Real-time cutting tool condition monitoring in milling

Franc Čuš (Author), Uroš Župerl (Author)

Abstract

Reliable tool wear monitoring system is one of the important aspects for achieving a self-adjusting manufacturing system. The original contribution of the research is the developed monitoring system that can detect tool breakage in real time by using a combination of neural decision system and ANFIS tool wear estimator. The principal presumption was that force signals contain the most useful information for determining the tool condition. Therefore, the ANFIS method is used to extract the features of tool states from cutting force signals. ANFIS method seeks to provide a linguistic model for the estimation of tool wear from the knowledge embedded in the artificial neural network. The ANFIS method uses the relationship between flank wear and the resultant cutting force to estimate tool wear. A series of experiments were conducted to determine the relationship between flank wear and cutting force as well as cutting parameters. Speed, feed, depth of cutting, time and cuttingforces were used as input parameters and flank wear width and tool state were output parameters. The forces were measured using a piezoelectric dynamometer and data acquisition system. Simultaneously flank wear at the cutting edge was monitored by using a tool maker's microscope. The experimental force and wear data were utilized to train the developed simulation environment based on ANFIS modelling. The artificial neural network, was also used to discriminate different malfunction states from measured signals. By developed tool monitoring system (TCM) the machining process can be on-line monitored and stopped for tool change based on a pre-set tool-wear limit. The fundamental limitation of research was to develop a single sensor monitoring system, reliable as commercially available system, but 80% cheaper than multisensor approach.

Keywords

end-milling;tool condition monitoring;wear estimation;ANFIS;

Data

Language:	English
Year of publishing:	2011
Typology:	1.01 - Original Scientific Article
Organization:	UM FS - Faculty of Mechanical Engineering
Publisher:	= Association of Mechanical Engineers and Technicians of Slovenia et al.
UDC:	621.9
COBISS:	14812182
ISSN:	0039-2480
Parent publication:	Strojniški vestnik
Views:	735
Downloads:	37
Average score:	0 (0 votes)
Metadata:

Other data

Secondary language:	Slovenian
Secondary keywords:	nadzor orodja;oblikovno frezanje;obraba;lom orodja;ANFIS;nevronske mreže;
URN:	URN:NBN:SI:doc-MW8QLHUX
Type (COBISS):	Not categorized
Pages:	str. 142-150
Volume:	Vol. 57
Issue:	no. 2
Chronology:	feb. 2011
DOI:	10.5545/sv-jme.2010.079
ID:	1728647