Indirect cutting tool wear classification using deep learning and chip colour analysis

In the growing Industry 4.0 market, there is strong need to implement automatic inspection methods to support manufacturing processes. Tool wear in turning is one of the biggest concerns that most expert operators are able to indirectly infer through the analysis of the removed chips. Automatising t...

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Veröffentlicht in:	International journal of advanced manufacturing technology 2020-11, Vol.111 (3-4), p.1099-1114
Hauptverfasser:	Pagani, Luca, Parenti, Paolo, Cataldo, Salvatore, Scott, Paul J., Annoni, Massimiliano
Format:	Artikel
Sprache:	eng
Schlagworte:	CAE) and Design Channels Chips Computer-Aided Engineering (CAD Cutting tool materials Cutting wear Deep learning Digital cameras Digital imaging Engineering Image classification Image processing Image segmentation Industrial and Production Engineering Inspection Machine learning Management planning Mechanical Engineering Media Management Neural networks Original Article Process parameters Process planning Sensitivity analysis Tool wear Turning (machining) Workpieces
Online-Zugang:	Volltext
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