3D Plant Layout Generation From 2D Schemas Using Object Mapping
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Solution Overview
Problem
Generating a 3D model of a plant layout from a 2D schema is cumbersome and time-consuming, especially when dealing with diverse CAD formats, requiring manual intervention and compatibility issues between different CAD tools.
Innovation Solution
A machine learning algorithm is trained to detect 2D plant objects and associate them with corresponding 3D models, automatically generating a 3D plant layout by recognizing and positioning plant objects based on their identifiers and location data, using a plant catalogue and additional manufacturing process semantics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual methods are used to generate 3D plant layout models from 2D schemas, then layout planners can create accurate 3D models, but the process becomes cumbersome and time-consuming
Solution Approach 1:
The system enables self-service by allowing the 2D schema to automatically generate the 3D model without requiring manual intervention. The plant objects in the 2D schema contain embedded metadata that automatically triggers the generation of corresponding 3D plant objects, eliminating the need for layout planners to manually create 3D models from 2D schemas.
Solution Approach 2:
The solution applies preliminary action by pre-enriching 2D plant objects with metadata during the schema creation phase. This metadata includes information about the corresponding 3D plant objects, so that when the schema is loaded, the 3D model generation can proceed automatically without requiring manual data preparation or object selection.
2Adaptability or versatility
If layout planners manually browse plant component libraries to find suitable 3D plant objects, then they can select appropriate objects, but the process becomes time-consuming and labor-intensive
Solution Approach 1:
The system enables self-service by allowing the 2D schema to automatically generate the 3D plant layout model without requiring manual intervention. The plant objects in the 2D schema contain embedded metadata that automatically triggers the generation of corresponding 3D plant objects, eliminating the need for layout planners to manually create 3D models from 2D schemas.
Solution Approach 2:
The system uses an intermediary mechanism by introducing a mapping layer between 2D plant objects and 3D plant objects. The metadata embedded in 2D plant objects serves as an intermediary that automatically identifies and retrieves the corresponding 3D plant objects from the plant component library, eliminating the need for manual browsing and selection.
3Reliability
If all data preparation is done using the same CAD tool, then compatibility issues are avoided, but this restricts flexibility when receiving schemas from various CAD tools
Solution Approach 1:
The system applies universality by designing the plant schema format to be tool-agnostic and format-independent. The schema uses a standardized structure with metadata that can represent plant objects from any CAD tool, allowing the system to universally handle schemas from various sources without requiring tool-specific processing or conversion.
Solution Approach 2:
The system uses an intermediary mechanism by introducing a mapping layer between 2D plant objects and 3D plant objects. The metadata embedded in 2D plant objects serves as an intermediary that automatically identifies and retrieves the corresponding 3D plant objects from the plant component library, eliminating the need for manual browsing and selection.
4Productivity
If automated methods are used to generate 3D models from 2D schemas, then time consumption is reduced, but manual intervention is still required for data preparation and object selection
Solution Approach 1:
The system enables self-service by allowing the 2D schema to automatically generate the 3D model without requiring manual intervention. The plant objects in the 2D schema contain embedded metadata that automatically triggers the generation of corresponding 3D plant objects, eliminating the need for layout planners to manually create 3D models from 2D schemas.
Solution Approach 2:
The solution applies preliminary action by pre-enriching 2D plant objects with metadata during the schema creation phase. This metadata includes information about the corresponding 3D plant objects, so that when the schema is loaded, the 3D model generation can proceed automatically without requiring manual data preparation or object selection.
Data Source
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AI summary
Systems and a method for generating a 3D-model of a plant layout departing from a 2D- schema of the plant-layout. Access to a plant catalogue of identifiers of 3D plant objects is provided, wherein at least one of the 3D plant object identifiers is associated to an identifier of a corresponding 2D plant object. Data on a given 2D schema of a plant-layout are received as input data; A function trained by a machine learning algorithm is applied to the input data for detecting a set of 2D plant objects, wherein a set of identifier and location data on the detected 2D plant object set is provide as output data. A set of 3D plant objects is selected from the plant catalogue whose identifiers are associated to the set of 2D plant objects identifiers of the output data. A 3D model of the plant-layout is generated by arranging the selected set of 3D plant objects in accordance with the corresponding location data, of the output data.