Cutting Tool Reliability Research Articles

Parameter Estimation of the Weibull Distribution in Modeling the Reliability of Technical Objects

The article discusses one of the most widely used distribution laws for reliability analysis – Weibull distribution. It describes a wide range of processes for all stages of the life cycle of technical objects, including yield stress of steel distribution and failures in the reliability theory regarding the wide range of technical objects (e.g., metal cutting tools, bearings, compressors, and wheels). A significant number of works are devoted to evaluating distribution law parameters based on empirical data in search of the most precise one, ignoring the probabilistic character of the parameters themselves. Parameters may have a relatively wide confidence range, which can be considered the parameter estimation error compared to biases of parameters estimated by different methods. Moreover, many approaches should be used for certain selection volumes, including comprehensive calculating procedures. Instead, this paper suggested and statistically confirmed a universal simplified approach. It demands a minimal set of data and connects the shape and scale parameters of the Weibull distribution with the variation coefficient as one of the leading statistical characteristics. This approach does not demand variational sequence arrangement. Nevertheless, it is supposed to be quite efficient for the engineering practice of reliability analysis. The adequacy of the results was confirmed using generated selections analysis and experimental data on cutting tool reliability. Within the achieved results, it was also demonstrated that the variation coefficient reflects not only selection stability and variable volatility degree, which are its main aim, but the cause of failure as well.

An Experimental Investigation of Cutting Tool Reliability and its Prediction Using Weibull and Gamma Models: A Comparative Assessment

This paper enlightens different methods that can be employed for assessment of cutting tool reliability. In this study the methods that are put to test are Weibull and Gamma distribution models. Test were carried out on AISI 4340 steel (35 HRC) using TiAlN coated carbide tool. Experimental results revealed that cutting tool reliability decreases with machining time. To ensure the feasibility and accuracy of the predicted results of cutting tool reliability using the Gamma model and Weibull model, multiple tool life experiments were conducted under different cutting conditions. The coeffiecient of correlation obtained for experimental values of cutting tool reliability and predicted results using Gamma model is close to one and marginally higher than the correlation coefficient for Weibull model, shows that the Gamma and Weibull models with their obtained values of characteristic parameters could be usedfor the estimation of cutting tool reliability during turning of workpiece-tool combination used in the present work.

Analysis of cutting tool reliability

Analysis of cutting tool reliability

Reliability of PVD-coated single-layer TiAlN carbide tool during turning of hardened AISI 4340 alloy steel

Reliability of a cutting tool in terms of tool wear is of foremost importance in metal cutting owing to its direct impact on the surface quality of the machined surface, and its dimensional accuracy, and consequently, on the economics of machining operations. With this view, in the present work, reliability of single layer PVD-coated TiAlN carbide tool is assessed during turning of hardened AISI 4340 steel (35 HRC) at various cutting conditions. Dry cutting tests were carried out with cutting speeds of 142, 265, 345 and 487 m/min and feed and depth of cut values of 0.125 mm/rev and 0.8 mm, respectively. Flank wear and its growth was monitored at regular intervals of length of cut using a digital microscope with a maximum magnification of 230X. Reliability of cutting tool obtained at different cutting conditions is compared with a view to understand the progression of tool wear and wear mechanisms at different stages of tool life. Environmental scanning electron microscope (ESEM) with energy dispersive X-ray spectroscopy (EDAX) system was used to understand tool wear and wear mechanisms. It has been observed that a better reliability of a PVD- coated tool could be obtained by limiting the cutting speed 200-250 m/min as at higher cutting speeds lower cutting tool reliability resulted due to the weakening of the cutting edge by an accelerated crater wear rate.

Reliability of Coated Carbide Tool During Turning Hardened Steel

Reliability of a cutting tool in terms of tool wear is of foremost importance in metal cutting owing to its direct impact on the surface quality of the machined surface, and its dimensional accuracy, and consequently, on the economics of machining operations. With this view, in the present work, reliability of single layer PVD-coated TiAlN carbide tool is assessed during turning of hardened AISI 4340 steel (35 HRC) at various cutting conditions. Dry cutting tests were carried out with cutting speeds of 142, 265, 345 and 487 m/min and feed and depth of cut values of 0.125 mm/rev and 0.8 mm, respectively. Flank wear and its growth was monitored at regular intervals of length of cut using a digital microscope with a maximum magnification of 230X. Reliability of cutting tool obtained at different cutting conditions is compared with a view to understand the progression of tool wear and wear mechanisms at different stages of tool life. Environmental scanning electron microscope (ESEM) with energy dispersive X-ray spectroscopy (EDAX) system was used to understand tool wear and wear mechanisms. It has been observed that a better reliability of a PVD-coated tool could be obtained by limiting the cutting speed 200-250 m/min as at higher cutting speeds lower cutting tool reliability resulted due to the weakening of the cutting edge by an accelerated crater wear rate.

Cutting tools reliability and residual life prediction from degradation indicators in turning process

In the field of cutting tool reliability, an investigation based on four complementary approaches for tool wear assessment is proposed: the approach 1 is a general failure times approach (statistical reliability based on flank wear threshold hitting times), the approach 2 is based on power consumption monitoring (statistical reliability based on power threshold hitting times), the approach 3 is based on vibration signal analysis (statistical reliability based on vibration threshold hitting times), and the approach 4 is based on the evolution of flank wear for each insert (statistical reliability based on predicted failure times). For this study, 30 identical inserts from a same batch were studied with a CNC lathe in identical turning conditions. As the remaining useful life assessment is the final goal, this study highlight four approaches in order to find out the safest one. The results obtained showed that the approach 1 has too many uncertainties, whereas the approach 2 provides more specific and safer replacement times. The approach 3, in the first hand, highlights the fact that cutting conditions are not exactly identical and, in the second hand, leads to a safe conditional replacement of an insert. Finally, it appeared that the approach 4 allows applying a predictive maintenance strategy.

Fuzzy Reliability Estimation for Cutting Tools

A cutting tool is an important part of machine tools and its reliability influences the total manufacturing effectiveness and stability of machine tools. The paper presents the application of state space model in the cutting tool reliability assessment. As the single evaluation threshold is not easy to determine, the paper puts forward the concept of fuzzy threshold to solve this problem. We use the performance or substitute variable to fuzzify the states of the system and the success/failure events are treated as fuzzy sets. The acoustic emission signal is measured in the test, and wavelet packet (WP) energy extracted from the acoustic emission signal is used to estimate the tool state. The deterioration of the system is seen as a stochastic dynamic process with continuous degrading. The deterioration tendency is predicted by the Kalman filter algorithm, and the corresponding fuzzy reliability is calculated based on the forecasted deterioration state and a pre-set fuzzy threshold. The best time of when the tool should be replaced can be obtained from the decision making model.

Cutting tool reliability analysis for variable feed milling of 17-4PH stainless steel

Variable feed machining has recently been proposed as a significant method to improve cutting tool life particularly for hard and diffucult to machine materials. This method, which is easy to apply in industry, has been shown to improve tool life in the order of 40% in certain cases. This paper presents a reliability model for the quantitative study of the effect of feed variation on tool wear and tool life. To better compare processes with two different wear modes, a reliability model taking simultaneously into account both flank and face wear has been developed. With this model, which is based on experiments, the tool life for the constant and variable feed cases was calculated from the reliability function. The mean time to failure, obtained from the reliability function, provides an accurate evaluation for any probabilistic distribution. The proposed method is therefore a general approach that can be used for analyzing cutting tool life under any conditions and for any equipment and material.

Cutting-tool reliability assessment in variable machining conditions

It is a common industrial practice to use the same cutting tool for different operations and on different part types to minimize cutting-tool change-overs and the number of cutting-tools required, and to increase part-routing flexibility. This paper derives a recursive formula to calculate the cutting-tool reliability in variable conditions if the failure-time distribution of the cutting-tool can be represented by the accelerated failure time model (AFTM). The formulae for the cutting-tool reliability when the processing time for each operation is random are also derived. The unknown parameters in the reliability function can be estimated from cutting-tool life-data obtained under either fixed conditions or variable conditions by using the method of maximum likelihood. Two examples based on real cutting-tool life-data demonstrate the computational results.

Cost of cutting tools and total machining costs as a function of the cutting-tool reliability in automatic flow lines

Abstract This paper explains an approach to establishing the total reliability of cutting tools on feeding automatic machine lines as a function of time, and based on this the establishment of cutting-tool costs and total machining costs as a function of cutting-tool reliability. Based on observations, made over a long period, cutting-tool reliability is established for certain operations (Weibull distribution), and the total reliability for the whole line established as the product of the individual operations. Cutting-tool costs are shown as the sum of tool replacement, sharpening and depreciation costs, and total machining costs as the sum of machining values, machine tools and cutting tools. By variation of the cutting-tool replacement time, the tabular change dependencies are obtained as a function of cutting-tool replacement time. By elimination of replacement time from the above dependencies, the cutting-tool cost changes and machining costs are obtained as a function of the cutting-tool reliability. These could prove valuable in the choice of optimal cutting-tool replacement times.