Name
Abstract | ||
|---|---|---|
Prediction is the way to optimize the maintenance task by determining the correct moment to interview, repair or replace equipment which the most difficult decision for companies in Industry 4.0 environment. This research present MASPI. I is a multiagent system based on advantages of virtual organization. The goal of MASPI is to be a reference model for making predictions about data captured by sensors installed in equipment or industrial machines. The capability of MASPI is evaluated by applying it to SCANIA trucks dataset, using machine learnings algorithms to obtain the prediction and compare their accuracy. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/978-3-319-94120-2_19 | INTERNATIONAL JOINT CONFERENCE SOCO'18-CISIS'18- ICEUTE'18 |
Keywords | Field | DocType |
Virtual organization,Multiagent system,Predictive maintenance,Failure diagnosis,Industry 4.0 | Truck,Industrial engineering,Reference model,Computer science,Multi-agent system,Artificial intelligence,Predictive maintenance,Industry 4.0,Machine learning,Virtual organization | Conference |
Volume | ISSN | Citations |
771 | 2194-5357 | 0 |
PageRank | References | Authors |
0.34 | 9 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Inés Sittón-Candanedo | 1 | 14 | 1.99 |
| Sara Rodríguez-González | 2 | 27 | 4.59 |
| Fernando De la Prieta | 3 | 263 | 41.90 |
| Angélica González Arrieta | 4 | 31 | 10.04 |