Confidence Heat Maps for AI Reliability in P&ID Documents
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Solution Overview
Problem
The automation of process automation systems in industrial plants is hindered by the limited use of digital data exchange standards and the lack of integration of AI/ML model confidence/uncertainty values in process design specification documents, leading to manual efforts and underutilized automation potential.
Innovation Solution
A method to generate a confidence heat map based on structured representations of information, overlaying input documents to indicate AI/ML model confidences, allowing for joint confidence estimations and visualization of uncertainties, thereby enhancing the understanding of AI reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If AI/ML models are used to process process design specification documents, then productivity and automation potential are improved, but reliability and understandability of results deteriorate due to lack of confidence/uncertainty visualization
Solution Approach 1:
The patent applies color-coded heat maps to visualize AI confidence levels, where different colors represent different confidence thresholds. This allows engineers to quickly assess the reliability of AI-generated information without sacrificing automation benefits, directly resolving the contradiction between productivity improvement and reliability maintenance.
Solution Approach 2:
The confidence heat map acts as an intermediary layer between the AI model and the engineer, providing transparent visualization of uncertainty. This mediator enables engineers to understand AI reliability while maintaining automation efficiency, bridging the gap between automated processing and trusted decision-making.
2Ease of operation
If confidence estimations are visualized using heat maps, then ease of operation and understanding are improved, but device complexity increases due to additional processing requirements
Solution Approach 1:
The patent merges the confidence visualization directly with the original process design specification documents by overlaying heat maps. This integration allows engineers to evaluate AI reliability within the existing document context without requiring separate complex visualization systems, improving ease of operation while managing complexity through consolidation.
Data Source
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AI summary
There is disclosed a method to assist in evaluating confidence estimations in a structured representation of information in an industrial plant context. The method comprises obtaining a target structured representation of information comprising one or more target pieces of information associated with confidence estimations determined by an information model, wherein at least part of the one or more target pieces of information overlap with one or more pieces of information comprised by one or more different structured representations. The method further comprises 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. The method further comprises 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.