New Yield Prediction Method Aims to Speed Up Panel Packaging Ramps

At a glance

Fan-out panel-level packaging (FOPLP, a method that places chips on a large panel and makes many packages at once) is more efficient than wafer-based methods for AI chip packages. But as panels grow, circuit patterns distort and chips shift out of place, which lowers yield. The article describes using offline measurement data and yield prediction algorithms to evaluate process conditions before running full production trials.

Key points

1. 1

   Panel-based packaging can produce more packages from the same substrate than wafers can.

2. 2

   Larger panels cause pattern distortion and chip shifts that lead to alignment errors.

3. 3

   Correction methods that improve accuracy also slow throughput, making the right balance hard to find.

4. 4

   Measurement data and prediction algorithms can estimate yield before repeated physical trials.

Why it matters

As demand for AI chips grows, packaging output must ramp quickly, and cutting repeated trials can shorten preparation time and reduce material waste.