TY  - JOUR
T1  - An Autonomic Computing based on Big Data Platform for High-Reliable Smart Factory
AU - Kim, Jeong-Joon AU - Lee, Deuk-Woo AU - Ko, Dong-Beom AU - Jeong, Sung-Il AU - Park, Jeong-Min 
JO  - Journal of Engineering and Applied Sciences
VL  - 12
IS  - 10
SP  - 2662
EP  - 2666
PY  - 2017
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2017.2662.2666
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2017.2662.2666
KW  - Big data
KW  -trust system
KW  -autonomic computing
KW  -analytics
KW  -system architecture
AB  - This study will design a big data platform for the high reliability smart factory. With the advent of the fourth industrial revolution, the interest and demand for autonomic control systems are increasing. Autonomic control system in order to establish an accurate diagnosis and error response for the target system, the machine requires a machine learning through big data. But now big data platform cannot guarantee the reliability of the data because there is not enough data verification. In addition, existing facilities need a uniform standard because the format for data collection differs depending on the manufacturer. Therefore, this study designs a reliable big data platform for autonomic control engine using manufacturing facility data standard. Through this, pattern recognition of autonomic control engine using reliable data, machine learning, accurate diagnosis of system and countermeasure strategy against error can be established.
ER  -