Reliability assessment of cutting tools life based on advanced approximation methods

Cutting tools' reliability influences the whole manufacturing efficiency. However, in most cases the same cutting tool may be used for different operations with different processing parameters, making thus difficult to estimate the remaining life of the tool precisely. The present study proposes a new reliability estimation approach to the cutting tools based on advanced approximation methods. Reliability-based design/operation is a technique extensively employed for problems of structural reliability, assessing the performance of critical infrastructure under stochastic design parameters. Due to the complexity of machining processes which involve a significant number of hidden or difficult to statistically model variables, advanced approximation methods, such as response surface or surrogate modelling methods may be applied, starting from a few sample points obtained through fundamental experiments and extending them to models able to predict/estimate the values of control values/indicators as a function of the key design variables, often referred to as limit states. Having constructed such models, and according to the level of probability that need to be measured, different reliability analysis methods can be employed such as Monte Carlo Simulations or First Order Reliability Methods (FORM). In the present study these two reliability analysis methods are assessed for estimating the reliability of cutting tools.