InImpact: The Journal of Innovation Impact |
| Publisher |
Future Technology Press |
| Vol. 7 No. 2 |
KES Transactions on SDM I - Sustainable Design and Manufacturing 2014 |
| Volume Editors |
KES International |
| Journal ISSN |
2051-6002 |
| |
| Article Title | Self-Learning Production Systems: A New Production Paradigm |
| Primary Author | Giovanni Di Orio, CTS - UNINOVA |
| Other Author(s) |
Gonçalo Cândido; José Barata
|
| Pages |
887 - 898
|
| Article ID |
sdm14-115 |
| Publication Date |
01-May-16 |
| Abstract | Self-Learning Production System (SLPS) is a fundamental paradigm introduced to ensure industrial systems evolvability along time. Evolvability is considered as the capability of a system to change its behaviour, i.e. its internal status and/or parameters, according to different production contexts. The SLPS approach is intended to confer evolvable capabilities to a manufacturing production system by enhancing its monitoring and control solutions with context-awareness and data mining techniques. The key assumption is that the deep use of context-awareness and data mining techniques to extract, analyse, and process relevant data generated during production activities will ensure system adaptation. Current work is an effort to systematize the technical and theoretical developments in the context of SLPS in order to provide the baseline upon which SLPS solutions can be built. |
| | View Paper |
