リソースセンター 

Data centers are growing in both size and complexity. Keeping track of thousands of servers, cables, and rack components through manual inspections is slow, inconsistent, and leaves gaps where problems can go unnoticed. AI-powered machine vision systems address this by monitoring rack conditions continuously by detecting issues as they happen rather than during the next scheduled check. This application note covers: Identifying and verifying rack components automatically Detecting problems like disconnected cables or missing hardware Reading labels, port IDs, and asset tags and checking them against your configuration records Deploying inspection across multiple racks, aisles, and facilities at scale.

半導体製造は、世界で最も高度かつ要求の厳しい製造プロセスのひとつでです。今日のチップは、微細な構造の中に何十億ものトランジスタを詰め込んでおり、製造のあらゆる段階を絶対的な精度で実行しなければなりません。わずかな欠陥やアライメントエラーが、歩留まりの低下、ウェーハの無駄、数百万ドルの損失へとつながる可能性があります。