PSI - Issue 59

Viktor Kovalov et al. / Procedia Structural Integrity 59 (2024) 779–785

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V. Kovalov et al. / Structural Integrity Procedia 00 (2019) 000 – 000

1. Introduction Studies of the peculiarities of tool operation on heavy machine tools (Yang et al., 2019; Yanbin et al., 2020; Qin 2023; Gaddafee et al., 2020), have shown that along with increased average loads on cutting tools associated with significant shear cross-sections, during machining there is also a large number of perturbing factors associated with the dispersion of operating parameters and tool properties. One of the most important criteria for the quality of the technological process is its reliability (Dai et al., 2019; Gaddafee et al., 2020). Since the process of machining parts on heavy machine tools is a complex system, a number of different indicators are used to assess its reliability in the works (Klymenko et al., 2019; Letot et al., 2016; Cui et al., 2017). When machining on heavy machine tools, the formation of target functions should be made based on a given level of reliability of the cutting tool (Liu et al., 2020). Reliability assessment of prefabricated tools for heavy machine tools is important not only at the operation stage, but also at the stage of their design. Currently, a large number of indicators are used to determine the failure free (Wardany et al., 1997; Karimi et al., 2019), durability (Baksa et al., 2015) and maintainability (Huynh 2021; Zaretalab et al., 2020) of the tool separately. The distribution of the tool durability period characterizes the reliability of the cutting blade and does not allow solving the problem of ensuring reliable operation of the tool including other structural elements of the prefabricated tool. A complex indicator of reliability of the prefabricated tool as a system can serve as a readiness factor (Klymenko et al., 2019). From the point of view of reliability, an assembled carbide turning cutter can be represented as a sequential system, since failure of any element of the turning cutter leads to failure of the entire system. It can be considered as a serviceable system due to the presence of the process of serviceability recovery, i.e. replacement of the failed elements. The availability factor characterizes both the fail-safe and maintainability of the tool. It determines the probability of the system being in a serviceable state at some point in time, provided that at the initial moment the system was in a serviceable state. Applying the Markovian approach to the description of the system, it is necessary to assume that turning cutter failures occur according to the exponential distribution law, and the time of replacement of failed elements is a random variable with an exponential distribution. Statistical studies of carbide turning cutter performance do not always confirm the assumption of exponential distribution. However, due to the fact that failed elements (e.g., the cutting insert) require a small recovery time compared to the duration of operation of other elements (e.g., the tool body), the application of the Markovian approach to assessing the reliability of the system makes it possible to obtain mathematical models that describe the behavior of the system with sufficient accuracy for practical application (Yamany et al., 2021; Karandikar et al., 2014). Nomenclature  cutting insert failure rate  intensity of cutting insert recovery (replacement of cutting tops) P 0 probability of the system being in a serviceable state P 1 probability of the system staying in a failure state А (t) system availability function As F system availability factor Т cutting tool durability А ( Т ct ) average time of operable state of the turning cutter T р average cutting tool durability period Тγ gamma-percentage period of cutting tool durability PMFT pulsed magnetic field treatment VT vibration treatment 2. Experimental device and methodology When developing a system of rational cutting tool operation, one of the target functions for multicriteria optimization of operation regulations is proposed to use the system readiness function, which characterizes its reliability and is an indirect indicator of the machine operator's labour intensity. The readiness function in steady state mode (i.e. at a sufficiently large time interval under consideration) is a readiness factor numerically equal to the