Advanced low-k die singulation defect inspection and pre-emptive singulation defect detection

Advanced packaging has a challenge on its hands in dealing with reliability issues caused during singulation. Specifically, in the case of Wafer Level Chip Scale packaging (WLCSP) where the sawn die edge is the package edge and is exposed. WLCSP manufactured on the newer nodes are based on Ultra-low K dielectric material. This material is inherently porous and mechanically fragile. During the singulation step, there is a likelihood of creating chipping and delamination. Rudolph have developed a comprehensive approach to detecting defects generated at the laser grooving and saw process steps. There are two recommended approaches. The first approach is an inspection approach that is focused on detecting the defects after it has occurred. The second, a more sophisticated approach is to attempt to pre-empt occurrence of defects. In the first approach-die seal ring inspection, algorithms have been developed around the die seal ring to ensure the die integrity. These algorithms not only include the capability to detect the defect but also measure the defect size, defect position and frequency of defects. All of this is done while minimizing false defects that are typically found due to street and reticle artifacts that are often falsely detected as chipping. This enables customers to perform advanced disposition to ensure the optimal balance between shipping good die and preventing the shipment of potential reliability fails. The second approach - Kerf metrology and Saw control comprises of Fault detection and classification (FDC) to record equipment data during the singulation processes and inspection equipment to detect surface defects such as chips, delamination and cracks. The combination of FDC to monitor equipment performance and the ability to correlate Metrology/Inspection performance data enables customers to not only detect defects but preemptively eliminate them. Poorly singulated dies can now be analyzed all the way back to the process equipment signals. Once these signals are identified they can be monitored to prevent or alert operators of possible excursions. These analytics will help customers define and ramp robust processes, justify consumable costs and ultimately lead to a better understanding of this difficult and challenging process. Finally, specific YMS capabilities exist to align and analyze the collected equipment and process data.