Tula State University (Tula, Russia):

A. V. Antsev, Cand. Eng., Associate Prof., e-mail: a.antsev@yandex.ru
N. I. Pasko, Dr. Eng., Prof.
N. V. Antseva, Cand. Eng., Associate Prof.

A tool life of cutting tool during ferrous metals machining is a random variable. The spread of a tool life of cutting tool can be 15-35 % within same batch. Unforeseen tool failure has a serious impact on the cost of products. Many scientific works are devoted to predicting the tool life of a cutting tool and optimizing cutting speed and the period of its replacement. However, most researchers do not take into account the stochastic nature of the process of cutting of ferrous metals. In this work it is considered that a tool life with abrasive wear due to the variation in the cutting properties of individual tools even in single batch and due to the variation in the properties of workability of workpieces (hardness, machining allowance, etc.) is a random variable with a certain distribution law. It is necessary to know the distribution law of this random variable and the dependence of the parameters of this law on the parameters of the cutting mode. As an optimization criterion, the unit costs are taken. The unit costs are the costs of replacing the tool and possible defects during machining with the failed tool per one processed part. The search for optimal values of the cutting speed and the period of the cutting tool replacement with minimum of the unit costs was performed by an enumerative technique with a small step due to the multi-extremality of the unit costs function. The article describes an example of optimization of cutting speed and tool replacement period when machining 1X18H9T (1Kh18N9T) steel with replaceable hard-alloy T30K4 plates. It is shown that taking into account stochastic nature of machining will reduce the unit costs by 86.4% with a zero reject level and 69.5% with a reject level of 0.1% while optimizing for productivity and cost, respectively, in the case when the tool life of the cutting tool has a variation with variation coefficient 0.1.
The results of the study have been published with financial support of the TSU within the framework of the scientific project No. 8705.

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