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> FabGuard Suite
> Guardian Co-Deposition Controller
> Helium Leak Detectors
> RF Sensing Technology with FabGuard
>Stiletto In Situ Particle Detectors
> Transpector Residual Gas Analyzers
> Vacuum Components
> Vacuum Gauges
> Vacuum Valves and Gas Dosing Systems

Stiletto Scanning-Laser Particle Detector


Real-Time In Situ Particle Monitoring for Maximum Yield

INFICON Stiletto® is a breakthrough vacuum in situ particle detector that can find yield-limiting contamination in real time on every wafer with scanning-laser sensitivity and accuracy. An easy-to-use interface with INFICON FabGuard® Sensor Integration and Analysis System enables synchronized data collection and diagnostics for real-time Advanced Process Control, wafer yield improvement, and increased tool productivity for the most demanding semiconductor applications.

Features at a Glance

  • resonant scanning-laser for increased detection area and accurate particle sizing
  • reduces costs by improving yield and reducing test wafer usage
  • improves productivity and tool availability by predicting maintenance events and isolating particle sources
  • fully compatible with FabGuard Sensor Integration and Analysis System
  • sensor bus communication is compliant with existing AEC/APC systems
  • available for pump line applications in process chambers, transfer chambers and loadlocks

Scanning for Greater Sensitivity

The Stiletto resonant scanner continuously monitors a large volume of the process chamber or vacuum pumping line and is able to provide statistically significant count rates for process control. Superior noise rejection and fast signal processing speed provide Stiletto with unprecedented accuracy and count rate for demanding processes. This combination of cutting-edge technologies delivers submicron sensitivity that detects "killer particles" while avoiding nuisance events. So you get reliable fault detection for every wafer, every run, every time.

Applications

  • process/equipment/component optimization
  • process fingerprinting
  • PM prediction and recovery
  • fault detection and classification for maximum yield