creative tool
Process Functional Modeling (PFM) is an analytical tool to learn the process through modeling of different operations, solving problems, and defining ways to the improvement of any fabrication process. PFM is an extension of the System Functional Modeling (SFM) and it allows us to analyze the whole process vs one particular operation in the process.
Among many cases when Process Functional Modeling is useful for us as problem solvers and innovators, we want to highlight just a few:
Implementing PFM can lead to significant improvements in operational efficiency. By breaking down each operation within a process, organizations can pinpoint specific areas that require enhancement. This detailed understanding helps in reducing bottlenecks, improving throughput, and ultimately increasing overall productivity. Additionally, PFM facilitates better communication among team members as it establishes a clear and common understanding of the process, ensuring everyone is aligned with the goals and objectives.
As technology continues to evolve, the integration of advanced tools such as artificial intelligence and machine learning with PFM is becoming more prevalent. These technologies can enhance the analytical capabilities of PFM, allowing for real-time monitoring and more accurate predictions of process performance. Additionally, the increasing adoption of digital twins—a virtual replica of physical processes—enables organizations to simulate and test process changes in a risk-free environment before implementing them in the real world. These trends are set to further revolutionize the way businesses optimize their processes.
Wet cleaning is widely used in microchip manufacturing. Single wafer equipment is working as follows. A wafer rotates, and chemistry is poured from a movable nozzle. Water rinsing is performed at the end of the process. Loading of a new batch of the chemistry resulted in excursion - a strongly increased amount of defects was observed on the wafer after the processing. The project is dedicated to the failure analysis and creation of innovative solutions.
Flash heating of a wafer is widely used in microchip manufacturing. The purpose of the process is to prevent the diffusion of ions and atoms. During the flash process, a wafer breakage occurs. The project's purpose is to learn and understand the mechanism of the wafer breakage and propose the solutions to prevent the wafer breakage
The process is related to microelectronics - microchip manufacturing. The purpose of the process is to create a SiO2 layer on the surface of a Si wafer. Equipment: Vertical furnace to heat the wafers in the Q2 atmosphere and perform oxidation on the wafer surface. Process: The oxidation occurs on the front side and on the back side of the wafer Requirements: Create a SiO2 thin layer with a certain thickness and low sigma - low standard deviation of the thickness between the wafers and within the wafer Failure: Wafers from the lower zone have higher thickness and significantly higher within wafer sigma (standard deviation of the thickness within the wafer)
This project investigates radial non-uniformity of CDO low-k dielectric deposited by PECVD and its possible impact on wafer performance. Final test data indicate that faster dies are mainly located closer to the wafer center, while slower dies are more often found near the wafer periphery. The corresponding RC-delay trend also increases toward the wafer edge. The focus of the project is the capacitance component of RC-delay. CDO is expected to provide a low dielectric constant between BEOL metal lines, but the deposited film may not have uniform properties across the wafer. Near the wafer edge, the process can be influenced by different gas flow, plasma behavior, residence time, temperature, and pumping conditions. This may lead to stronger oxidation and deeper precursor decomposition near the periphery, forming CDO that is more oxygen-rich, less carbon-rich, denser, and closer in behavior to SiO₂. As a result, the dielectric constant k may increase toward the wafer edge, causing higher interline capacitance, higher RC-delay, and lower die speed. The project uses Functional Modeling to understand how PECVD chamber components and process conditions affect CDO film properties. The goal is to identify the main functional and problematic interactions and propose directions for compensation, such as radial gas-flow tuning, multi-zone showerhead design, edge compensation flow, and local plasma or temperature control.
This project investigates the nonuniform erosion of an expensive Ta sputtering target during Ta/TaN PVD. A deep racetrack groove forces target replacement while a significant amount of tantalum remains unused. Using PRIZ problem-solving tools, the project explores the system’s functions, identifies the root causes of localized erosion, and develops ways to improve target utilization without reducing deposition rate or production throughput.
This project applies Functional Modeling to analyze the single-wafer wet etch process in semiconductor manufacturing. The model shows that wet etch defects are not caused only by chemistry, but also by interactions between the wafer, liquid flow, air, rotation, rinsing, drying, drain, and chamber environment. Key challenges include incomplete wetting, trapped air or bubbles, residue and particle redeposition, evaporation-driven watermarks, and contamination during rinse or drying. The project identifies improvement directions such as better wafer pre-wetting, controlled airflow, reduced evaporation, optimized rinse and drying conditions, and alternative chamber concepts such as face-down processing in a shallow liquid bath.
This project investigates particle-defect formation during SiO₂ dry etch. Functional modeling revealed that defects can be generated by two coupled mechanisms: chemical formation of SiO₂/SiOFₓ particles from SiF₄ interaction with moisture, and mechanical generation of particles by excessive ion bombardment and sputtering. The proposed improvement direction is to balance chemical etching and ion-assisted etching by properly adjusting the source and bias generators, reducing moisture, improving by-product evacuation, minimizing sputtering, and using pulsed or multi-step process recipes. The goal is to reduce particles and micromasking while maintaining etch rate, profile control, and process stability.
This project investigates how to increase the copper removal rate during Chemical Mechanical Planarization (CMP). Functional modeling revealed that increasing H₂O₂ alone is ineffective beyond an optimum level because rapid oxidation creates a thick, passivating Cu₂O/CuO layer that must be mechanically removed. The winning direction is to balance faster oxidation with stronger mechanical removal by optimizing pad speed, abrasive concentration, pressure, conditioning, and slurry transport.
