Using Big Data to Explore the Analysis of Smart Machine Management System

• Main Authors: YU AN,LIN, 林宥安
• Other Authors: Wen-Tsann Lin
• Format: Others
• Language: zh-TW
• Published: 2018
• Online Access: http://ndltd.ncl.edu.tw/handle/9ycf3k

碩士 === 國立勤益科技大學 === 工業工程與管理系 === 106 === The modern global industry is at the beginning of an era of innovation. Industry 4.0 combines machines, analysis, the Internet of Things (IoT), automation, and data exchange. We added communication capabilities to each device to connect the world of machines between devices and devices through the IoT, to establish a smart machine factory with resource efficiency and adaptability, provide perfect an after-sales service in business processes and value processes for integrating customers and business partners. In this study, we use WebAccess to let the production data and production status to do a charting, and the process can be monitored immediately to facilitate the transformation of the company in the future into a Small and Medium Enterprises with Industry 4.0 advanced technology. Through this mechanic analytical process technology, the mechanical industry can help factory to control the controllability of the robotic arm. The robotic arm is used to replace the traditional manual packaging mode. The robotic arm sucks and removes the plastic blister, grab the color pen, to pick up the paper card to insert in the plastic blister. During the process, the inspection data are transmitted to WebAccess. WebAccess collects test the production loop data and the data mining screens a large number of data and then discards the data to the inverted transmission neural network for analysis to examine the model of the production rate. Finally, the two-stage clustering method is used to verify the consistent rate. The planning of production processes through data models to achieving consistency, it can also reduce the production risks and reduce personnel costs, evolution to a lights-out manufacturing.