Name
Abstract | ||
|---|---|---|
Production systems modeling aims at offering a generic representation applicable to industrial cases in order to assess their operating modes, evaluate their performances or guide their evolution. This paper provides a modeling method to represent complex networked production systems in mind to control them. The model is suitable to analyze a system at different steps in its life cycle: design, operating, re-engineering. For each of these steps, the model represents either the functional view or the organic view of the system or both to provide the analysts with the relevant information. Guidelines for model tuning during system's life cycle are also defined, based on the analysis of the nature and criticality of the events, which justify re-engineering activities. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1109/ICSMC.2004.1401368 | SMC (7) |
Keywords | Field | DocType |
control assessment,production system life-cycle modeling,manufacturing systems,production control,distributed control,complex networked production system,production system,life cycle,functional model,complex network,production management | Production manager,Production control,Systems engineering,Computer science,Manufacturing systems,Systems modeling,Artificial intelligence,Criticality,System lifecycle,Functional modeling,Machine learning | Conference |
Volume | ISSN | ISBN |
7 | 1062-922X | 0-7803-8566-7 |
Citations | PageRank | References |
2 | 0.52 | 1 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Severine Spérandio | 1 | 2 | 0.86 |
| Frederic Pereyrol | 2 | 4 | 1.59 |
| Jean-paul Bourrières | 3 | 8 | 3.06 |