Controlling process disruptions is essential as today’s factories invest more in automated information handling, equipment integration and advanced process control (APC) tools such as Run‐to‐Run (R2R) controllers that monitor and control process variances. The SmartFactory® Run-to-Run solution is an out-of-box (OOB) APC solution that improves process capability (Cpk) and optimizes tool recipe parameters. It is deployed with EngineeredWorks®, which is Applied’s pre-built automation logic that executes on a proven Applied platform, increasing speed-to-value for customers and providing quicker deployment times.
Improve Your Process Capabilities
SmartFactory Run-to-Run offers a patented model predictive control platform providing a multivariate, constrained, optimization-based process controller with proven deployment success. Historical data from SmartFactory Run-to-Run implementations at customer sites have shown over 30% improvement in Cpk on several tool types. Implementations have also resulted in a 75% reduction in rework rate in the photolithography module.
Lower Your Cost Of Ownership
SmartFactory out-of-box (OOB) Run-to-Run solutions currently include Furnace, Photolithography, Etch, CMP and CVD modules. The solution reduces model management activities through a unified modeling structure approach and advanced patented technology. Manufacturers benefit from SmartFactory’s R2R solution by improving process capability, reducing send‐ahead and pilot wafers, and improving overall equipment effectiveness.
Improve Process Consistency And Product Quality
With Run-to-Run, manufacturers can make automatic adjustments to processes to maintain a required target value for specific properties, such as wafer thickness and critical dimension. Manufacturers can also use metrology data from each process step to adjust process recipes on a run‐to‐run basis and define customized strategies, such as rework, to be performed in a highly automated fashion. The solution is designed to support high-mix and low-volume manufacturing operations, which have always posed a challenge in the industry.
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Article
Run-to-run Control Modeling with Recurrent Neural Networks, Ivan Chen, Shijing Wang, and Ben Williams, APC Conference XXXI, San Antonio, Texas, October 2019.
Minimizing Pilot Runs With Observable R2R Control For High-Mix Manufacturing, Jianping Zou, Adrianto Kumara, and Kwee Thiam Lim. December 2014.
Article References
Strulovich, Anna; Eitan, Nadav; Berman, Ohad. “Enhancement of R2R Controller in Photolithography Area”. Presented at the 12th European Advanced Process Control and Manufacturing Conference, Grenoble, France, April 16‐18, 2012.
TowerJazz to Present at 12th European APCM Conference April 16‐18, 2012. April 10, 2012.
Micron Technology Optimizes Process Control With Applied Materials' E3 Equipment Control System. August 30, 2010.
Shijing Wang, et al. “A R2R Control and Preventive Maintenance Strategy for Batch LPCVD Furnace”, AEC/APC Conference XXI, Ann Arbor MI, September 28‐30, 2009
Darren Ross, et al. “Migration from manual SPC to automated R2R control in existing fabs: Case study of diffusion control at IBM”, AEC/APC Conference XXI, Ann Arbor MI, September 28‐30, 2009.