Selected problems of cutting tool diagnosis and use

The growing requirements related to the capacity of automatic machining systems impose the necessity to carry out an online diagnosis of a tool. The online diagnosis is prevailingly applied so as to prevent any possible negative effects, especially the so-called catastrophic edge blunting (CEB) which means an unexpected tool edge chipping during a machining operation. The determination of optimum time-schedules to minimise outage of machine tools is also important. This paper provides a cohesive strategy method to minimise the cost of monitored tool use. The cost determination is based on the so-called a priori probability of CEB to happen, its detection uncertainty and the costs of decisions made up by a control circuit that controls the machining system run (e.g. change of tool). The cost of use, including deterministic and stochastic variables, is minimised according to Bayes's Model. It was shown that a non-stationary and stochastic character of cost causes the CEB detection to differ from the common problems considered in the theory of decisions. It was found that the costs of decisions strictly depend on the method of machine tool run assumed, together with CEB detector, and shall be established for a specific process case.