Industrial Automation Rules Engine for Compatibility Checking
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Solution Overview
Problem
Designing industrial automation systems is time-consuming and prone to errors due to manual code writing, incompatible object usage, and lack of real-time troubleshooting capabilities, requiring highly skilled designers and causing inefficiencies in system modifications.
Innovation Solution
Implementing AI and machine learning to enforce design rules, suggest compatible component interactions, provide historical troubleshooting guidance, and enable light engineering clients for minor adjustments, along with automated naming conventions and project code analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual code writing is used for each device and object, then design flexibility is maintained, but design time and error rate increase significantly
Solution Approach 1:
The system performs preliminary actions by automatically generating code for each device and object before the designer needs to use it. The code is pre-written with proper naming conventions, comments, and interconnections already established, eliminating the need for manual code writing during the design process.
Solution Approach 2:
The design system serves itself by automatically generating code, updating naming conventions, and maintaining consistency across devices and objects without requiring manual intervention. The system self-corrects and self-updates based on the configured naming convention rules.
2Reliability
If designers manually update object names according to naming conventions, then naming consistency is maintained, but time consumption and human error increase
Solution Approach 1:
The system automatically maintains naming consistency by self-updating object names according to the configured naming convention. When devices or objects are added, removed, or modified, the system automatically adjusts names and updates all related code references without human intervention, ensuring consistency while eliminating manual work.
Solution Approach 2:
The system implements feedback mechanisms that automatically detect when naming convention rules are violated and trigger automatic corrections. The system monitors name changes, updates cross-references, and ensures consistency throughout the project by continuously checking and adjusting names based on the configured conventions.
3Adaptability or versatility
If designers are free to use incompatible objects without warnings, then design freedom is maintained, but system operability may be compromised
Solution Approach 1:
The system applies preliminary anti-action by proactively preventing incompatible object combinations before they can cause system failures. The compatibility checking mechanism identifies potential conflicts between devices and objects and either blocks their combination or issues warnings, preventing operability issues before they arise while still allowing valid designs.
4Reliability
If highly skilled designers are required to design automation systems, then design quality is maintained, but resource availability and cost increase
Solution Approach 1:
The system performs self-service by automatically generating high-quality code, maintaining naming conventions, and ensuring system consistency without requiring highly skilled designers for these routine tasks. The automation handles code generation, name updates, and compatibility checking, allowing less experienced designers to produce reliable results.
Solution Approach 2:
The system replaces the mechanical skill-based process of manual code writing and consistency checking with an automated computational system. Instead of relying on designer expertise and manual effort, the system uses algorithms and rules to automatically maintain design quality, reducing the skill threshold while preserving output quality.
5Measurement precision
If troubleshooting requires taking the system offline and bringing in engineers, then problem diagnosis accuracy is maintained, but system availability and response time decrease
Solution Approach 1:
The system implements continuous feedback mechanisms that automatically monitor system operation, detect issues, and provide real-time troubleshooting guidance. The feedback loop captures system state information, compares it against known problem patterns, and suggests or automatically applies corrections without taking the system offline, maintaining both availability and diagnostic accuracy.
Data Source
AI summary
A (GUI) for designing an industrial automation system includes a design window and a first accessory window. The GUI presents a library visualization representative of a plurality of objects within the first accessory window, each object is represented by an icon and corresponds to a respective industrial automation device. The GUI receives inputs indicative of a selection of one or more objects of the plurality of objects from the library, presents the one or more objects in the design window, determines that the one or more inputs do not comply with a set of industrial automation system rules comprising one or more relationships between a plurality of industrial automation devices, and displays a warning message that the one or more inputs do not comply with the set of industrial automation system rules.