Automation Logic Diagnostics for Rule-Based Design Validation
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Solution Overview
Problem
Industrial automation system design and troubleshooting are hindered by the lack of guidance in existing design environments, leading to inefficiencies and errors due to the freedom to use incompatible objects and invalid connections, requiring extensive manual updates and reliance on skilled designers for modifications and troubleshooting.
Innovation Solution
Implementing AI and machine learning to enforce design rules, suggest compatible components and connections, provide historical data-based troubleshooting suggestions, and enable minor adjustments through a light engineering client environment, thereby automating code generation and maintaining naming conventions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If designers are given freedom to use any objects and connections in industrial automation systems, then design flexibility and adaptability are improved, but system reliability and design quality deteriorate due to incompatible objects and invalid connections
Solution Approach 1:
The system performs preliminary validation of design elements before they are instantiated in the automation system. Design rules are enforced during the design phase to prevent incompatible objects and invalid connections from being created, rather than detecting them after the fact. This preliminary action ensures reliability is maintained while preserving design flexibility.
Solution Approach 2:
The system provides real-time feedback to designers about design rule violations, compatibility issues, and potential errors as they are creating the automation system. This feedback mechanism guides designers toward valid design choices without restricting their creativity, thus maintaining both reliability and adaptability.
2Manufacturing precision
If manual updates are required for naming conventions and component modifications, then design precision can be maintained, but productivity and time efficiency deteriorate due to tedious manual updates
Solution Approach 1:
The system automatically updates naming conventions and component references without requiring manual intervention. When a component is added, removed, or modified, the system self-updates all related naming conventions and connections, eliminating tedious manual work while maintaining precision through automated rule enforcement.
Solution Approach 2:
The system performs automatic updates and propagations of naming conventions as a preliminary action when design changes are made. Rather than requiring designers to manually update names after making changes, the system proactively handles the updating process, improving productivity without sacrificing naming precision.
3Measurement precision
If extensive manual troubleshooting is required when issues arise, then diagnostic accuracy can be achieved, but time to resolve problems and system availability deteriorate
Solution Approach 1:
The system provides automated diagnostic feedback by monitoring the automation system for rule violations and potential issues. When problems arise, the system immediately identifies and reports the specific violation or error, providing accurate diagnostic information that speeds up resolution while maintaining diagnostic precision through systematic analysis.
Solution Approach 2:
The system performs preliminary detection and diagnosis of potential issues before they manifest as full system failures. By continuously monitoring design elements against established rules, the system identifies problems early and provides diagnostic information in advance, reducing both troubleshooting time and maintaining accuracy.
4Reliability
If highly trained designers are required to design and modify industrial automation systems, then design quality and system reliability are improved, but ease of operation and accessibility deteriorate
Solution Approach 1:
The system acts as an intermediary between operators and the complex design rules of industrial automation systems. It provides automated guidance, validation, and assistance that enables operators with less training to perform design and modification tasks while maintaining design quality through enforced rules and best practices.
Solution Approach 2:
The system provides self-service capabilities through automated design rule enforcement, validation, and guidance. This enables operators to independently perform design tasks with confidence that their work meets quality standards, reducing the need for highly trained designers while maintaining design reliability.
Data Source
AI summary
A method includes receiving an input indicative of a selection of an object associated with an industrial automation project, each object of a plurality of objects corresponding to a respective industrial automation component, retrieving logic associated with the object from a storage component, evaluating an operability of the logic when executed by the respective industrial automation component corresponding to the object, wherein evaluating the operability of the logic comprises running one or more scripts, executing one or more algorithms, applying one or more rules, or a combination thereof, and updating a GUI to present: a first window visualization comprising a logic schematic visualization of one or more tasks that the logic is configured to cause the object to perform and a second window visualization comprising an indication of the operability of the logic when executed by the respective industrial automation component.