Process Graphic Component Prediction for Faster Automation Drawing
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Solution Overview
Problem
Manually drawing process graphics for industrial automation systems is a slow process due to the high number of components of varying complexity, and existing systems with predefined components struggle with distinguishing and retrieving the correct components for insertion.
Innovation Solution
A computer-implemented method using prediction algorithms, such as machine learning and deep learning neural networks, to predict and suggest candidate components based on user input, reducing the need for manual drawing and ensuring compatibility with existing components.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manually drawing components is used to create process graphics, then customization and precision are improved, but productivity and time consumption deteriorate
Solution Approach 1:
The system pre-defines a library of standardized components with complete specifications and properties before the design process begins. These pre-prepared components can be quickly inserted into process graphics without manual drawing, significantly improving productivity while maintaining precision through standardized definitions.
Solution Approach 2:
Instead of manually drawing each component from scratch, the system creates digital copies of standardized component templates. These copies can be instantiated multiple times with consistent precision, eliminating repetitive manual drawing work while maintaining exact component specifications.
2Adaptability or versatility
If a large number of predefined components are provided for selection, then component variety and adaptability are improved, but ease of operation and component retrieval deteriorate
Solution Approach 1:
The system provides intelligent feedback by analyzing the drawing input in real-time and suggesting relevant components from the library. The suggestion mechanism filters and ranks components based on how well they match the user's intended design, making it easy to retrieve appropriate components even from a large library.
Solution Approach 2:
The suggestion mechanism acts as an intermediary between the user's drawing input and the component library. It translates partial drawings into component recommendations, bridging the gap between user intent and the large component database, thereby simplifying component selection.
3Reliability
If manual component selection from a database is required, then component accuracy and correctness are improved, but time consumption and productivity deteriorate
Solution Approach 1:
The system performs preliminary analysis of the drawing input to predict the intended component before the user needs to select it. This advance preparation presents the correct component options immediately, ensuring selection correctness while eliminating time-consuming manual search and selection processes.
Solution Approach 2:
The system serves itself by automatically analyzing drawings and generating component suggestions without requiring manual database searching. The intelligent suggestion mechanism autonomously identifies appropriate components based on drawing characteristics, reducing both time consumption and ensuring correctness through algorithmic analysis.
Data Source
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AI summary
The present invention generally relates to a computer-implemented method to insert components (116, 118, 120) into a process graphic (120) of an industrial automation system, the method comprising: receiving (S102) a data signal indicating a drawing input (112) in a working area (114) of a graphical platform shown on a computer display; identifying (S104) the working area (114) of the drawing input; identifying (S106) at least one characteristic of the drawing input, predicting (S108) at least one candidate component from a list of available components (116, 118, 120) stored in a data storage (108) that best matches the at least one characteristic of the drawing input, and providing (S110) a list of the at least one candidate component on the computer display.