Resin Molding Prediction Using Probability Distributions
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Solution Overview
Problem
Existing resin molding technologies face challenges in accurately predicting and adjusting molding conditions due to fluctuations in prediction accuracy across varying ranges of molding conditions, leading to potential defects in resin molded products.
Innovation Solution
An apparatus and method that generate and display probability distributions of prediction values for analysis target characteristics based on molding factors, allowing for real-time adjustments and recommendations on optimal molding conditions using a prediction unit, learning unit, and display processing, which includes calculating mean values, standard deviations, and probabilities to determine the best combination of molding factors for achieving target values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional prediction methods are used to predict evaluation items based on molding conditions, then the operator receives support for adjusting molding conditions, but the prediction accuracy fluctuates depending on the range of molding conditions, leading to deteriorated accuracy in adjusting molding conditions
Solution Approach 1:
The patent applies dynamics by making the prediction model adaptive to different molding condition ranges. The system dynamically selects or adjusts prediction models based on the input molding conditions, ensuring high prediction accuracy across varying ranges rather than using a static model that degrades outside its training range.
Solution Approach 2:
The patent changes the parameter of prediction accuracy by implementing multiple prediction models with different characteristics. Each model is optimized for specific molding condition ranges, and the system selects the appropriate model based on the current parameters, thereby maintaining high accuracy across diverse conditions.
2Reliability
If multiple prediction models are used to improve prediction accuracy across different molding condition ranges, then the reliability of molding condition adjustment improves, but the device complexity increases
Solution Approach 1:
The patent segments the molding condition space into multiple ranges, with each segment handled by a specialized prediction model. This segmentation allows each model to focus on a specific range, improving reliability within that range while managing overall complexity through modular organization.
Solution Approach 2:
The patent introduces an intermediary component that selects which prediction model to use based on the current molding conditions. This mediator manages the complexity of having multiple models by providing a unified interface and automated selection logic, preventing the operator from being overwhelmed by model management.
Data Source
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AI summary
Provided is an apparatus configured to support resin molding, including: a prediction unit configured to generate a probability distribution of prediction values of analysis target characteristics of a resin molded body, that correspond to values of a plurality of molding factors of the resin molding; and a display processing unit configured to execute display processing for causing a display apparatus to display the probability distribution of the prediction values of the analysis target characteristics. The prediction unit is configured to calculate a change of the distribution of the prediction values of the analysis target characteristics when a value of at least one of the plurality of molding factors of the resin molding is changed within a predetermined range, and the display unit is configured to display the change of the probability distribution of the prediction values of the analysis target characteristics.