Robotic Process Automation for Standard Operating Procedure Conversion
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Solution Overview
Problem
Industrial facilities face significant challenges in converting thousands of standard operating procedures from various structural and application-based formats into an intelligent format, requiring manual effort that is time-consuming and resource-intensive.
Innovation Solution
The implementation of a robotic process automation system that learns procedure document formatting and transforms the content into an intelligent format, utilizing business process management and artificial intelligence to automate the conversion process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual conversion is used to transform procedures from various formats to intelligent format, then conversion accuracy can be maintained, but the time and resources required increase significantly
Solution Approach 1:
The patent replaces the manual mechanical conversion process with an automated robotic process automation system that uses AI models and machine learning algorithms to perform format transformation, thereby reducing time consumption while maintaining conversion accuracy through intelligent document analysis and transformation
Solution Approach 2:
The system enables procedures to convert themselves automatically from various source formats to intelligent format without human intervention. The robotic process automation system extracts content from source documents, transforms it through AI models, and generates standardized intelligent format procedures autonomously
2Ease of manufacture
If manual conversion is used for thousands of procedures, then format transformation can be completed, but the resource consumption and effort required become unsustainable
Solution Approach 1:
The patent substitutes manual human effort with an automated robotic process automation system that handles format conversion at scale. The system uses document processing bots, AI models, and machine learning algorithms to transform thousands of procedures efficiently without requiring proportional human resources
Solution Approach 2:
The robotic process automation system is designed to handle multiple source formats (Word, Excel, PDF, custom formats) and convert them all to a unified intelligent format using the same automated pipeline, making the conversion process universally applicable across diverse document types without requiring separate manual efforts for each format
3Productivity
If automated robotic process automation is implemented, then conversion speed and productivity increase, but system complexity increases
Solution Approach 1:
The patent divides the complex conversion system into modular components: document processing bots that handle specific format types, AI models for content extraction and transformation, machine learning algorithms for format recognition, and standardized output generators. Each module handles a specific aspect of the conversion process, making the overall complex system manageable through clear segmentation of functions
4Adaptability or versatility
If diverse source formats are supported, then the system's adaptability improves, but the complexity of maintaining consistent conversion quality increases
Solution Approach 1:
The patent implements a universal robotic process automation framework that can process multiple source formats (Word documents, Excel spreadsheets, PDF files, custom proprietary formats) through the same automated pipeline. The system uses format detection algorithms and adaptable extraction templates to maintain consistent conversion quality across diverse input types without requiring separate manual processes for each format
Data Source
AI summary
A system extracts procedure content from a procedure in a source format in a source document. The system identifies, in the procedure content, first section content in a first section and second section content in a second section. The system identifies, in a template for the procedure, a primary section that corresponds to the first section in the source document, and a secondary section that corresponds to the second section in the source document, The system transforms the first section content from the source format into first transformed content in a target format for the primary section and the second section content from the source format into second transformed content in a target format for the secondary section. The system stores the first transformed content and the second transformed content as part of a standardized format procedure in a procedure repository, and provides user access to the standardized format procedure.


