Open AccessReal-time Big Data Processing System to Improve Semiconductor Production Efficiency in Smart Factory
Author(s) -
Hyeopgeon Lee,
Yong Woon Kim,
KiYoung Kim
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i3.33.21021
Subject(s) - production line , semiconductor device fabrication , factory (object oriented programming) , data processing , computer science , production (economics) , process (computing) , process control , big data , production control , process engineering , real time computing , engineering , database , electrical engineering , data mining , operating system , mechanical engineering , wafer , economics , macroeconomics , programming language
Semiconductor production efficiency is closely related to the defect rate in the production process. The temperature and humidity control in the production line are very important because these affect the defect rate. So many smart factory of semiconductor production uses sensor. It is installed in the semiconductor process, which send huge amounts of data per second to a central server to carry out temperature and humidity control in each production line. However, big data processing systems that analyze and process large-scale data are subject to frequent delays in processing, and transmitted data are lost owing to bottlenecks and insufficient memory caused by traffic concentrated in the central server. In this paper, we propose a real-time big data processing system to improve semiconductor production efficiency. The proposed system consists of a production line collection system, task processing system and data storage system, and improves the productivity of the semiconductor manufacturing process by reducing data processing delays as well as data loss and discarded data.