TY - JOUR
T1 - IDARTS – Towards intelligent data analysis and real-time supervision for industry 4.0
AU - Peres, Ricardo Silva
AU - Rocha, André Dionísio
AU - Leitão, Paulo
AU - Barata, José
N1 - Sem PDF conforme despacho.
PY - 2018/10/1
Y1 - 2018/10/1
N2 - The manufacturing industry represents a data rich environment, in which larger and larger volumes of data are constantly being generated by its processes. However, only a relatively small portion of it is actually taken advantage of by manufacturers. As such, the proposed Intelligent Data Analysis and Real-Time Supervision (IDARTS) framework presents the guidelines for the implementation of scalable, flexible and pluggable data analysis and real-time supervision systems for manufacturing environments. IDARTS is aligned with the current Industry 4.0 trend, being aimed at allowing manufacturers to translate their data into a business advantage through the integration of a Cyber-Physical System at the edge with cloud computing. It combines distributed data acquisition, machine learning and run-time reasoning to assist in fields such as predictive maintenance and quality control, reducing the impact of disruptive events in production.
AB - The manufacturing industry represents a data rich environment, in which larger and larger volumes of data are constantly being generated by its processes. However, only a relatively small portion of it is actually taken advantage of by manufacturers. As such, the proposed Intelligent Data Analysis and Real-Time Supervision (IDARTS) framework presents the guidelines for the implementation of scalable, flexible and pluggable data analysis and real-time supervision systems for manufacturing environments. IDARTS is aligned with the current Industry 4.0 trend, being aimed at allowing manufacturers to translate their data into a business advantage through the integration of a Cyber-Physical System at the edge with cloud computing. It combines distributed data acquisition, machine learning and run-time reasoning to assist in fields such as predictive maintenance and quality control, reducing the impact of disruptive events in production.
KW - Cyber-physical systems
KW - Data analytics
KW - Industry 4.0
KW - Multi- agent systems
KW - Predictive manufacturing systems
UR - http://www.scopus.com/inward/record.url?scp=85050319341&partnerID=8YFLogxK
U2 - 10.1016/j.compind.2018.07.004
DO - 10.1016/j.compind.2018.07.004
M3 - Article
AN - SCOPUS:85050319341
VL - 101
SP - 138
EP - 146
JO - Computers in Industry
JF - Computers in Industry
SN - 0166-3615
ER -