Industrial Automation Code Analysis for Rule Checking and Tag Usage
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Solution Overview
Problem
Industrial automation system design and troubleshooting are hindered by the lack of guidance in preventing incompatible object usage and invalid connections, leading to inefficient design processes and resource-intensive troubleshooting, often requiring external expertise for minor adjustments.
Innovation Solution
Implementing AI and machine learning to enforce design rules, suggest compatible components and connections, and provide remedial actions based on historical data, while also enabling a light engineering client environment for operators to make minor adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If designers manually review previous designs and specifications to ensure compatibility, then design accuracy is improved, but design time and productivity deteriorate
Solution Approach 1:
The system performs preliminary compatibility checking and validation rules enforcement during the design phase, automatically identifying incompatible object combinations before they are implemented. This prevents design errors early in the process, maintaining high design accuracy while reducing the time designers would otherwise spend on manual review and troubleshooting later.
Solution Approach 2:
The system provides real-time feedback to designers about compatibility issues, invalid connections, and violations of best practices as they are created. This immediate feedback mechanism allows designers to correct errors during the design process rather than discovering them later, improving both design accuracy and productivity.
2Stability of the object's composition
If designers manually update object names according to naming conventions, then naming consistency is improved, but time consumption and error rate deteriorate
Solution Approach 1:
The system automatically enforces naming conventions by detecting when object names violate established conventions and prompting designers to update them. This self-service approach maintains naming consistency without requiring manual intervention for each name change, significantly reducing time consumption and human error while ensuring stable, consistent naming across the design.
3Manufacturing precision
If external expertise is brought in to troubleshoot issues, then problem resolution accuracy is improved, but system downtime and cost deteriorate
Solution Approach 1:
The system provides comprehensive feedback including error messages, warnings, and guidance about best practices throughout the design and operation phases. This built-in feedback mechanism enables operators to diagnose and resolve common issues independently without requiring external expertise, reducing system downtime while maintaining effective problem resolution for complex issues.
Solution Approach 2:
The system acts as an intermediary between operators and complex troubleshooting scenarios by providing automated diagnostic capabilities and guidance. This intermediary function empowers operators to handle routine issues independently while still enabling access to external expertise when needed, optimizing both response time and resolution accuracy.
4Reliability
If design rules are enforced to prevent incompatible objects, then system reliability is improved, but design flexibility and ease of operation deteriorate
Solution Approach 1:
The system provides intelligent feedback that informs designers about compatibility issues and suggests corrective actions rather than simply blocking design choices. This approach maintains system reliability by preventing incompatible configurations while preserving design flexibility by allowing designers to understand the rationale and make informed decisions about their design choices.
Data Source
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AI summary
A system includes a processor and a memory accessible by the processor. The memory stores instructions that, when executed by the processor, cause the processor to receive an industrial automation project code file, wherein the industrial automation project code file defines one or more operations of an industrial automation system during performance of an industrial automation process, retrieve a set of industrial automation rules associated with a set of best practices for project code files, analyze the industrial automation project code file based on the set of industrial automation rules, including identifying one or more instances of inefficient tag usage, and identifying one or more sets of parallel overlapping tasks, and generate a report based the analysis of the industrial automation project code file based on the set of industrial automation rules.