Chatter vibration and surface location error prediction for helical end mills

Mann, Brian P.; Edes, Ben T.; Easley, Sam J.; Young, Keith A.; Ma, Kong

doi:10.1016/j.ijmachtools.2007.10.003

Cited by 62 publications

(31 citation statements)

References 20 publications

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“…For calculation of surface location error, there exist the numerical method [12], the frequency domain method [56], the TFEA method [16,57,58] and the harmonic balance method [59]. It is worth noting that the TFEA method can be used for simultaneous prediction of milling stability and SLE [58].…”

Section: Machining Error Calculation Methodsmentioning

confidence: 99%

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On time-domain methods for milling stability analysis

Ding

Zhu

2012

Chin. Sci. Bull.

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As a basic and advanced machining technique, the high-speed milling process plays an important role in realizing the goal of high performance manufacturing. From the viewpoint of machining dynamics, obtaining chatter-free machining parameters is a prerequisite to guaranteeing machining accuracy and improving machining efficiency. This paper gives an overview on recent progress in time domain semi-analytical methods for chatter stability analysis of milling processes. The state of art methods of milling stability prediction in milling processes and their applications are introduced in detail. The bottlenecks involved are analyzed, and potential solutions are discussed. Finally, a brief prospect on future works is presented. High speed milling is widely utilized in manufacturing of complex surfaces for the fields of aerospace, ship, automotive, dies and molds etc., due to its advantage of obtaining high machining accuracy and high material removal rate with keeping low-amplitude cutting forces. Regarding to modeling of machining processes, the research topics on high speed milling can be categorized as: tool path planning, machining dynamics and machining physical modeling. Tool path planning is to plan the tool path according to the workpiece model, machining strategy and required machined error [1][2][3][4][5]. From the viewpoint of machining dynamics, the relative vibration between the workpiece and cutter in the milling process is the main reason of reducing product surface quality and limiting the production efficiency. To suppress the vibration impact by optimizing the machining parameters, the following two questions need to be addressed.(1) Stability analysis based on the dynamics of milling processes. As far as chatter vibrations are concerned, there are four different mechanisms: regeneration [6], mode coupling [7], friction [8] and thermo-mechanics of chip formation [9]. In milling processes, regenerative chatter is the most common form of self-excited vibration to reduce surface quality and machining efficiency [10,11]. The works on analysis of the stability of milling processes focus on calculating the stability boundary of the machining parameters based on the dynamic models characterizing the milling processes.(2) Machining accuracy analysis on the basis of stability analysis. Due to forced vibrations in milling processes, chatter-free machining parameters cannot ensure high performance machining. Vibration-induced surface errors can be classified as surface location error (SLE) [12] and surface roughness [13]. It is essential to take the stability and dynamical errors into account in machining optimization models to achieve high performance milling.

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Section: Machining Error Calculation Methodsmentioning

confidence: 99%

“…It is worth noting that the TFEA method can be used for simultaneous prediction of milling stability and SLE [58]. It is much efficient than other methods, since the fixed point technique is employed to calculate the SLE.…”

Section: Machining Error Calculation Methodsmentioning

confidence: 99%

On time-domain methods for milling stability analysis

Ding

Zhu

2012

Chin. Sci. Bull.

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“…This method is considered to be a stratified sampling technique that provides an efficient way to sample random variables from their entire distributions. LHS has been applied to a wide range of probabilistic analysis problems, ranging from estimation of reliability (probability of failure), coefficient estimation for polynomial chaos, neural network, and other types of surrogate (Chojaczyk et al, 2015;Olsson et al, 2003). In the present study, LHS scheme is employed to generate random samples.…”

Section: Training Data Generationmentioning

confidence: 99%

“…Mann et al(2005) proposed an approach for simultaneous prediction of SLE in milling using Temporal Finite Element Analysis (TFEA). This method was then generalized for helical end mills (Mann et al, 2008). Schmitz and Mann (2006) presented an analytical method to compute SLE based on frequency domain and harmonic balance analysis.…”

Section: Introductionmentioning

confidence: 99%

Prediction of surface location error in milling considering the effects of uncertain factors

et al. 2017

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Abstract. Machining accuracy of a milled surface is influenced by process dynamics. Surface location error (SLE) in milling determines final dimensional accuracy of the finished surface. Therefore, it is critical to predict, control, and minimize SLE. In traditional methods, the effects of uncertain factors are usually ignored during prediction of SLE, and this would tend to generate estimation errors. In order to solve this problem, this paper presents methods for probabilistic analysis of SLE in milling. A dynamic model for milling process is built to determine relationship between SLE and cutting parameters using full-discretization method (FDM). Monte-Carlo simulation (MCS) method and artificial neural network (ANN) based MCS method are proposed for predicting reliability of the milling process. Finally, a numerical example is used to evaluate the accuracy and efficiency of the proposed method.

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“…The geometrical accuracy of the machined surface is influenced by the process parameters as well as tool oscillations. Since surface accuracy is a measure of machining performance, various literatures are devoted to the investigation of surface location error (SLE) for the stable cutting conditions [17][18][19][20][21][22][23]. Bachrathy et al [23] investigated surface properties based on the helical fluted tool model and introduced surface error parameters for the stable (forced) motion of the tool.…”

Section: Introductionmentioning

confidence: 99%

Chaotic vibrations in high-speed milling

Banihasan

Bakhtiari-Nejad

2011

Nonlinear Dyn

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A large number of literatures are devoted to the stability of the milling process and various control methods for chatter suppression. But chaotic dynamics beyond the stable region has not been considered extensively. Moreover, modeling issues for chaotic motion need more challenge for accurate prediction of its complex dynamical behavior. This paper presents a detailed two-degree-of-freedom mechanics based model for the study of chaotic vibrations in milling. Segmental multiple regenerative effect that is the principle feature of nonlinear vibrations in milling processes besides two state dependent time delays has been considered. Exact geometrical formulation of multiple regenerative effects by considering simultaneously different numbers of delayed tool positions over the cutting zone is presented for the first time. Phase portrait, bifurcation diagram, largest Lyapunov exponent, and surface profile were calculated for a given machine tool and workpiece parameters. The simulation results show positive values of the largest Lyapunov exponent corresponding to the existence of chaos in high-speed milling operations. Also, investigation of

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Chatter vibration and surface location error prediction for helical end mills

Cited by 62 publications

References 20 publications

On time-domain methods for milling stability analysis

On time-domain methods for milling stability analysis

Prediction of surface location error in milling considering the effects of uncertain factors

Chaotic vibrations in high-speed milling

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