Laser Irradiation Failure Prediction for Movable Parts
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Solution Overview
Problem
Existing laser annealing apparatuses lack a mechanism for predicting failures in their components, particularly movable parts, which can lead to unexpected downtime and inefficiencies.
Innovation Solution
A laser irradiation apparatus equipped with a failure prediction unit that acquires physical quantities from movable parts during operation and uses a learning model to derive a failure time based on these measurements, utilizing sensors for temperature and vibration data to predict component failures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a laser annealing apparatus is used to form polycrystalline silicon thin films, then manufacturing capability is improved, but failure prediction capability deteriorates (no failure prediction mechanism is provided)
Solution Approach 1:
The system performs preliminary actions by acquiring physical quantity data (vibration, temperature, current, voltage) from movable parts before actual failure occurs. The learning model processes this historical data to predict future failure times, enabling maintenance to be scheduled in advance and preventing unexpected downtime.
Solution Approach 2:
The system implements feedback by continuously monitoring physical quantities from sensors on movable parts, comparing actual values against predicted values from the learning model, and using this information to update failure predictions. This closed-loop feedback enables dynamic adjustment of maintenance schedules based on actual component conditions.
2Measurement precision
If physical quantity data is collected and processed using a learning model, then failure prediction accuracy is improved, but device complexity increases
Solution Approach 1:
The learning model serves as an intermediary between raw sensor data and failure prediction results. It processes complex multi-parameter data (vibration, temperature, current, voltage) and transforms it into meaningful failure time predictions, reducing the complexity burden on the control system while maintaining high prediction accuracy.
Solution Approach 2:
The system creates a virtual copy or digital twin of the movable part's operational state through the learning model. This virtual model replicates the physical component's behavior patterns based on historical data, allowing failure prediction without adding physical sensors or complex hardware to the actual device.
Data Source
AI summary
A laser irradiation apparatus is a laser irradiation apparatus including a laser light source, the laser irradiation apparatus including a failure prediction unit configured to perform failure prediction on a movable part used when a substrate is processed by the laser light source, in which the failure prediction unit acquires a physical quantity when the movable part is movable, and derives a failure time of the movable part based on an acquired physical quantity.