Self-propelled Rotary Tool Research Articles

Self-Propelled Rotary Tools in Hard Turning: Analysis and Optimization via Finite Element Models.

This study investigates self-propelled rotary tool (SPRT) performance in hard turning using 3D finite element (FE) models. The FE models developed in this study are based on coupled temperature-displacement analysis using an explicit time-integration scheme. The developed FE models can predict chip morphology, cutting forces, tool and workpiece stresses and temperatures. For model verification, hard turning experiments were conducted using an SPRT on AISI 4340 bars. Cutting forces and maximum tool-chip interface temperatures were recorded and compared with the model findings. The effects of different process parameters were analyzed and discussed using the developed FE models. The FE models were run with a central composite design (CCD-25) matrix with four input variables, i.e., the cutting speed, the feed rate, the depth of the cut and the inclination angle. Response surfaces based on the Gaussian process were generated for each performance variable in order to predict design points not available in the original design of the experiment matrix. An optimization study was carried out to minimize tool stress and temperature while setting limits for the material removal rate (MRR) and specific cutting energy for the process. Optimized processes were found with moderate cutting speeds and feed rates and high depths of cut and inclination angles.

Tool Wear Prediction When Machining with Self-Propelled Rotary Tools.

The performance of a self-propelled rotary carbide tool when cutting hardened steel is evaluated in this study. Although various models for evaluating tool wear in traditional (fixed) tools have been introduced and deployed, there have been no efforts in the existing literature to predict the progression of tool wear while employing self-propelled rotary tools. The work-tool geometric relationship and the empirical function are used to build a flank wear model for self-propelled rotary cutting tools. Cutting experiments are conducted on AISI 4340 steel, which has a hardness of 54–56 HRC, at various cutting speeds and feeds. The rate of tool wear is measured at various intervals of time. The constant in the proposed model is obtained using genetic programming. When experimental and predicted flank wear are examined, the established model is found to be competent in estimating the rate of rotary tool flank wear progression.

Numerical and experimental investigation of cutting temperature in turning with a self-propelled rotary tool

This study focuses on the analysis of temperature distribution in a self-propelled rotary insert for dry turning of SKD11 steel both experimentally and numerically using ABAQUS solver. The simulation results showed that the tool temperature increased with increasing the cutting speed, feed rate, and depth of cut, and the self-propelled rotary tool exhibited a considerably lower temperature than that of the one with a fixed cutting edge. The simulation results were experimentally validated by capturing the steady temperature field in the cutting zone with an IR camera. Thanks to the continuous introduction of a fresh part of the cutting edge into the shear region of the self-propelled rotary tool, both simulated and experimental results revealed a large reduction in the tool temperature of more than 170oC at various cutting conditions.

Evaluation of Self-Propelled Rotary Tool in the Machining of Hardened Steel Using Finite Element Models.

This paper presents a model for assessing the performance of self-propelled rotary tool during the processing of hardened steel. A finite element (FE) model has been proposed in this analysis to study the hard turning of AISI 51200 hardened steel using a self-propelled rotary cutting tool. The model is developed by utilizing the explicit coupled temperature displacement analysis in the presence of realistic boundary conditions. This model does not take into account any assumptions regarding the heat partitioning and the tool-workpiece contact area. The model can predict the cutting forces, chip flow, induced stresses, and the generated temperature on the cutting tool and the workpiece. The nodal temperatures and heat flux data from the chip formation analysis are used to achieve steady-state temperatures on the cutting tool in the heat transfer analysis. The model outcomes are compared with reported experimental data and a good agreement has been found.

Study on physical and technological effects of precise turning with self-propelled rotary tool

This study is focused on some physical and technological aspects of a precise turning with Self-Propelled Rotary Tool (SPRT). As part of experiment, the cutting forces, on-line insert run-out and machined surface topography were investigated. Turning tests were carried in the range of variable feeds, depths of cut and cutting speeds for a hardened 41Cr4 steel with the use of a coated carbide round indexable inserts. The effect of cutting conditions on the tool rotation and the dynamics of cutting force signal were evaluated. In particular, changes of cutting forces vs. cutting lengths for different cutting parameters were analyzed in terms of the cutting insert rotation, and Power Spectral Density (PSD) analysis. Moreover, the original method based on cutting force oscillations was employed to estimate the on-line insert run-out. Ultimately, the analysis of a machined surface topography was conducted, considering the interactions between the process inputs and outputs. It was shown that application of high cutting speeds and feeds during SPRT turning can lead to the improvements in surface finish, as well as the stabilization of cutting force values.

An energy-efficient optimization of the hard turning using rotary tool

The turning operation using a self-propelled rotary tool (SPRT) is efficient manufacturing for hard machining. However, optimization-based energy saving of the rotary turning has not presented because of expensive implementation. This study addresses a parameter optimization to enhance the machining rate (MR) and decrease the energy consumption (ET) as well as the machined roughness (R) for a hard turning using SPRT. The process inputs are the inclined angle (α), depth of cut (a), feed rate (f), and cutting speed (V). The hard turning runs were performed using the experimental plan generated by the Taguchi approach. The adaptive neuro-fuzzy inference system (ANFIS) was used to construct the correlations between the process inputs and responses. The analytic hierarchy process technique was adopted to explore the weight values of the outputs, and the optimum solution was obtained utilizing the adaptive simulated annealing. Moreover, an integrative approach using the response surface method and utilizing the desirability approach was employed to select the optimal outcomes and compare with the proposed technique. The findings revealed that the proposed ANFIS models minimize the predictive error in comparison with the traditional one. The accurate weights may help to select reliable optimal results. The optimal values of the α, a, f, and V are 18°, 0.15 mm, 0.40 mm/rev, and 200 mm/min, respectively. Moreover, ET and roughness are decreased by 50.29% and 19.77%, while the MR is enhanced by 33.16%, respectively, as compared to the general process.

Cutting force and surface roughness depend on the tool path used in side milling: an experimental investigation

This paper proposes a method, based on the driven and self-propelled rotary tool cutting processes, using tool path strategies on side milling with a solid end mill to change the process kinematics. The main objective of this work is to evaluate the path’s influence on the cutting forces and surface roughness, and simultaneously the impact of milling parameters (cutting speed—v c , feed—f, and path period—T). A randomized experiment and a Taguchi Method were applied, and as a result of the experiments, the sinusoidal and triangular paths imply lower net forces (45–70%) and can improve surface quality with similar cutting times to the linear path method, as demonstrated by simulations. Mainly, the triangular and sinusoidal paths could increase the effective feed in the perpendicular direction of the programed feed; however, the maximum material thickness removed remains constant. Thus, this increase in feed causes a specific cutting force reduction, and consequently, forces become smaller than those on the linear path. It is possible to improve the surface roughness in comparison to the linear path, a 20–30% reduction, using the alternative paths (sinusoidal and triangular). Minimal cutting forces and surface roughness can be achieved with triangular path (also easier to program), path period T = 60 mm, cutting speed v c = 120 m/min, and feed f = 0.1 mm/rev.

Narzędzia z obrotowymi krawędziami skrawającymi – klasyfikacja i terminologia

Research focuses on unconventional tools with the rotary edges (RET – rotary edges tools) type self-propelled rotary edges tool (SPRET) and driven rotary edges tools (DRET). Based on the analysis, corrected terminology and classification are presented.

難削材加工に適応可能な従動式ロータリミーリング工具の開発

In order to improve milling performance of difficult-to-cut materials, a unique milling cutter with SPRT (Self-Propelled-Rotary-Tool) was developed. Use of slide bearings enables a compact SPRT mechanism, while influence of bearing friction becomes not negligible. To attain self-revolution of a circular insert regardless of the bearing friction, the cutter geometry was optimized. Through face milling experiments of Inconel 718, superior tool wear resistance was verified as compared to the conventional milling without insert rotation. Analytical result of the measured cutting forces also indicated interesting phenomena in SPRT milling.

Multi Response Optimization of Turning Operation with Self-propelled Rotary Tool

The purpose of the study is to determine the cutting performance of self-propelled rotary tool (SPRT) in the turning operation of hardened EN24 steel by optimizing the cutting conditions. Parameters such as horizontal inclination angle of the SPRT, depth of cut, feed rate and spindle speed were chosen while two conflicting factors; surface roughness (Ra) and metal removal rate (rMMR) were decided as performance criteria. Regression model was used to determine the quantitative relationships between the process variables in terms of performance parameters. Then, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Non-dominated Sorting Genetic Algorithm-II (NSGA-II)-TOPSIS Hybrid Model and Goal Programming methods were employed to obtain the optimum conditions. In the analyses, optimization was determined by minimizing the Ra and maximizing the rMMR. Consequently, Goal Programming produced better results among the applied models. Optimum cutting conditions help operators and engineers to make decisions in the turning operations.

Modeling and multi-response optimization of machining performance while turning hardened steel with self-propelled rotary tool

There are many advanced tooling approaches in metal cutting to enhance the cutting tool performance for machining hard-to-cut materials. The self propelled rotary tool (SPRT) is one of the novel approaches to improve the cutting tool performance by providing cutting edge in the form of a disk, which rotates about its principal axis and provides a rest period for the cutting edge to cool and allow engaging a fresh cutting edge with the work piece. This paper aimed to present the cutting performance of SPRT while turning hardened EN24 steel and optimize the machining conditions. Surface roughness (R a) and metal removal rate (r MMR) are considered as machining performance parameters to evaluate, while the horizontal inclination angle of the SPRT, depth of cut, feed rate and spindle speed are considered as process variables. Initially, design of experiments (DOEs) is employed to minimize the number of experiments. For each set of chosen process variables, the machining experiments are conducted on computer numerical control (CNC) lathe to measure the machining responses. Then, the response surface methodology (RSM) is used to establish quantitative relationships for the output responses in terms of the input variables. Analysis of variance (ANOVA) is used to check the adequacy of the model. The influence of input variables on the output responses is also determined. Consequently, these models are formulated as a multi-response optimization problem to minimize the R a and maximize the r MMR simultaneously. Non-dominated sorting genetic algorithm-II (NSGA-II) is used to derive the set of Pareto-optimal solutions. The optimal results obtained through the proposed methodology are also compared with the results of validation experimental runs and good correlation is found between them.

Experimental investigations and development of cutting force model for self-propelled rotary face milling cutter in machining of titanium alloy

In self-propelled rotary tool machining, a circular cutting tool insert is used that continuously rotates about its axis during machining, as the tool is fed into the workpiece. The continuous rotation of the insert allows the insert to cool between engagements and improves tool life. In order to make use of this methodology for rough machining and bulk material removal in machining of aerospace materials, a self-propelled rotary face milling cutter is developed at Defence Research and Development Laboratory, Hyderabad. This cutter was developed to study the influence of inclination angle on the cutting forces generated during machining, and hence the cutter is provided with the provision to have the inclination angle of the insert for 20°, 30°, 40° and 50°. This article discusses the performance of the developed self-propelled rotary face milling cutter in face milling of titanium alloy at different inclination angles. The cutting forces developed in FX, FY and FZ directions are evaluated at different cutting speed, feed, depth of cut and inclination angles. The cutting forces obtained in self-propelled rotary face milling cutter is compared with that of conventional face milling cutter and the results are presented and discussed. Finally, regression models for prediction of cutting forces are developed.

Turning of High-performance Materials with Rotating Indexable Inserts

High-performance materials with excellent heat resistance are necessary to meet future demands on improving the efficiency of energy converting technologies in the field of power plant construction and aviation industry. Nickel base super alloys can meet these demands to a large extent. However, their excellent corrosion resistance and heat resistance as well as hardness and wear resistance have an adverse effect on the machinability with geometrically defined cutting edges. High local thermal and mechanical stress leads to short tool life and long non-productive time for the tool change. Along with a 90% decrease of cutting speed in comparison to conventional steel machining, cutting of nickel base super alloys demands for more efficient machining processes. One attempt to reduce thermal loads of the tool is machining with rotary tools, where a round indexable insert is mounted on a rotating axis. While machining the workpiece, the rotation of the cutting insert constantly exchanges the active cutting edge section. This allows for a better cooling of the temporarily inactive sections. Also tool wear is distributed equally along the circumference instead of using discrete positions only.In this paper two different types of rotary tools, a self-propelled rotary tool (SPRT) and an actively driven rotary tool (ADRT), are presented. In a series of experiments the influence of the modification of process parameters, penetration angle and tool rotation to the characterization of the surface area of the workpiece, stability of the cutting process and economic efficiency was investigated. Finally a process model was developed as a user-oriented guideline for turning the nickel base super alloy Inconel 718 with rotating indexable inserts.

Cutting of Nickel-Based Superalloys with Rotating Indexable Inserts

In this paper the technological basics of machining the nickel-based superalloy Inconel 718 with a self-propelled rotary tool and an actively driven rotary tool are presented. The advantages compared to conventional machining with fixed round indexable inserts are discussed. In a series of experiments the influence of the tool rotation and modification of the process parameters to the chip formation process and characterization of the surface area of the workpiece are investigated. By using a multitasking lathe with a milling spindle further experiments are conducted. Thereby the influence of the direction of the tool rotation, the relative speed between tool and workpiece and the variation of the penetration angles are analysed.

Modeling of tool wear during hard turning with self-propelled rotary tools

In this paper, an attempt is made to evaluate the self-propelled rotary carbide tool performance during machining hardened steel. Although several models were developed and used to evaluate the tool wear in conventional tools, there were no attempts in open literature for modeling the progress of tool wear when using the self-propelled rotary tools. Flank wear model for self-propelled rotary cutting tools is developed based on the work-tool geometric interaction and the empirical function. A set of cutting tests were carried out on the AISI 4340 steel with hardness of 54–56 HRC under different cutting speeds and feeds. The progress of tool wear was recorded under different interval of time. A genetic algorithm was developed to identify the constants in the proposed model. The comparison of measured and predicted flank wear showed that the developed model is capable of predicting the rate of rotary tool flank wear progression.

Autoregressive Spectrum Analysis of Vibration and Condition Monitoring of Self-Propelled Rotary Tool

Self-propelled rotary tools are being rediscovered for their applications in machining of ‘difficult-to-machine’ materials or for general improvement in the productivity of machining operations. The vibration characteristic and the occurrence of chatter during high speed cutting will induce the deterioration of precision and machining surface, tool wear and tool life. This paper deals with the identification of the vibration in SPRT cutting system with AR time series model. The experiment and deduction method provide a sound foundation for improving the structure with high antivibration strength, which could reduce the relative vibration between tool and workpiece in the alloweable scope.

Prediction of cutting force for self-propelled rotary tool using artificial neural networks

In this paper, a cutting force model for self-propelled rotary tool (SPRT) cutting force prediction using artificial neural networks (ANN) has been introduced. The basis of this approach is to train and test the ANN model with cutting force samples of SPRT, from which their neurons relations are gradually extracted out. Then, ANN cutting force model is achieved by obtaining all weights for each layer. The inputs to the model consist of cutting velocity V, feed rate f, depth of cut a p and tool inclination angle λ, while the outputs are composed of thrust force F x , radial force F y and main cutting force F z . It significantly reduces the complexity of modeling for SPRT cutting force, and employs non-structure operator parameters more conveniently. Considering the disadvantages of back propagation (BP) such as the convergence to local minima in the error space, developments have been achieved by applying hybrid of genetic algorithm (GA) and BP algorithm hence improve the performance of the ANN model. Validity and efficiency of the model were verified through a variety of SPRT cutting samples from our experiment tested in the cutting force model. The performance of the hybrid of GA–BP cutting force model is fairly satisfactory.

Prediction of chip flow direction during machining with self-propelled rotary tools

This paper presents a model for chip flow prediction during tube-end machining process using self-propelled rotary tools. The analysis performed is based on the transformation of the relative kinematic relationships in rotary cutting to that of the conventional cutting with large nose radius. Both relative and absolute chip flow angles are investigated. Tests were performed to measure the absolute chip flow angle, insert self propelled motion, and the deformed chip thickness during machining with self-propelled rotary tool under different cutting conditions. The predicted values of the absolute chip flow angle were in good agreement with that measured experimentally.

A model for cutting forces generated during machining with self-propelled rotary tools

In this paper, a force model for self-propelled rotary tool is presented. Conventional oblique cutting force predictions were reviewed and extended to predict the cutting forces generated during machining with the self-propelled rotary tools. The model presented is based on Oxley's analysis and was verified by cutting tests using a typical self-propelled tool. Good agreement was obtained between the predicted and the experimentally measured forces under a wide range of cutting conditions. The effect of different cutting conditions on the friction coefficient along the chip/tool interface and tool rake face normal force were also presented and discussed.

Tool performance and attainable surface quality during the machining of aerospace alloys using self-propelled rotary tools

This paper presents an experimental investigation to evaluate the performance of self-propelled rotary tools and machined surface quality during machining waspaloy and titanium alloys. A new rotary tool design with different insert diameters and material/coatings is utilized. The criteria used in the assessment of tool performance are modes of tool wear and roughness as well as topography of machined surface. The performance of the self-propelled rotary tool is compared to that of other conventional tool designs with the same circular tool as well as cutting angles. The experimental results are used to define the optimum and safe cutting conditions for high performance machining of aerospace material using self-propelled tools.