消費性電子

裝配前安裝檢查

發現組件干擾、錯位和錯配的組件、孔洞及扣件

相關產品

VisionPro ViDi Product Tile

VisionPro Deep Learning

深度學習工業圖像分析的圖形化程式設計環境

In-Sight D900

In-Sight D900

採用 In-Sight ViDi 深度學習視覺軟體

在裝置裝配之前,模組的外殼區域周圍常會有異物落入。像鬆脫的螺絲這類的異物會從鄰近的模組掉入裝置。這種碎片通常很小且有各種不同顏色,使用傳統的灰階相機通常非常難以偵測出來。此外,鑄模流程進行時可能會忽略溢料或鰭片 (塑膠元件輪廓邊緣的異物) 而送交生產,但這會在裝配期間造成妨礙。

使用三維視覺 (運用獨立色彩) 進行裝配前安裝檢查,可確定模組安裝區域沒有任何碎片、螺絲 (小至 1mm 以下) 及溢料會中斷裝配流程。

Cognex Deep Learning allows the manufacturer to check the battery’s integrity before the phone undergoes final assembly, and to differentiate between cosmetic and functional anomalies. Using the defect detection tool in supervised mode, an engineer can train the software on “good” images as well as “bad” images with labeled defects. From these images, the tool learns the battery’s normal appearance, including natural acceptable variations. Parameters can continually be adjusted during the training phase and validation period until the trained model correctly detects and segments all images with functional anomalies. Once deployed, the defect detection tool identifies and rejects batteries with defects

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