Quality Control in Sapphire Growing: From Automated Defect Detection to Big Data Approach

Abstract

We illustrate how automated scanners visualise internal defects in raw sapphire prior to its processing, and present some defect statistics that Scientific Visual has collected over five years of serving key sapphire suppliers in Europe and Asia. The article illustrates use of defect location and morphology data to reveal trends in sapphire quality, compare production modes, and to find out the optimal parameters for sapphire growth.