A large-scale framework for storage, access and analysis of time series data in the manufacturing domain

被引:4
|
作者
Moerzinger, Benjamin [1 ]
Weiler, Thomas [1 ]
Trautner, Thomas [1 ]
Ayatollahi, Iman [1 ]
Angerer, Bernhard [1 ]
Kittl, Burkhard [1 ]
机构
[1] TU Wien, Inst Prod Engn & Laser Technol, Karlspl 13, A-1040 Vienna, Austria
关键词
Linked data; Semantic web; Manufacturing; IMPROVEMENT;
D O I
10.1016/j.procir.2017.12.267
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Time series data from machining process monitoring promises to be a rich resource for optimization applications. Limited data access, however restricts the number of potential applications significantly. Semantic technologies such as ontology based data access could help overcoming those restrictions and therefore pave the way for a wider use of state of the art data analysis applications. Semantic web technologies are not yet widely applied in the manufacturing domain which partly has to do with the fact that in the past no relevant use cases where presented in this area. Therefore, in this paper, semantic technologies and their potential applications are illustrated using an existing research database. (C) 2017 The Authors. Published by Elsevier B.V.
引用
收藏
页码:595 / 600
页数:6
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