Wafer Process Simulation Iterative Parameter Optimization
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Solution Overview
Problem
Current methods for simulating semiconductor wafer fabrication are inefficient as they typically input only one process condition at a time, overlooking dependencies among parameters and failing to find optimal combinations, leading to time-consuming processes and suboptimal results.
Innovation Solution
A computerized wafer simulation tool that iteratively adjusts multiple process parameters in small steps, considering interdependencies to reach a target goal, such as optimizing interconnect structures or alignment marks, by simulating various fabrication steps and testing the structure until it meets user-specified criteria.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional trial and error methods are used to find optimal processing conditions, then the process can be completed with simple tools, but the time required and number of iterations are excessive
Solution Approach 1:
The simulation tool implements automated feedback loops where simulation results are continuously compared against target specifications, and process parameters are automatically adjusted based on this feedback. This closed-loop system eliminates manual trial-and-error iterations and rapidly converges to optimal processing conditions.
Solution Approach 2:
The patent replaces manual mechanical adjustment of parameters with computerized automated control systems. The simulation software automatically modifies process parameters based on simulation outcomes, substituting human operators and manual adjustment mechanisms with algorithm-driven automated optimization.
2Productivity
If only one process condition is input to the simulation tool at a time, then the simulation setup is simple, but the process becomes time-consuming and fails to find optimal combinations
Solution Approach 1:
The simulation tool merges multiple process parameter adjustments into a single integrated simulation run. Instead of sequentially testing one parameter at a time, the system simultaneously evaluates combinations of multiple process conditions, identifying optimal parameter sets in fewer iterations.
Solution Approach 2:
The simulation system dynamically adjusts multiple process parameters simultaneously based on real-time simulation feedback. The tool adapts parameter combinations iteratively, allowing flexible exploration of the parameter space to discover optimal conditions that account for interdependencies among process variables.
3Manufacturing precision
If existing simulation approaches are used, then the tool is easy to operate with single parameter input, but dependencies among process parameters are overlooked and optimal combinations are missed
Solution Approach 1:
The system incorporates automated feedback mechanisms that monitor simulation results and automatically adjust multiple process parameters to account for their interdependencies. This feedback-driven approach ensures that parameter relationships are properly considered, improving optimization accuracy without requiring complex manual intervention.
Solution Approach 2:
The simulation tool systematically varies multiple process parameters simultaneously according to defined relationships and constraints. By coordinating parameter changes across different process steps, the system captures interdependencies and identifies optimal parameter combinations that single-parameter approaches would miss.
Data Source
AI summary
A method includes establishing a simulation process for simulating fabrication of a structure on a wafer. The simulation process includes multiple simulation steps for simulating multiple wafer fabrication steps respectively, and further includes a step of testing the structure that produces a result representing quality of the structure. Each of the simulation steps has a respective adjustable process parameter. The method further includes specifying a respective workable range for each process parameter and running the simulation process in iterations using a wafer process simulator until the result becomes optimal. During the running of the simulation process, every two consecutive iterations either adjust two different process parameters within their workable ranges or adjust a same process parameter at opposite directions within its workable range.