No abstract

Machining wear models are useful for the prediction of tool life and the estimation of machining productivity. Existing wear models relate the cutting parameters of feed, speed, and depth of cut to tool wear. The tool wear is often reported as changes in flank width or crater depth. However, these one-dimensional wear measurements do not fully characterize the tool condition when tools wear by other types of wear such as notching, chipping, and adhesion. This is especially true when machining difficult-to-machine materials such as titanium. This paper proposes another approach for characterizing tool wear. It is based on taking measurements of the retained volume of the cutting tool. The new wear characterization approach is used to demonstrate the progression of volumetric wear in titanium milling.

In part 1, traditional methods of tool wear characterization were qualitatively assessed, and consequently a volumetric approach of wear quantification was developed, standardized, and evaluated using a gauge R&R study. The objective of this paper is to experimentally investigate and validate this assessment methodology using the wear results from a series of controlled machining experiments on grade-5 titanium alloy. The traditionally difficult-to-machine alloy, TÍ-6AI-4V, was specifically chosen as the work material in order to highlight how the use of this assessment methodology is necessitated especiatty because of(i) the pronounced comptexities in the geometric profites of typicat cutting toots emptoyed for machining its nonconformity in behavior with standard toot wear modets, such as the Taytor's toot tife modet and its extensions. This assessment methodology is then vatidated through the simuttaneous anatysis and comparison of traditional flank wear and associated photomicrographs with volumetric wear and its evolution. Furthermore, the concept of the M-ratio and its derivatives are developed to quantify the efficiency of the cutting tool during each pass at a constant material removal rate (MRR).

No abstract

No abstract