Automatically Generate SMT Mounter Production Data with Python Web Scraping

This study proposes an automated data collection method that combines web scraping and production data storage web pages to improve the efficiency of data production for SMT production metrics. It focuses on extracting data from Panasonic's “Proviewer” webpages and generating data on the Mounters' Line Balance Rate and Loss Rate. After confirming with the vendor that using web scrapping for USI's internal data collection does not cause copyright infringement, Python's Selenium and BeautifulSoup packages were implemented. This automated the traditional manual data collection and measurement methods of the IE and PD departments, capturing data directly from the platform and presenting it visually with statistical verification. The ultimate goal is not only to automate the generation of metrics but also to reduce the workload of counterparts through programming language assistance.