Engineering Diagram Automation Using Knowledge Graph Recommendations
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Solution Overview
Problem
The traditional manual design of engineering diagrams, particularly Piping and Instrumentation Diagrams (P&IDs), faces challenges such as expertise drain, inefficiency, human error, and lack of scalability, leading to increased costs and delays in large-scale projects.
Innovation Solution
A method and system that utilize a knowledge graph with semantically tagged nodes and edges, combined with natural language processing and machine learning algorithms, to semi-automate the design process by interpreting user queries, predicting diagram elements and connections, and validating recommendations based on historical data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual design process is used with expert knowledge, then design accuracy is improved, but productivity deteriorates
Solution Approach 1:
The system creates a digital copy of expert knowledge by training machine learning models on historical P&ID data and expert designs. This digital replica captures design patterns, standards, and best practices, enabling the system to generate accurate designs without requiring constant human expert intervention, thus resolving the contradiction between maintaining high design accuracy and improving productivity.
Solution Approach 2:
The patent replaces the mechanical system of manual expert design with an automated computational system using machine learning algorithms and natural language processing. This substitution maintains design quality through algorithmic validation while dramatically increasing design speed and reducing dependency on human experts, thereby resolving the productivity-accuracy tradeoff.
2Manufacturing precision
If more experts are involved in design process, then design quality is improved, but device complexity deteriorates
Solution Approach 1:
The system introduces an intermediary layer between raw design requirements and final P&ID outputs. This intermediary consists of machine learning models that process design specifications, validate against multiple expert rules simultaneously, and generate consistent designs. This intermediary manages the complexity by centralizing validation logic rather than requiring multiple independent experts to coordinate, thus maintaining design quality while reducing process complexity.
3Productivity
If standard templates are used, then productivity is improved, but adaptability deteriorates
Solution Approach 1:
The system implements dynamic templates that can adapt to specific project requirements. Instead of static standard templates, the machine learning models generate context-aware design patterns that automatically adjust based on the particular project's industry, scale, and specific requirements. This dynamic approach maintains the speed benefits of templating while achieving the adaptability of custom design through automated parameter adjustment and pattern selection.
Data Source
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AI summary
Disclosed is a method (100) for semi-automating design of engineering diagrams. The method comprises receiving, via a user interface (312), a natural language query related to an engineering diagram from a user. The method further comprises processing the received natural language query using a language model (314) to interpret the query and generate a corresponding structured query. The method further comprises querying a knowledge graph (304) with the structured query. The knowledge graph includes nodes representing engineering diagram elements and edges representing connections between the engineering diagram elements. The method further comprises retrieving query results from the knowledge graph including relevant engineering diagram elements and connections. The method further comprises conducting one or more of predictive analysis and sequence prediction on the query results to recommend engineering diagram elements and their connections. The method further comprises displaying, via the user interface, the recommended engineering diagram elements and their connections.