Confidence Heat Map Overlay for AI Document Reliability
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Solution Overview
Problem
The manual effort in automation engineering of process automation systems in industrial plants is significant due to limited support for interpreting and processing process design specification documents, and the automation potential is underutilized despite existing digital data exchange standards.
Innovation Solution
A method and apparatus using AI-based processing to generate confidence heat maps that overlay process design specification documents, providing visualizations of AI/ML model uncertainties to assist engineers in understanding the reliability of AI processing results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If AI/ML models are used to process process design specification documents, then productivity and automation are improved, but reliability and ease of operation deteriorate due to model uncertainties and lack of interpretability
Solution Approach 1:
The patent implements feedback by generating confidence heat maps that visually represent AI model confidence levels across different regions of process design documents. This feedback mechanism allows users to identify low-confidence regions and review them manually or trigger reprocessing, thereby maintaining high productivity while addressing reliability concerns through continuous confidence monitoring and iterative improvement.
Solution Approach 2:
The confidence heat map serves as an intermediary between the AI/ML model and the end user. It translates complex model confidence metrics into an intuitive visual format that bridges the gap between automated processing and human understanding, enabling users to quickly assess reliability without compromising processing speed.
2Productivity
If AI/ML models process process design specification documents, then productivity increases, but ease of operation worsens due to difficulty in understanding and interpreting AI results
Solution Approach 1:
The patent employs color changes in confidence heat maps to represent different confidence levels, with distinct color ranges indicating high, medium, and low confidence regions. This visual encoding makes AI processing results immediately interpretable, allowing users to quickly understand model confidence without complex technical analysis, thus maintaining ease of operation alongside high productivity.
3Reliability
If confidence heat maps are generated and overlaid on input documents, then reliability and ease of operation are improved, but device complexity increases
Solution Approach 1:
The patent creates a visual copy of the original process design document with overlaid confidence heat maps rather than modifying the underlying AI model architecture. This approach maintains the original document integrity while adding confidence information as a separate visual layer, thereby improving reliability and interpretability without significantly increasing system complexity.
Data Source
AI summary
A method to assist in evaluating confidence estimations in a structured representation of information in an industrial plant context includes obtaining a target structured representation of information comprising one or more target pieces of information associated with confidence estimations determined by an information model, generating a confidence heat map based on the target structured representation, wherein the generated confidence heat map indicates confidences for the one or more target pieces of information based on the associated confidence estimations, and laying the generated confidence heat map over at least part of an input document of one or more input documents inputted to the IM and based on which the target structured representation and the one or more different structured representations are obtained by the IM, wherein the one or more input documents are associated with a same process plant.