在製造的相關產業中，大多數在倉儲上的管理多以人做管理，撇開自動倉儲不談，業界99.5%以上的公司都是以傳統人員作業為主，尤其公司的品項多且雜，在處理上往往仰賴有經驗的作業人員做辨識，如此人離職或請假，後續的工作者在作業上也有很大問題，此技術是希望解決傳統人工辨識及時間上的浪費。本研究開發的目的是種新型態的倉儲作業管理。本論文使用OpenCV結合人工智慧的影像辨識技術在倉儲管理上做到人員以及物料辨識作業管理，以較為經濟的方式做到迅速的辨別來節省人力及不必要的浪費，有效改善傳統倉儲作業模式，其中包含的技術有Python、OpenCV、Tensorflow、Keras…等。 In the related industries of manufacturing, most of the management in warehousing is managed by people. Automatic warehousing aside , more than 99.5% of companies in Taiwan are managed by manpower.When a company's products are numerous and complex, they often rely on experienced operators to handle. If someone take time off, no one can help to take care his work in a short time. This research is intended to solve mistakes of traditional manual identification and time waste.The purpose of this research is to develop a new type of warehouse operation management.This research include the latest identification technology ex, Python, OpenCV, Tensorflow and more economical methods to quickly identify and effectively improve the traditional storage operation mode.
