Process Visualization Interface for Semiconductor DOE Analysis
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Solution Overview
Problem
The analysis of large datasets from semiconductor wafer manufacturing processes is time-consuming and difficult due to the complexity of processing variables and their effects on wafer properties, leading to a combinatorial explosion of data that overwhelms resources and complicates the optimization of process development.
Innovation Solution
A visualization tool is developed that generates interactive visualizations of on-wafer results, allowing users to adjust multiple variables through graphical user interface control elements, reducing data analysis time and resources by presenting data in an immersive and organized manner, similar to a virtual cockpit experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If design of experiments (DOEs) are conducted to test many different processing variables and their effects on wafer properties, then process development completeness is improved, but data analysis time and difficulty increase significantly
Solution Approach 1:
The patent segments the massive DOE dataset into manageable visual components by displaying data across multiple virtual screens arranged in a grid layout. Each screen shows a portion of the wafer map or parameter visualization, allowing analysts to systematically examine different segments of the data without being overwhelmed by the complete dataset at once. This segmentation approach enables efficient navigation and analysis of process variable effects across the entire experiment scope.
Solution Approach 2:
The patent transitions from traditional two-dimensional screen displays to a three-dimensional virtual cockpit environment where multiple screens are arranged in spatial configurations around the user. This dimensional expansion allows simultaneous visualization of multiple parameters and wafer maps from different angles and perspectives, enabling comprehensive process development analysis without increasing analysis time linearly with data volume.
2Manufacturing precision
If multiple process variables are tested to ensure thorough process development, then manufacturing precision is improved, but device complexity increases due to combinatorial explosion of data
Solution Approach 1:
The patent implements a universal virtual cockpit interface that can simultaneously display and analyze multiple process variables, wafer maps, and parameter combinations in a single integrated environment. The system provides multi-functional capabilities including wafer map visualization, parameter trend analysis, and comparative evaluation across different DOE conditions, all within one cohesive interface. This eliminates the need for separate analysis tools for each variable or parameter combination, reducing overall system complexity despite the comprehensive data being analyzed.
Solution Approach 2:
The patent merges multiple data visualization functions into a unified virtual cockpit display where wafer maps, parameter tables, and process variable controls are integrated in a single immersive environment. By combining these previously separate analytical functions into one cohesive interface, the system reduces the complexity of navigating between multiple tools and windows, allowing analysts to evaluate the interactions of multiple process variables simultaneously without being overwhelmed by data structure complexity.
3Loss of energy
If traditional data analysis methods are used for large DOE datasets, then resource usage is maintained at current levels, but productivity decreases due to time-consuming analysis
Solution Approach 1:
The patent creates virtual copies of wafer maps and parameter visualizations across multiple simulated screens within the virtual cockpit environment. Instead of requiring multiple physical displays or duplicating data across separate analysis systems, the virtual cockpit generates digital replicas of the same data from different perspectives and scales. This copying approach enables simultaneous examination of multiple aspects of the DOE data without proportionally increasing computational resource usage, maintaining efficient resource utilization while dramatically improving process development productivity through immersive parallel visualization.
Data Source
AI summary
A process development visualization tool generates a first visualization of a parameter associated with a manufacturing process, and provides a GUI control element associated with a process variable of the manufacturing process, wherein the GUI control element has a first setting associated with a first value for the process variable. The process development tool receives a user input to adjust the GUI control element from the first setting to a second setting, determines a second value for the process variable based on the second setting, and determines a second set of values for the parameter that are associated with the second value for the process variable. The process development tool then generates a second visualization of the parameter, wherein the second visualization represents the second set of values for the parameter that are associated with the second value for the process variable.