Distance Sensor Assessment of Substrate Support Flatness and Alignment
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Solution Overview
Problem
Substrate processing chambers face issues due to non-flat or misaligned substrate supports, which can lead to inconsistent processing, particle generation, and component damage, necessitating a method to determine substrate support properties before use.
Innovation Solution
A system using distance sensors to measure substrate support properties, including surface roughness and alignment, generating metric values for display or corrective actions based on these measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If substrate supports are used without prior assessment, then productivity is maintained, but processing consistency deteriorates due to non-flat or misaligned supports
Solution Approach 1:
The system performs preliminary assessment of substrate support properties (flatness, alignment, surface finish) using distance sensors before the substrate support is installed in the processing chamber. This advance evaluation allows identification of defective supports that could cause processing inconsistencies, enabling preventive maintenance or replacement before they impact production, thus maintaining both reliability and productivity
2Measurement precision
If substrate supports are assessed using traditional methods, then surface properties can be evaluated, but alignment properties cannot be determined
Solution Approach 1:
The distance sensor system is designed to perform multiple assessment functions using a single device. The same distance sensors that measure surface flatness and roughness are also used to determine alignment properties by measuring distances at multiple locations and calculating positional deviations. This multi-functional approach enables comprehensive assessment (both surface and alignment properties) without requiring separate specialized equipment, thus improving measurement capability while controlling system complexity
3Object-affected harmful factors
If substrate supports with poor surface finish are used, then productivity is maintained, but particle generation increases causing harmful effects
Solution Approach 1:
The system performs preliminary assessment of substrate support surface finish quality using distance sensors before installation in the processing chamber. By evaluating surface roughness and identifying defective supports in advance, the system prevents installation of supports that would generate particles during processing. This proactive approach eliminates harmful particle generation while avoiding production delays, thus protecting both product quality and productivity
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Improves processing consistency by allowing for maintenance or replacement of substrate supports, reducing scrap and enhancing system throughput.
Implementation Method 1
one or more distance sensors disposed above the substrate support and configured to generate a first plurality of distance measurements of first distances between the substrate support and the distance sensor
Data Source
AI summary
One or more distance sensors disposed above a substrate support generate distance measurements between the substrate support and the one or more distance sensors. A processing device determines at least one of (i.) one or more first metric values indicative of one or more surface properties of the substrate support based on the distance measurements, or (ii.) one or more second metric values indicative of one or more alignment properties associated with the substrate support based on the distance measurements. The processing device causes one or more of (a.) at least one of the one or more first metric values or at least one of the one or more second metric values to be output for display on a GUI, or (b.) performance of a corrective action associated with the substrate support based on the one or more first metric values or the one or more second metric values.