Abstract
This paper provides a review and proposal for condition-based maintenance (CBM) in blanking of sheet metal. To date, little research on this topic can be found in literature, which is probably due to the complex nature of the process. Previous statistical, artificial intelligence (AI) and model-based approaches are analysed. Special attention is given to inherent assumptions and other sources of inaccuracy. In addition, it is demonstrated how the signature of the force-displacement relation changes significantly with increasing tool wear in a typical configuration of sheet steel blanking. An analysis follows as to how such behaviour could be used in CBM. A practical implementation of CBM in sheet metal blanking is proposed based on a hybrid solution. (c) 2007 Elsevier Ltd. All rights reserved.
| Original language | English |
|---|---|
| Pages (from-to) | 589-598 |
| Number of pages | 10 |
| Journal | International journal of machine tools & manufacture |
| Volume | 48 |
| Issue number | 5 |
| DOIs | |
| Publication status | Published - Apr-2008 |
Keywords
- blanking
- condition-based maintenance
- tool wear
- in-process control
- artificial neural networks
- expert systems
- TOOL WEAR
- DUCTILE FRACTURE
- BLANKING
- MODEL
- STEEL
- GROWTH
- SYSTEM