This study addresses the challenge of modeling flank wear impact on cutting forces in metal cutting. Accurate models are crucial for simulating the cutting process, optimizing insert geometry and monitoring machine tools. The objective is to develop an extended Kienzle-Sağlam force model that considers tool rake angle, uncut chip thickness and tool flank wear. Experimental tests involve orthogonal turning with coated inserts, cutting force measurements with a dynamometer and flank wear progression monitored using an optical measuring robot. By integrating measured cutting forces and flank wear progression, the study extends the mechanistic cutting force model, with flank wear as an input parameter. The proposed model is validated against force measurements, using commercial cutting tools in longitudinal turning conditions. The findings of this study suggest that the developed cutting force model effectively captures the effects of the considered input parameters and accounts for different stages of tool wear. The results also show that the tool flank wear significantly affects the radial and feed force components, which is an important finding potentially affecting the prediction capabilities in future generations of sensor-embedded cutting tools, aiming at tool life monitoring, prediction of tool deflection and cutting process stability.

Sensor-equipped cutting tools are becoming more common in the metal cutting industry as the demand for process monitoring and automation grows. These products are used for monitoring cutting forces and vibrations during machining with the objective of providing valuable insight into tool deflection, tool wear, surface finish, and process stability. The number of sensors and their position in the cutting tool, are often restricted by price and the thermo-mechanical loads acting in the cutting zone. Obtaining accurate measurements is a challenge due to mechanical filtering between the sensor positions and the tool tip as well as due to measurement noise from the sensors and electronics. This paper presents a method to estimate dynamic loads and tool tip vibrations using recorded data from strain sensors in a cutting tool. This is achieved through output-only calibration of an analytical model of the cutting tool, which defines the strain-force relationship based solely on the measured strain response data. This approach provides key parameters, including the first resonance frequency and the damping ratio of the cutting tool. The model is then applied to eliminate unwanted dynamic effects from the measured strain data, enhancing the accuracy of predictions of forces and tool tip displacement.

Sensor-equipped metal cutting tools are one of the branches of Industry 4.0. A particularly interesting application for the sensors is to estimate the cutting forces for ensuring efficient machining and process monitoring. However, due to the extreme pressure and temperature in the cutting zone during machining, sensors such as strain sensors and accelerometers need to be placed away from the cutting zone. The signals measured by the sensors are filtered by the mechanical properties of the cutting tool, making accurate estimation of the cutting forces challenging. This paper presents a method to calculate the residues and poles describing strain-force transfer functions of a cantilever beam with multiple modes, representing a simplified model of a cutting tool. The model is then used in conjunction with inverse filtering to estimate the input force from recorded strain, incorporating the static and dynamic properties of the system. The suggested approach is demonstrated both in simulations and experimental tests with promising results. © 2024 Proceedings of ISMA 2024 - International Conference on Noise and Vibration Engineering and USD 2024 - International Conference on Uncertainty in Structural Dynamics. All rights reserved.

Coolant channels allow internal coolant delivery to the cutting region and significantly improve drilling, but these channels also reduce the torsional and torsional-axial stiffness of the drills. Such a reduction in stiffness can degrade the quality of the drilled holes. The evacuation of cutting chips and the delivery of the cutting fluid put strict geometrical restrictions on the cross-section design of the drill. This necessitates careful selection and optimization of features such as the geometry of the coolant channels. This paper presents a new method that uses Prandtl’s stress function to predict the torsional and torsional-axial stiffness values. Using this method drills with one central channel are compared to those with two eccentric coolant channels, which shows that with the same cross-section area, the reduction of axial and torsional-axial stiffness is notably smaller for the design with two eccentric channels compared to a single central channel. The stress function method is further used to select the appropriate location of the eccentric coolant channels to minimize the loss of torsional and torsional-axial stiffness. These results are verified by compari-son to the results of three-dimensional finite element analyses. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

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In this study, the flow stress behavior of ferritic-pearlitic steel (C45E steel) is investigated through isothermal compression testing at different strain rates (1 s-1, 5 s-1, and 60 s-1) and temperatures ranging from 200 to 700 °C. The stress-strain curves obtained from experimental testing were post-processed to obtain true stress-true plastic strain curves. To fit the experimental data to well-known material models, Johnson-Cook (J-C) model was investigated and found to have a poor fit. Analysis of the flow stress as a function of temperature and strain rate showed that among other deformation mechanisms dynamic strain aging mechanism was active between the temperature range 200 and 400 °C for varying strain rates and J-C model is unable to capture this phenomenon. This lead to the need to modify the J-C model for the material under investigation. Therefore, the original J-C model parameters A, B and n are modified using the polynomial equation to capture its dependence on temperature and strain rate. The results show the ability of the modified J-C model to describe the flow behavior satisfactorily while dynamic strain aging was operative. © 2019 by the authors. Licensee MDPI, Basel, Switzerland.

Boring bars with tuned mass dampers have a passive damper tuned with respect to the frequency of the first bending mode of the tool. When the tool is clamped into the machine tool there is a stiffness loss that lowers the natural frequency of the bar compared to ideal clamping conditions. For large tools the difference can be more than 35%, depending on clamping structure, tool size and overhang. In this paper we investigate a simple two-degree-of-freedom model for the tool-machine interaction consisting of a bending mode coupled with a rotational stiff mode. The model gives good insight into the system behavior and fits well with measurements. © 2019 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the scientific committee of The 17th CIRP Conference on Modelling of Machining Operations

Accurate estimates of cutting forces are important in the evaluation of different cutting tool geometries and concepts. However, dynamic influences from the measurement system affect the result, which can make the obtained cutting force data erroneous and misleading. This article presents a method to obtain an inverse filter which compensates for the dynamic influences of the measurement system. Using this approach, unwanted dynamic effects of the measurement system can be counteracted, making it possible to retain information related to the cutting forces contained in the high frequency region. The advantage of the proposed method is illustrated by comparing simulated, inverse- and low-pass filtered forces to unfiltered forces under different cutting conditions. The results show that inverse filtering increases the usable frequency range of the force dynamometer and thereby provide more reliable results compared to both low-pass and unfiltered forces.

When dealing with nonlinear dynamical systems, it is important to have efficient, accurate and reliable tools for estimating both the linear and nonlinear system parameters from measured data. An approach for nonlinear system identification widely studied in recent years is "Reverse Path". This method is based on broad-band excitation and treats the nonlinear terms as feedback forces acting on an underlying linear system. Parameter estimation is performed in the frequency domain using conventional multiple-input-multiple- output or multiple-input-single-output techniques. This paper presents a generalized approach to apply the method of "Reverse Path" on continuous mechanical systems with multiple nonlinearities. The method requires few spectral calculations and is therefore suitable for use in iterative processes to locate and estimate structural nonlinearities. The proposed method is demonstrated in both simulations and experiments on continuous nonlinear mechanical structures. The results show that the method is effective on both simulated as well as experimental data.

With growing demands on product performance and growing complexity of engineering structures, efficient tools for analyzing their dynamic behavior are essential. Linear techniques are well developed and often utilized. However, sometimes the errors due to linearization are too large to be acceptable, making it necessary to take nonlinear effects into account. In many practical applications it is common and reasonable to assume that the nonlinearities are highly local and thus only affect a limited set of spatial coordinates. The purpose of this paper is to present an approach to finding the spatial location of nonlinearities from measurement data, as this may not always be known beforehand. This information can be used to separate the underlying linear system from the nonlinear parts and create mathematical models for efficient parameter estimation and simulation. The presented approach builds on the reverse-path methodology and utilizes the coherence functions to determine the location of nonlinear elements. A systematic search with Multiple Input/Single Output models is conducted in order to find the nonlinear functions that best describe the nonlinear restoring forces. The obtained results indicate that the presented approach works well for identifying the location of local nonlinearities in structures. It is verified by simulation data from a cantilever beam model with two local nonlinearities and experimental data from a T-beam experimental set-up with a single local nonlinearity. A possible drawback is that a relatively large amount of data is needed. Advantages of the approach are that it only needs a single excitation point that response data at varying force amplitudes is not needed and that no prior information about the underlying linear system is needed.