Modeling micro-end-milling operations. Part I: analytical cutting force model

A new analytical cutting force model is proposed for micro-end-milling operations. The model calculates the chip thickness by considering the trajectory of the tool tip while the tool rotates and moves ahead continuously. The proposed approach allows the calculation of the cutting forces to be done accurately in typical micro-end-milling operations with very aggressively selected feed per tooth to tool radius (f_t/r) ratio. The difference of the simulated cutting forces between the proposed and conventional models can be experienced when f_t/r is larger than 0.1. The estimated cutting force profile of the proposed model had good agreement with the experimental data.     

Modeling micro-end-milling operations. Part III: influence of tool wear

The characteristics of the cutting forces were studied at different usage levels and the analytical model of the micro-end-milling operations was modified to represent the tool wear. A new expression was derived from the model to estimate the remaining tool life from experimental data. The parameters of the model are estimated by using genetic algorithms. The difference between the simulated and experimental cutting force profiles for new and worn tools was less than 8%. The remaining tool life was estimated with typically 10% error from the experimental data. Maximum error was 20%. The introduced analytical model and genetic algorithm-based parameter estimation approach is very convenient for on-line tool wear monitoring without extensive experimental study.     

Genetic tool monitor (GTM) for micro-end-milling operations

Almost all existing tool condition monitoring methods require either the critical parameters of models which are experimentally found or the self-learning algorithms that are trained with existing data. Genetic Tool Monitor (GTM) is proposed to identify the problems by using an analytical model for micro-end-milling operations and genetic algorithm. The current version of the GTM is capable to monitor the micro-end-milling operations without any previous experience and is able to estimate symmetrical wear and local damages at the cutting edges of a tool. Genetic algorithms (GA) are found as a promising health monitoring tool if an expression exists and the necessary computational time is allowable in that particular application. GTM generates meaningful information about the ongoing operation and allows the establishment of rules based on the operators' experience.     

Tool wear estimation in micro-machining.: Part II: neural-network-based periodic inspector for non-metals

The relationship between the cutting force characteristics and tool usage (wear) in a micro-end-milling operation was studied for two different metals. Neural-network-based usage estimation methods are proposed that use force-variation- and segmental-averaging-based encoding techniques.     

Tool wear estimation in micro-machining.: Part I: tool usage–cutting force relationship

The relationship between the cutting force characteristics and tool usage (wear) in a micro-end-milling operation was studied for two different metals. Neural-network-based usage estimation methods are proposed that use force-variation- and segmental-averaging-based encoding techniques.     

Prediction of micro-milling forces with finite element method

This paper presents the prediction of micro-milling forces using cutting force coefficients evaluated from the finite element (FE) simulations. First an FE model of orthogonal micro-cutting with a round cutting edge is developed for Brass 260. The simulated cutting forces are compared against the experimental results obtained from turning tests. The cutting force coefficients are identified from a series of FE simulations at a range of cutting edge radii and chip loads. The identified cutting force coefficients are used to simulate micro-milling forces considering the tool trajectory, run-out and the dynamometer dynamics. The same process is also simulated with a slip-line field based model. FE and slip-line field based simulation results are compared against the experimentally measured turning and micro-milling forces.     

Measurement of quasi-mean resultant force using the vibrational signal of spindle in milling

The quasi-mean resultant force has been proven to be useful on the real-time process control and tool monitoring in milling operations. This paper presents a new way to measure the quasi-mean resultant force using the vibrational displacement signal of spindle. The quasi-mean resultant force can be obtained by subtracting the spindle run-out pattern from the average displacement signal per tooth period, then multiplying a constant, k^*. This new approach is illustrated by computational simulations and experimental cutting tests.     

Investigation of Cutting Characteristics in Side-milling a Multi-thread Worm Shaft on Automatic Lathe

This paper investigates the cutting characteristics of side-milling which is proposed as a more efficient way to manufacture worms of higher accuracy than form-threading and planetary milling. A tool-tip trajectory based on the tool-workpiece interaction is modelled in terms of matrix transformation. Chip thickness, cutting force and surface roughness are simulated using the calculated tool-tip trajectories. The effects of various errors in the real cutting such as run-out errors of a tool axis, tool setup errors and workpiece deflection due to cutting forces are investigated. The simulation results are verified through numerous experiments on an automatic lathe.     

Compensation of progressive radial run-out in face-milling by spindle speed variation

This paper investigates the use of spindle speed variation to compensate for progressive radial run-out in the face-milling process. Machine setup errors like spindle axis tilt, cutter axis tilt and cutter center offset result in radial and axial run-out on the inserts. Cutter center offset, in particular, results in progressive radial run-out on the inserts which can be compensated by continuously varying the spindle speed in a sinusoidal pattern. The amplitude and phase of the sinusoidal trajectory significantly influence the capability of this technique for run-out compensation. A method is proposed for selection of optimal values of the speed variation amplitude and phase based on the idea of matching the chip load pattern under variable speed machining conditions in the presence of progressive radial run-out with that of constant speed machining in the absence of any run-out. Experiments performed with optimal values of the speed variation parameters show a significant reduction in the cutting force component at the spindle frequency and a shift in the frequency content of cutting force from the harmonics of the spindle frequency to those of the tooth passing frequency. An industrial implementation strategy of the proposed scheme is also presented that integrates run-out estimation with its subsequent compensation.     

A new model for the prediction of cutting forces in micro-end-milling operations

In this work an analytical forces model for real micro-end-milling is developed by regarding the main factors which have influence on the process. The run-out or eccentric deviation of the tool path is taken into account as well as the tool deflection. A linear equation system has to be solved to obtain the forces, so it requires a low computational cost. Size effect is also considered since the chip thickness is comparable to the edge radius and therefore there is chip removal only when it is higher than a certain value. This phenomenon causes variation in the entry and exit angles of the tool in the workpiece. These factors have already been studied in conventional milling. However, since they have not been yet considered for micromilling, the validity of mechanistic models is limited. The model has been developed for two different types of side micromilling: up milling and down milling. Experimental results carried out on Steel and Aluminum show a good correlation with the model. The forces model proposed in this work can be used in a process monitoring in real time as well as in adaptive control of the process.     

Development of micro milling force model and cutting parameter optimization

Taking the minimum chip thickness effect,cutter deflection,and spindle run-out into account,a micro milling force model and a method to determine the optimal micro milling parameters were developed.The micro milling force model was derived as a function of the cutting coefficients and the instantaneous projected cutting area that was determined based on the machining parameters and the rotation trajectory of the cutter edges.When an allowable micro cutter deflection is defined,the maximum allowable cutting force can be determined.The optimal machining parameters can then be computed based on the cutting force model for better machining efficiency and accuracy.To verify the proposed cutting force model and the method to determine the optimal cutting parameters,micro-milling experiments were conducted,and the results show the feasibility and effectiveness of the model and method.     

A study on initial contact detection for precision micro-mold and surface generation of vertical side walls in micromachining

The surface quality and the dimensional accuracy are important criteria for micro-mold production, specially for micro-fluidic devices. Important cutting parameters that affect the quality of vertical side walls created by the peripheral cutting edge in micro-end-milling operations were identified. Surface roughness and form error were used to define the quality of side walls on stainless steel and aluminum workpieces. An acoustic emission sensor was used to detect initial contact between a tool and a workpiece for higher dimensional accuracy where the referencing is a critical element for precision micromachining feature creation.     

Study of milling cutting force pulsation applied to the detection of tool breakage

A study of the cutting force pulsation due to tool breakage is presented. Monitoring algorithms extracting the cutting force signal changes caused by tool breakage and further processing the extracted cutting force signal to recognize tool breakage are proposed. Theoretical studies and experimental results performed in milling operations have proven the feasibility of the algorithms proposed.     

Micro-end-milling of single-crystal silicon

Ductile-regime machining of silicon using micro-end-mill is almost impossible because of the brittle properties of silicon, crystal orientation effects, edge radius of the cutter and the hardness of tool materials. Micro-end-milling can potentially be used to create desired three dimensional (3D) free form surface features using the ductile machining technology for single-crystal silicon. There is still a lack of fundamental understanding of micro-end-milling of single-crystal silicon using diamond-coated tool, specifically basic understanding of material removal mechanism, cutting forces and machined surface integrity in micro-scale machining of silicon. In this paper, further research to understand the chip formation mechanism was conducted. An analysis was performed to discover how the chips are removed during the milling process. Brittle and ductile cutting regimes corresponding to machined surfaces and chips are discussed. Experiments have shown that single-crystal silicon can be ductile machined using micro-end-milling process. Forces generated when micro-end-milling single-crystal silicon are used to determine the performance of the milling process. Experimental results show that the dependence of the cutting force on the uncut chip thickness can be well described by a polynomial function order n. As cutting regime becomes more brittle, the cutting force has more complex function.     

A worn tool force model for three-dimensional cutting operations

Previous studies have shown that there is a region on the flank of a worn cutting tool where plastic flow of the workpiece material occurs. This paper presents experimental data which shows that in three-dimensional cutting operations in which the nose of the tool is engaged, the region of plastic flow grows linearly with increases in total wearland width. A piecewise linear model is developed for modeling the growth of the plastic flow region, and the model is shown to be independent of cutting conditions. A worn tool force model for three-dimensional cutting operations that uses this concept is presented. The model requires a minimal number of sharp tool tests and only one worn tool test. An integral part of the worn tool force model is a contact model that is used to obtain the magnitude of the stresses on the flank of the tool. The force model is validated through comparison to data obtained from wear tests conducted over a range of cutting conditions and workpiece materials. It is also shown that for a given tool and workpiece material combination, the incremental increases in the cutting forces due to tool flank wear are solely a function of the amount and nature of the wear and are independent of the cutting condition in which the tool wear was produced.     

Sensing tool breakage in face milling with a neural network

A new approach using a neural network to process the features of the cutting force signal for the recognition of tool breakage in face milling is proposed. The cutting force signal is first compressed by averaging the cutting force signal per tooth. Then, the average cutting force signal is passed through a median filter to extract the features of the cutting force signal due to tool breakage. With the back propagation training process, the neural network memorizes the feature difference of the cutting force signal between with and without tool breakage. As a result, the neural network can be used to classify the cutting force signal with or without tool breakage. Experiments show this new approach can sense tool breakage in a wide range of face milling operations.     

Dynamic response analysis in end milling using pre-twisted beam finite elements

This paper develops an analytical model for estimating the dynamic responses in end milling, i.e. dynamic milling cutter deflections and cutting forces, by using the finite-element method along with an adequate end milling-cutting force model. The whole cutting system includes the spindle, the bearings and the cutter. The spindle is modelled structurally with the Timoshenko-beam element, the milling cutter with the pre-twisted Timoshenko-beam element due to its special geometry, and the bearings with lumped springs and dampers. Because the damping matrix in the resulting finite-element equation of motion for the whole cutting system is not one of proportional damping due to the presence of bearing damping, the state-vector approach and the convolution integral is used to find the solution of the equation of motion. To assure the accuracy of prediction of the dynamic response, the associated cutting force model should be sufficiently precise. Since the dynamic cutting force is proportional to the chip thickness, a quite accurate alogorithm for the calculation of the variation of the chip thickness due to geometry, run-out and spindle-tool viration is developed. A number of dynamic cutting forces and tool deflections obtained from the present model for various cutting conditions are compared with the experimental and analytical results available in the literature, good agreement being demonstrated for these comparisons. The present model is useful, therefore, for the prediction of end milling instability. Also, the tool deflections obtained using the pre-twisted beam element are found to be smaller than those obtained using the straight beam element without pre-twist angle. Hence neglecting the pre-twist angle in the structural model of the milling cutter may overestimate the tool deflections.     

The shape characteristic detection of tool breakage in milling operations

Detection of tool failure is very important in automated manufacturing. All previously developed tool breakage detection approaches in milling operations have adopted the strategy of parameter detection in which the detection of tool breakage was carried out according to values of specific parameters selected to reflect tool state (with or without tool breakage). In this paper the new concept of shape characteristic detection of tool breakage in milling operations is proposed. The detection of tool breakage is conducted according to the shape characteristics of discrete dyadic wavelet decomposition of cutting force. By means of the proposed method, the influence caused by the variation of cutting parameters and transients is eliminated. The proposed method is conducted in two steps. In the first step, cutting force signals are decomposed by discrete dyadic wavelet, with the shape characteristic vectors then being generated by the proposed shape characteristic vector-generating algorithm. In the second step, the shape characteristic vectors are fast classified by the ART2 neural networks. The accuracy and effectiveness of the proposed method are verified by numerous experiments.     

Modeling of dynamic micro-milling cutting forces

This paper investigates the mechanistic modeling of micro-milling forces, with consideration of the effects of ploughing, elastic recovery, run-out, and dynamics. A ploughing force model that takes the effect of elastic recovery into account is developed based on the interference volume between the tool and the workpiece. The elastic recovery is identified with experimental scratch tests using a conical indenter. The dynamics at the tool tip is indirectly identified by performing receptance coupling analysis through the mathematical coupling of the experimental dynamics with the analytical dynamics. The model is validated through micro end milling experiments for a wide range of cutting conditions.     

A three-dimensional analytical cutting force model for micro end milling operation

In the present day manufacturing arena one of the most important fields of interest lies in the manufacturing of miniaturized components. End milling with fine-grained carbide micro end mills could be an efficient and economical means for medium and small lot production of micro components. Analysis of the cutting force in micro end milling plays a vital role in characterizing the cutting process, in estimating the tool life and in optimizing the process. A new approach to analytical three-dimensional cutting force modeling has been introduced in this paper. The model determines the theoretical chip area at any specific angular position of the tool cutting edge by considering the geometry of the path of the cutting edge and relates this with tangential cutting force. A greater proportion of the helix face of the cutter participating in the cutting process differs the cutting force profile in micro end milling operations a bit from that in conventional end milling operations. This is because of the reason that the depth-of-cut to tool diameter ratio is much higher in micro end milling than the conventional one. The analytical cutting force expressions developed in this model have been simulated for a set of cutting conditions and are found to be well in harmony with experimental results.