Semiconductor Wafer Usability Assessment via Multi-Parameter Process Window Analysis
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Solution Overview
Problem
Aggressive semiconductor wafer manufacturing processes lead to non-uniform stress and positional errors between layers, causing overlay and critical dimension issues, which are difficult to accurately assess within traditional process windows, resulting in defective wafers.
Innovation Solution
A method and apparatus that gather a wide range of processing data, apply process models to derive results, and compare them to a process window to adapt parameters and improve yield, considering multiple dimensions of data such as overlay errors, critical dimensions, and other geometry data, allowing for more comprehensive analysis and adjustment of manufacturing processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If aggressive manufacturing processes are used to shrink ground rules and improve productivity, then productivity increases, but manufacturing precision deteriorates due to non-uniform stress and overlay errors
Solution Approach 1:
The system performs preliminary assessment of overlay and critical dimension data before final processing decisions. By evaluating multiple measurement parameters in advance and comparing them against process windows, the system identifies wafers that can be processed despite individual parameter deviations, enabling aggressive manufacturing schedules while maintaining quality control through pre-screening
Solution Approach 2:
The system changes the assessment parameters from traditional single-parameter overlay checks to a multi-parameter evaluation including overlay measurements, critical dimension measurements, and process window comparisons. This comprehensive parameter set allows the system to tolerate deviations in individual parameters while maintaining overall manufacturing precision through holistic assessment
2Device complexity
If traditional overlay and critical dimension measurements are used individually, then measurement simplicity is maintained, but measurement precision deteriorates due to inability to capture comprehensive process quality
Solution Approach 1:
The system merges multiple measurement types (overlay measurements, critical dimension measurements) and process data into a unified assessment framework. By combining these measurements and comparing them against a process window, the system achieves comprehensive process quality assessment that is more accurate than individual measurements while maintaining manageable system complexity through integrated analysis
Solution Approach 2:
The system creates a universal process window that can evaluate multiple measurement parameters simultaneously. This multi-functional assessment tool can handle overlay errors, critical dimension variations, and other process parameters within a single framework, improving measurement precision without requiring separate complex evaluation systems for each parameter type
3Manufacturing precision
If comprehensive multi-dimensional processing data is collected and analyzed, then manufacturing precision improves through better process control, but device complexity increases due to multiple measurement parameters and process models
Solution Approach 1:
The system implements self-service through automated collection, analysis, and interpretation of multi-dimensional processing data. By automatically gathering overlay and critical dimension measurements, applying process models, comparing results against process windows, and generating assessment outcomes without manual intervention, the system handles complex data analysis internally, improving manufacturing precision while keeping the user interface simple
4Ease of operation
If traditional process window boundaries are applied rigidly, then ease of operation is maintained through clear pass/fail criteria, but reliability deteriorates due to inability to account for compensating errors and fuzzy boundaries
Solution Approach 1:
The system changes the decision-making parameters from rigid single-parameter thresholds to a multi-parameter evaluation against a process window. By considering multiple measurements (overlay, critical dimension) simultaneously and evaluating their combined effect within defined boundaries, the system achieves more reliable wafer acceptance decisions while maintaining operational simplicity through automated multi-dimensional assessment
Data Source
AI summary
An apparatus and a method for analysis of processing of a semiconductor wafer is disclosed which comprises gathering a plurality of items of processing data, applying at least one process model to the at least some of the plurality of items of processing data to derive at least one set of process results, comparing at least some of the derived sets of process results or at least some of the plurality of items of processing data with a process window, and outputting a set of comparison results based on the comparison of the derived sets of process results or the plurality of items of processing data with the process window.