Ting Cheng, Process Engineer, Applied Materials
Cui Yue, Process Engineer, Applied Materials
In an AMAT Six Sigma Black Belt project regarding to PVD sputtering process, the project goals were to optimize several film properties. A Pugh Matrix was used to select the most feasible hardware design. PVD sputtering process parameters were chosen (Xs) based on the physics of the PVD sputtering process.
To improve the design structure, definitive screening design and augment design were used to avoid confounding at Resolution II and III. RSM model and least square Fit were used to construct the predictive modeling of these film properties. In addition to main effects, several interaction effects were found to be significant in the reduced RSM model. Each interaction effect uncovered potential insights from two competing PVD sputtering physics models.
To further optimize the multiple-stream sputtering process, group orthogonal supersaturated design DOE was utilized to optimize each sputtering process block. Film properties (Ys) compete with each other when searching the optimal design. Three JMP techniques were used to find the optimal Robust Design:
- Set up simulation-based DSD to optimize the desirability functions.
- Conduct Profiler Robust Optimization to find the optimal design.
- Run a Monte Carlo simulation to estimate non-conforming defect %.
By using these JMP 16 modeling platforms and techniques, this Black Belt project was very successful, not only in improving the film properties, but also in furthering the understanding of how physics interact in the process. This multifaceted JMP DOE, modeling and simulation-based approach became the benchmark for several new JMP projects undertaking a similar approach.
