Abstract: At present, there are a variety of cutting tools in the market, so it’s difficult to select a suitable tool for a specific application, thus often spending a great deal of time and materials. To reduce selection difficulty, it’s necessary to develop a new method. Characteristic parameters, namely, tool life, dulling criteria, initial wear value and milling length at initial wear are picked out from 295 milling tool wear curves to calculate initial wear rate K0, final wear rate K1 and the ratio K between the two. Statistic analysis of K0, K1 and K is carried out, the results show that the random variables K0 and K1 comply with lognormal distribution, K complies with translational exponential distribution, K0 and K1 are not independent to each other, thus obtaining the statistical law that the faster the initial wear is, the shorter the tool life will be. Base on this, a milling tool rapid selection method is put forward and validated through tests. This method can greatly save material and time for experiments and make it possible to select best tool material from a large number of candidates.

Key words: Initial wear, Milling tool rapid selection, Statistical law, Tool life