Compact Manufacturing Model for Electronic Circuit Design
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Solution Overview
Problem
Current integrated circuit design processes face challenges in accurately modeling manufacturing variations, particularly in early design stages like floor planning and routing, due to the need for balancing speed and accuracy, and the limitations of existing rule-based and physics-based models in handling complex topographical and thickness variations.
Innovation Solution
A compact manufacturing model is implemented that uses statistically sufficient data from physics-based manufacturing processes, calibrated without requiring actual manufacturing process calibration, to provide a sliding scale for balancing speed and accuracy across all design stages, including early stages like floor planning and routing, using a golden manufacturing model and artificial intelligence processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If physics-based manufacturing models are used to accurately model manufacturing variations, then manufacturing precision is improved, but computation time increases significantly
Solution Approach 1:
The patent creates a simplified copy of the complex physics-based manufacturing model that captures essential variations without the computational burden. This compact model uses statistical data and calibrated parameters to replicate key manufacturing effects (such as thickness variations and topographical changes) while enabling fast computation during early design stages like floor planning and routing.
Solution Approach 2:
The patent transforms the physics-based model into a parameterized compact model where manufacturing variations are represented through calibrated statistical parameters rather than full physics simulations. By changing the representation from detailed physical processes to aggregated parameters (mean values, standard deviations, and correlation factors), the model achieves both accuracy and speed.
2Productivity
If rule-based models are used for fast computation, then productivity is improved, but manufacturing precision deteriorates
Solution Approach 1:
The patent enhances rule-based models by introducing statistically calibrated parameters that capture manufacturing variations. Instead of using fixed rules, the model employs parameterized representations (mean thickness values, variation standard deviations, and spatial correlation factors) that can adapt to different manufacturing conditions while maintaining computational efficiency.
Solution Approach 2:
The patent introduces an intermediary layer between simple design inputs and complex manufacturing outcomes. This compact model acts as a mediator that translates design parameters into predicted manufacturing variations using calibrated statistical relationships, providing more accurate predictions than direct rule-based approaches without the complexity of full physics simulations.
3Manufacturing precision
If comprehensive manufacturing process calibration is performed, then manufacturing precision is improved, but device complexity and time consumption increase
Solution Approach 1:
The patent extracts the essential calibration information from complex manufacturing process data and distills it into a compact set of statistical parameters. By separating the calibration step from the simulation step, the model performs comprehensive calibration once using available manufacturing data, then uses the resulting parameter sets for rapid, repeatable simulations without re-processing the full calibration data each time.
Solution Approach 2:
The patent performs comprehensive manufacturing process calibration as a preliminary action during model setup, where statistical parameters are derived from available manufacturing data. Once calibrated, these parameters are stored and reused in subsequent design iterations, eliminating the need to repeat the complex calibration process for each simulation and significantly reducing overall complexity.
4Manufacturing precision
If detailed topographical and thickness variation modeling is implemented, then manufacturing precision is improved, but computation time and model complexity increase
Solution Approach 1:
The patent segments the manufacturing variation modeling into independent spatial and parameter components. Instead of modeling every local topographical detail simultaneously, the model divides the chip into regions and uses statistical parameters to represent variations within each region. This segmentation allows the model to capture essential topographical effects (such as dishing or erosion patterns) while reducing computational complexity through spatial decomposition.
Data Source
AI summary
Disclosed are a method, a system, and a computer program product for implementing compact manufacturing model during various stages of electronic circuit designs. In some embodiments, the method or the system receives or identifies physics based data. In some embodiments, the method or the system receives or identifies the physics based data for the corresponding manufacturing process by using the golden manufacturing process model. In some embodiments, the method or the system uses the physics based data to fine tune, modify, or adjust the golden manufacturing process model. In some embodiments, the method or the system invokes the just-right module. In some embodiments, the method or the system implements the compact manufacturing model and the correct-by-design module and provides guidelines for the various stages of the electronic circuit design.