This pattern helps you automate the training and deployment of Amazon Lookout for Vision machine learning models for visual inspection. Although this pattern concentrates on anomaly detection for silicon wafers, you can adapt the solution for use in a wide range of products and industries.

In 2020, the annual capacity of one of the largest semiconductor manufacturers in the world exceeded 12 million 12-inch equivalent wafers. To ensure the quality and reliability of these wafers, visual inspection is an essential step in the production process. The traditional methods of visual inspection, such as manual sampling or the use of outdated, legacy tools that rely on statistical measures, can be time-consuming and inefficient. Given the scale of this process and its importance to the broader semiconductor industry, there is a significant opportunity to optimize and automate visual inspection by using advanced artificial intelligence (AI) technologies.