TY - GEN
T1 - A requirement for traceability of production logs in large-scale shop floor data
AU - Park, Jaehui
AU - Chi, Su Young
N1 - Publisher Copyright:
© 2015 ACM.
PY - 2015/10/20
Y1 - 2015/10/20
N2 - The rate of data growth in the manufacturing industry exceeds the capacity of conventional manufacturing information systems. Recently, big data analysis is considered to enhance the existing systems to extract an insight from the large-scale shop floor data. However, there remain a lot of unsolved, practical problems that the existing systems have not taken account of. In this paper, we propose a largescale data management system to integrate the set of manufacturing data with regard to four common elements: machine, material, method, and man. Additionally, we suggest a novel problem to trace production logs without any linkage between materials and products. Our ultimate goal is developing an information system for predictive manufacturing, which can capture, in advance, potential risk factors, such as machine worn out progress and production time loss tendency. The work is expected to meet the visions of emerging innovative projects for the future manufacturing industry.
AB - The rate of data growth in the manufacturing industry exceeds the capacity of conventional manufacturing information systems. Recently, big data analysis is considered to enhance the existing systems to extract an insight from the large-scale shop floor data. However, there remain a lot of unsolved, practical problems that the existing systems have not taken account of. In this paper, we propose a largescale data management system to integrate the set of manufacturing data with regard to four common elements: machine, material, method, and man. Additionally, we suggest a novel problem to trace production logs without any linkage between materials and products. Our ultimate goal is developing an information system for predictive manufacturing, which can capture, in advance, potential risk factors, such as machine worn out progress and production time loss tendency. The work is expected to meet the visions of emerging innovative projects for the future manufacturing industry.
KW - Integration
KW - Manufacturing execution systems
KW - Predictive manufacturing
KW - Production logs
KW - Traceability
UR - http://www.scopus.com/inward/record.url?scp=84996968555&partnerID=8YFLogxK
U2 - 10.1145/2837060.2837084
DO - 10.1145/2837060.2837084
M3 - Conference contribution
AN - SCOPUS:84996968555
T3 - ACM International Conference Proceeding Series
SP - 151
EP - 155
BT - Proceedings of the 2015 International Conference on Big Data Applications and Services, BigDAS 2015
A2 - Nasridinov, Aziz
A2 - Leung, Carson K.
PB - Association for Computing Machinery
T2 - 2015 International Conference on Big Data Applications and Services, BigDAS 2015
Y2 - 20 October 2015 through 23 October 2015
ER -