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Top1. Introduction
Chip form and tool wear are two of the major machining performance measures that have been the subject of extensive studies over several decades.
It must be said that having the true conception of chip formation and chip movement is an essential task in the prediction of chip breakability, furthermore, geometrical features of produced chip give us valuable information about tribological phenomena in cutting zone such as tool wear, cutting zone temperature, etc.
On the other hand, tool wear and economical estimations related to tool life are among essential issues associated with machining optimization, because in automated manufacturing operations, tool must be removed from the cutting process well before it fails, otherwise the parts produced become out of the allowable tolerance (Devillez & Lwsko & Mozer, 2004). Therefore, tool wear is of great significance in manufacturing since it affects the quality of the components, tool life and machine costs.
Mechanisms responsible for tool failure are abrasive, adhesive and diffusion wear (Devillez & Lwsko & Mozer, 2004). Considering that the chip radius has a direct relation with the form of crater wear and this type of wear is formed due to adhesive and diffusion factors, so it can be resulted that these factors affect chip geometry impressively.
There has been some research on tool wear estimation over the past several years, and some analytical (Dawson & Kurfess, 2005) and empirical models were proposed for the evaluation of crater depth and length, however most of them lack practical applications.
Several direct and indirect measurement techniques have been proposed for evaluating crater wear in carbide inserts. Direct methods are based upon direct measurements of the worn area of the tool using optical (Dawson & Kurfess, 2005) and vision systems (Jurkovich & Korosec & Kopac, 2005; Khalifa & Densibali & Faris, 2006). These methods have advantage of high-measuring accuracy, but cannot be easily adopted for online applications, mainly because of interruption of coolant and chips (Lister & Barrow, 1986; Tlutsy & Andrews, 1983). For this reasons, several authors have proposed indirect techniques for wear monitoring.
Various indirect methods have also been developed in which the state of the wear in different cutting operations is estimated from measurable parameters such as, the cutting forces (Choudhury & Kishore, 2000; Moriwaki, Shibasaka, & Tangjistcharoen, 2004), vibration analysis (Ramakrishna & Prasad & Kumar & Shantha, 1996), acoustic emission (Li, 2002; Telsang & Katu, 2004) and cutting temperature (Natarajan, Arun, & Periasamy, 2007) and using ultrasonic technique. However, few reliable and robust indirect methods are available for industrial use. This is mainly due to the intricacy involved in machining process and uncertainty in the correlation between the process parameters and tool wear.