Information processing method, computer program, and information processing apparatus

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Solution Overview

Problem

Existing information processing systems struggle to accurately control target apparatuses with the same configuration as reference apparatuses due to individual differences in sensors and processing mechanisms, leading to inconsistent processing results.

Innovation Solution

Utilizing a combination of machine learning models, including a characteristic value estimation model, control input value determination model, sensor value conversion model, and control input value conversion model, to adjust sensor values and control inputs to align the target apparatus with the reference apparatus, ensuring consistent processing outcomes.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Device complexity

If the same configuration apparatuses are used as reference and target, then device complexity is reduced, but manufacturing precision deteriorates due to individual differences in sensors and processing mechanisms

Engineering Contradiction:

Improveapparatus configurationVSAvoidprocessing results consistency

Core Design Contradiction:

Device complexityVSManufacturing precision

Solution Approach 1:

The patent applies parameter changes by using machine learning models to convert sensor values and control input values between reference and target apparatuses. The sensor value conversion model transforms sensor readings from the target apparatus into equivalent reference apparatus values, while the control input value conversion model adjusts control parameters to compensate for individual differences. This allows the system to maintain consistent processing results despite variations in individual apparatus characteristics.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent introduces intermediary conversion models as mediators between the target apparatus and the reference apparatus. The sensor value conversion model acts as an intermediary to translate sensor data from the target apparatus into the reference apparatus's measurement space. Similarly, the control input value conversion model serves as an intermediary to translate control commands from the reference apparatus's control space into the target apparatus's control space, enabling indirect control that compensates for individual differences.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Manufacturing precision

If machine learning conversion models are introduced to correct apparatus differences, then manufacturing precision is improved, but device complexity increases due to multiple conversion models

Engineering Contradiction:

Improveprocessing results consistencyVSAvoidconversion model system

Core Design Contradiction:

Manufacturing precisionVSDevice complexity

Solution Approach 1:

The patent applies the copying principle by creating virtual representations of the reference apparatus's sensor and control characteristics in the target apparatus's space. The sensor value conversion model creates a virtual copy of the reference apparatus's sensor response characteristics, allowing the target apparatus's sensors to be interpreted as if they were the reference apparatus's sensors. The control input value conversion model creates a virtual copy of the reference apparatus's control input characteristics, enabling control commands to be adapted to the target apparatus's specific response characteristics.

Inventive Principle:

Principle #26Copying

3Measurement precision

If sensor values are converted using machine learning, then measurement precision is improved for cross-apparatus comparison, but loss of information increases during the conversion process

Engineering Contradiction:

Improvesensor value comparabilityVSAvoidoriginal sensor data

Core Design Contradiction:

Measurement precisionVSLoss of information

Solution Approach 1:

The patent applies feedback by using the converted sensor values from the target apparatus (through the sensor value conversion model) to adjust and refine control commands via the control input value conversion model. The system continuously monitors the processing results and uses this feedback to iteratively improve the accuracy of the conversion models and control strategies, minimizing information loss while maintaining measurement precision across different apparatuses.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS20250231535A1Information processing method, computer program, and information processing apparatus

Publication Date: 2025.07.17 TOKYO ELECTRON LTD

AI summary

An information processing apparatus acquires a sensor value of a target apparatus, inputs the acquired sensor value of the target apparatus to a sensor value conversion model, acquires the sensor value of the reference apparatus output by the sensor value conversion model, inputs the acquired sensor value of the reference apparatus together with a desired target value to a control input value determination model, acquires the control input value of the reference apparatus output by the control input value determination model, inputs the acquired control input value of the reference apparatus to a control input value conversion model, acquires the control input value of the target apparatus output by the control input value conversion model, and controls the target apparatus, based on the acquired control input value of the target apparatus.