Substrate Measurement Feedback for Adaptive Process Recipes
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Solution Overview
Problem
Manufacturing systems face challenges in identifying and adapting to unexpected changes in conditions during substrate processing, leading to potential defects in finished products due to the difficulty in modifying process recipes effectively.
Innovation Solution
A substrate measurement subsystem that integrates with the manufacturing system to obtain spectral and positional data of substrates, allowing a system controller to determine necessary modifications to the process recipe based on data correlations and mappings, thereby preventing errors and increasing throughput.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the substrate is processed according to the pre-determined process recipe as conditions change, then the processing follows a stable and defined procedure, but errors occur and finished substrates become defective
Solution Approach 1:
The system implements feedback by measuring substrate properties at multiple stages (before, during, and after processing) and using this information to dynamically adjust process parameters. The controller receives measurement data from sensors and modifies subsequent processing steps based on actual substrate conditions, creating a closed-loop control system that adapts to changing manufacturing conditions.
Solution Approach 2:
The process recipe transitions from a static, pre-determined sequence to a dynamic, adaptive procedure. The system continuously monitors substrate properties and adjusts processing parameters in real-time based on measured deviations, allowing the process to evolve and respond to changing conditions rather than following a fixed predetermined path.
2Reliability
If an operation of the process recipe is modified in view of changed conditions, then errors can be prevented during processing, but it is difficult for the operator to identify which operation should be modified
Solution Approach 1:
The system automatically generates feedback reports that identify specific process operations requiring modification based on measured substrate deviations. The controller analyzes measurement data and provides targeted recommendations to operators about which process steps should be adjusted, eliminating the difficulty of identifying problematic operations.
Solution Approach 2:
The system performs self-diagnosis and self-adjustment by automatically analyzing measurement data and determining which process operations need modification. The controller autonomously identifies deviations and suggests or implements process changes without requiring extensive operator analysis, allowing the system to serve itself in identifying and correcting process issues.
3Measurement precision
If multiple measurements are taken at different positions and orientations, then comprehensive substrate data is obtained, but the complexity of determining which portions to measure increases
Solution Approach 1:
The measurement process is segmented into discrete, manageable steps with clearly defined measurement positions and orientations. The system divides the substrate surface into specific regions of interest and sequences measurement operations systematically, breaking down the complex task of comprehensive measurement into organized segments that are easier to control and execute.
Solution Approach 2:
The system performs preliminary actions by pre-determining measurement positions, orientations, and sequences based on the process recipe and substrate type. Before actual measurements begin, the controller plans the measurement path and selects relevant portions to measure, organizing the measurement task in advance to reduce complexity during execution.
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
The subsystem enhances manufacturing efficiency by reducing defects and increasing overall throughput by dynamically adjusting process recipes in response to changes in manufacturing conditions.
Implementation Method 1
obtain spectral and positional data of substrates
Data Source
AI summary
An identification feature of a substrate in a substrate measurement subsystem is identified. The identification feature is located at a predefined location relative to a reference location of the substrate. A position of the substrate within the substrate measurement subsystem is determined based on the identified identification feature. Based on the determined position of the substrate, one or more sensing components of the substrate measurement subsystem is caused to capture spectral data representing features of at least one of the reference location of the substrate or another location of the substrate. A determination is made of whether to update a process recipe associated with the substrate based on the captured spectral data.