# Defect Detection on Semiconductor Wafers by Distribution Analysis

arXiv: https://arxiv.org/abs/2111.03727 · HTML: https://mlsanity.com/paper/2111.03727/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 12 references that are in the map.
- First posted on arXiv 5 Nov 2021.

## Builds on (most cited first, 1 of 1)

- [Fast Accurate Defect Detection in Wafer Fabrication](https://mlsanity.com/paper/2108.11757/) (2021)

## Abstract (arXiv)

A method for object classification that is based on distribution analysis is proposed. In addition, a method for finding relevant features and the unification of this algorithm with another classification algorithm is proposed. The presented classification algorithm has been applied successfully to real-world measurement data from wafer fabrication of close to hundred thousand chips of several product types. The presented algorithm prefers finding the best rater in a low-dimensional search space over finding a good rater in a high-dimensional search space. Our approach is interesting in that it is fast (quasi-linear) and reached good to excellent prediction or detection quality for real-world wafer data.