AI HMI Dashboard Generation for Faster Industrial Data Integration
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Solution Overview
Problem
Existing HMI development platforms are cumbersome and time-consuming, requiring manual coding and struggle with integrating diverse system data from multiple sources, leading to design bottlenecks that hinder real-time decision-making in industrial automation systems.
Innovation Solution
A system utilizing generative AI to create HMI dashboards based on natural language prompts, leveraging custom models trained with domain-specific data to generate display screens, layouts, and data links without manual coding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual coding and graphical development workflow are used, then HMI developers can create customized display interfaces, but the development process becomes time-consuming and cumbersome
Solution Approach 1:
The system enables self-service HMI development by allowing operators to create customized display interfaces through natural language prompts without requiring manual coding or extensive use of graphical development tools. The generative AI automatically generates the HMI code and configuration based on the operator's specifications, eliminating the time-consuming manual development process while preserving full customization capability.
Solution Approach 2:
A natural language processing intermediary is introduced between the operator and the HMI development system. This intermediary translates human language requirements into technical HMI code and configuration, bridging the gap between operator intent and system implementation without requiring the operator to manually code or use complex graphical development workflows.
2Adaptability or versatility
If traditional HMI development platforms are used, then display interfaces can be created, but integrating diverse system data from multiple sources becomes difficult
Solution Approach 1:
The HMI generation system provides universal data integration capability that can connect to multiple diverse data sources including industrial automation systems, enterprise resource planning systems, and other external systems through a unified interface. The generative AI automatically generates the necessary data binding code and configuration for integrating data from any source, eliminating the need for complex manual integration work for each different data type.
Solution Approach 2:
The system performs self-service data integration by automatically generating the code and configuration needed to connect and integrate data from multiple diverse sources. When an operator specifies data requirements in natural language, the system autonomously creates the data binding logic, connection protocols, and integration configuration, eliminating the complexity of manual integration work.
3Manufacturing precision
If manual HMI development is used, then detailed control over visual behaviors can be achieved, but design bottlenecks hinder real-time decision-making
Solution Approach 1:
The system performs preliminary action by pre-generating optimized HMI code and configuration templates that incorporate best practices for visual behavior control. The generative AI creates ready-to-use, production-ready code that maintains detailed control over visual behaviors while eliminating the iterative manual development process, enabling rapid deployment and real-time decision-making.
Solution Approach 2:
The system enables self-service HMI development where operators can specify their requirements in natural language and receive immediately generated, production-ready HMI interfaces with detailed visual behavior control. This eliminates the time-consuming manual coding process while maintaining full control over visual behaviors, enabling rapid iteration and real-time decision-making.
Data Source
AI summary
A human-machine interface (HMI) development and runtime system leverages generative artificial intelligence (AI) to create HMI dashboards or graphical interfaces without the need for manual coding based on natural language prompts submitted by the user, which specify the information the user wishes to see. In one or more embodiments, the system can support industry-specific prompt engineering services that assist a user in generating a customized HMI dashboard that satisfies specified criteria using natural language prompts that describe functional and visual requirements of the dashboard. The system can make use of a generative AI model and associated neural networks to generate suitable dashboards in accordance with functional requirements provided to the system as intuitive natural language inputs (e.g., spoken or written natural language text).