A review of flank wear prediction methods for tool condition monitoring in a turning process

International Journal of Advanced Manufacturing Technology

Volumn 65, Issue 1-4, 2013, Pages 371-393

  Siddhpura, A ^a,b   Paurobally, R ^a,b  

^a UNIVERSITY OF WESTERN AUSTRALIA   (Australia)

^b CRC for Infrastructure and Engineering Asset Management (CIEAM)   (Australia)

Author keywords

Artificial intelligence; Flank wear; Signal acquisition; Tool condition monitoring; Turning

Indexed keywords

ARTIFICIAL INTELLIGENCE TECHNIQUES; DOWN TIME; ECONOMIC LOSS; FLANK WEAR; KEY FEATURE; MATERIAL LOSS; MONITORING TECHNIQUES; ON-LINE DETECTION; SIGNAL ACQUISITIONS; TOOL CONDITION MONITORING; TURNING PROCESS;

ARTIFICIAL INTELLIGENCE; FEATURE EXTRACTION; LOSSES; METAL CUTTING; MONITORING; SIGNAL ANALYSIS; TURNING;

MACHINE TOOLS;

EID: 84874312616     PISSN: 02683768     EISSN: 14333015     Source Type: Journal    
DOI: 10.1007/s00170-012-4177-1     Document Type: Article

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