Paddle Vibration Prediction in Substrate Plating Using Machine Learning
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Solution Overview
Problem
In substrate plating devices, it is challenging to accurately predict paddle vibration characteristics due to noise interference from operational motions, making it difficult to detect abnormalities in mechanical components like paddles.
Innovation Solution
An information processing device and method that acquire and analyze plating process information, including target paddle motion, plating solution motion, and carrier machine motion, to generate agitating-motion paddle vibration information using a learning model, thereby isolating vibration characteristics specific to the paddle's agitating motion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a sensor detecting vibration is attached to the paddle to monitor abnormality, then abnormality detection capability is improved, but measurement precision deteriorates due to noise interference from operational motions
Solution Approach 1:
The patent extracts the paddle's agitating motion characteristics from the complex operational motions by using a learning model to identify and isolate only the vibration components caused by paddle agitation, separating them from noise caused by carrier machine and plating solution motion
Solution Approach 2:
The patent introduces a learning model as an intermediary between the sensor and the abnormality detection system. This learning model processes the raw sensor data and extracts meaningful vibration patterns, acting as a mediator that filters out operational noise while preserving abnormality indicators
2Productivity
If multiple operational motions are performed simultaneously, then productivity is improved, but difficulty of detecting and measuring worsens due to superposable noise
Solution Approach 1:
The patent implements feedback by using the learning model to continuously analyze sensor data and identify patterns that indicate paddle abnormalities. The system learns from operational data and provides feedback signals that enable accurate abnormality detection even during simultaneous operational motions
Solution Approach 2:
The learning model serves as an intermediary that processes complex vibration data from multiple simultaneous operations, separating signal from noise and enabling measurement precision to be maintained despite high productivity operations
Data Source
AI summary
An information processing device includes: an information acquiring part configured to acquire plating process information including operational motion information including target paddle motion information indicating an agitating motion of a target paddle corresponding to a paddle to be processed, plating solution motion information indicating a motion of supplying a plating solution to a plating tank, and carrier machine motion information indicating a motion of carrying a substrate and operational-motion paddle vibration information indicating vibration characteristics of the target paddle when an operational motion is performed, the motions being operational motions performed by a substrate plating device; and an information generating part configured to generate agitating-motion paddle vibration information in response to the plating process information by inputting the plating process information acquired by the information acquiring part to a learning model which has learned a correlation between the plating process information and the agitating-motion paddle vibration information using machine learning.