and generating ready-to-deploy control code, eliminating the need for expert engineers to manually review and adjust each piece of code, thus reducing development time while maintaining precision
3Adaptability or versatility
If conventional configuration methods are used with multiple device-specific applications, then device compatibility and control functionality are achieved, but the complexity of the development process and number of tools required increase
Solution Approach 1:
The patent implements universality by creating a single natural language processing platform that can generate control code for multiple different device types and programming languages. Instead of requiring separate configuration applications for each device, the universal system translates natural language input into device-specific code, maintaining adaptability across different controllers while reducing the complexity of using multiple specialized tools
Data Source
AI summary
An integrated development environment (IDE) for designing, programming, and configuring aspects of an industrial automation system uses a generative artificial intelligence (AI) model and associated neural networks to generate portions of an industrial automation project in accordance with functional requirements provided to the industrial IDE system in intuitive formats, such as spoken or written plain language text. The system uses generative AI to translate plain language requests or functional specifications into industrial control code, human-machine interface (HMI) applications, device configuration settings, or other aspects of an industrial control project.