Adaptive Search Conditions for Trial Material Manufacturing
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Solution Overview
Problem
Existing data-driven development methods for material manufacturing face inefficiencies due to inappropriate setting of search conditions, leading to low improvement in evaluation values per search cycle and reduced development efficiency.
Innovation Solution
A system and method that includes a trial manufacturing apparatus and an information processing apparatus to execute multiple search cycles, dynamically adjusting search conditions based on data from previous cycles, using Bayesian optimization or other methods to determine optimal manufacturing conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the search condition is set by a user at first and kept fixed, then the system is simple to operate, but the amount of improvement in the evaluation value per search cycle becomes small and search efficiency is low
Solution Approach 1:
The search condition is changed dynamically during the execution of search cycles based on accumulated data. The system automatically adjusts the search condition after a predetermined number of search cycles or when specific conditions are met, transitioning from a static user-defined condition to a dynamic adaptive condition that improves search efficiency while maintaining ease of operation through automated adjustment.
2Productivity
If the search condition is changed dynamically during search cycles, then the search efficiency is improved, but the system complexity increases
Solution Approach 1:
The system uses feedback from accumulated data obtained during search cycles to automatically adjust the search condition. By monitoring the evaluation values and manufacturing conditions from previous cycles, the system determines whether to change the search condition, creating a closed-loop feedback mechanism that improves efficiency without requiring complex manual intervention.
Solution Approach 2:
The system performs self-adjustment of the search condition based on its own accumulated data. The information processing apparatus automatically determines whether to change the search condition using the data from executed search cycles, eliminating the need for external intervention and reducing system complexity while maintaining adaptive optimization.
3Device complexity
If manual manufacture and evaluation of samples is performed, then the system is simple and flexible, but the development efficiency is reduced
Solution Approach 1:
The system merges automated trial manufacturing apparatus with information processing apparatus to create an integrated automated search cycle system. The trial manufacturing apparatus automatically manufactures samples based on determined manufacturing conditions, and the information processing apparatus automatically evaluates them, combining multiple functions into a unified system that improves development efficiency while maintaining manageable complexity through modular integration.
Data Source
AI summary
An information processing apparatus receives input of a search condition and executes a determination process of determining a manufacturing condition for a sample in each of a plurality of search cycles. A trial manufacturing apparatus, in each of the plurality of search cycles, executes a manufacturing process of manufacturing the sample under the manufacturing condition determined in the determination process, and executes an evaluation process of evaluating the sample manufactured in the manufacturing process and outputting an evaluation result. The information processing apparatus, in the determination process in a first search cycle, determines the manufacturing condition in the first search cycle by using the search condition and a data set including data obtained in a second search cycle and a search cycle executed before the second search cycle. The information processing apparatus changes the search condition for a third search cycle and a search cycle after the third search cycle.