Rotation Shaft Defect Detection via Motor Current Analysis
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Solution Overview
Problem
Conventional substrate processing devices face challenges in efficiently determining whether a rotation shaft is defective, as existing methods require time-consuming vibration measurements or are hindered by numerous variables when analyzing current patterns.
Innovation Solution
A substrate processing device and defect detection method that utilize an abnormality diagnosis model to determine rotation shaft defects by analyzing current values applied to the driver, correlating current values with rotation shaft states, and recognizing abnormal patterns to identify defects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If vibration measurement is used to inspect the rotation shaft, then the inspection accuracy is improved, but the inspection time increases significantly
Solution Approach 1:
The patent replaces the mechanical vibration measurement system with an electrical current analysis system. Instead of using vibration sensors to physically measure the rotation shaft's vibration, the system analyzes the current consumption pattern of the motor driving the rotation shaft. An abnormality diagnosis model processes the current values to detect defects, substituting mechanical measurement with electrical signal analysis to achieve both accuracy and speed.
2Loss of time
If current pattern analysis is used to predict rotation shaft defects, then the inspection time is reduced, but the prediction accuracy decreases due to multiple variables
Solution Approach 1:
The patent introduces an abnormality diagnosis model as an intermediary between the raw current values and the defect prediction. This model processes the complex current patterns and filters out the noise from multiple variables, transforming the raw electrical signals into reliable defect predictions. The model acts as a mediator that converts difficult-to-interpret current data into accurate diagnostic information.
Solution Approach 2:
The system replaces complex multi-variable mechanical analysis with a focused electrical current analysis. Instead of monitoring multiple physical parameters simultaneously, the patent concentrates on analyzing the current consumption pattern of the motor, which serves as a proxy for the rotation shaft's mechanical state. This substitution simplifies the measurement system while maintaining diagnostic capability.
3Productivity
If the rotation shaft rotates at high speed, then the substrate processing efficiency is improved, but the rotation shaft wears out and generates dust
Solution Approach 1:
The patent implements a feedback mechanism where the abnormality diagnosis model continuously monitors the current values during high-speed rotation and provides real-time information about the rotation shaft's condition. When wear or abnormalities are detected through current pattern analysis, the system can alert operators or adjust operating parameters, creating a closed-loop control system that maintains both high-speed operation and component reliability.
Solution Approach 2:
The system performs preliminary detection of rotation shaft wear by analyzing current patterns before actual damage occurs. By monitoring the electrical characteristics during normal high-speed operation, the abnormality diagnosis model can predict potential failures and enable preventive maintenance, allowing the rotation shaft to operate at high speeds for longer periods without actual wear damage.
Data Source
AI summary
Disclosed is a device for processing a substrate, the device including: a support unit including a spin chuck supporting a substrate, a rotation shaft supporting the spin chuck, and a driver providing rotational force to the rotation shaft; and a determination unit for determining whether the rotation shaft is defective, in which the determination unit determines whether the rotation shaft is defective based on a current value applied to the driver while the rotation shaft is rotating.