Minor Flank Wear Research Articles

Machining mechanism in pulsed magnetic treatment for micro-tools

A new tool strengthening method for micro-tools using pulsed magnetic treatment has been experimentally investigated. Compared with the conventional tool strengthening method, the pulsed magnetic treatment of micro-tools enables effectively reduce tool wear both by improving the mechanical properties of the tool material and changing the tool-chip contact friction mechanism which results in efficient chip removal and good surface quality. On account of this method, the untreated and treated micro-tools and three different magnetic properties of ferromagnetic, paramagnetic, and diamagnetic workpiece materials were used to perform comparative cutting experiments. The tool wear, cutting force, and surface roughness were measured to quantitatively investigate the influence of magnetic treatment on the micro-cutting process. Results showed that wear resistance of micro-tools could be improved when machining ferromagnetic and paramagnetic materials, of which the minor flank wear could be reduced by up to 56%. However, the tool wear increased when machining the diamagnetic materials. On the basis of relationship between micro-tool, micro-chip, and workpiece, the machining mechanism is analyzed in detail in pulsed magnetic treatment for micro-tools.

Tool wear performance and surface integrity studies for milling DD5 Ni-based single crystal superalloy

Based on the results of slot milling experiments on the DD5 Ni-based single crystal superalloy (001) crystal plane along the [110] crystal direction, in this paper, efforts were devoted to investigate the tool wear process, wear mechanism and failure modes of the physical vapor deposition (PVD)-AlTiN and TiAlN coated tools under dry milling and water-based minimum quantity lubrication (MQL) conditions. The scanning electron microscope (SEM) morphological observation and energy dispersive X-ray spectroscopy (EDX) elements analysis methods were adopted. Moreover, under the water-based MQL condition, the surface integrity such as surface roughness, dimensional and shape accuracy, microhardness and microstructure alteration were researched. The results demonstrated that the tool edge severe adhesion with the work material, induced by the high Al content in the PVD-AlTiN coating caused the catastrophic tool tip fracture. In contrast, the PVD-TiAlN tool displayed a steady and uniform minor flank wear, even though the material peeling and slight chipping also occurred in the final stage. In addition, due to the high effective cooling and lubricating actions of the water-based MQL method, the PVD-TiAlN coated tool demonstrated intact tip geometry; consequently it could be repaired and reused even if the failure criterion was attained. Moreover, as the accumulative milling length and the tool wear increased, all indicators of the surface integrity forehand were deteriorated.

Wear characteristics of polycrystalline diamond tools in orthogonal cutting of CFRP/Ti stacks

CFRP/Ti stacks have become a viable alternative to conventional composite laminates and metal alloys in various aerospace applications because of their enhanced mechanical properties and improved structural functions. Machining these multilayer stacks with acceptable quality still remains a great challenge for the modern manufacturing sectors due to the ineffective management of the tool wear performance resulting from the varying properties of the stacked constituents. This paper describes, on a fundamental basis, the wear characteristics of polycrystalline diamond (PCD) tipped tools during the orthogonal cutting of CFRP/Ti stacks. Two cutting sequence strategies, i.e., cutting from CFRP to Ti and cutting from Ti to CFRP, were implemented throughout the cutting tests. The experimental results confirm the predominance of the cutting sequence strategy in affecting the CFRP/Ti chip separation and the machined surface quality. The chip adhesion is a most influential factor leading to the disparate influences of the two cutting sequence strategies on the CFRP/Ti cutting responses. The PCD tool suffers severe crater wear due to the Ti phase cutting, while it undergoes minor flank wear owing to its superior wear resistance against abrasive carbon fibers. The wear signatures on the tool-chip contact zone via the scanning electron microscope (SEM) observation reveal that the Ti phase cutting dominates the formation of the tool crater wear land. The edge chipping occurs mainly due to the sudden force variation in the CFRP/Ti interface machining and the inherent brittleness of the PCD material. The fiber orientation seems to have a great impact on the wear behavior of utilized PCD tools by altering the tool-chip contact length.

Influence of Pulsed Magnetic Treatment on Wear of Carbide Micro-end-Mill

This study is carried out to investigate the influence of pulsed magnetic treatment on wear of carbide micro-end-mill. To analyze the friction behavior of micro-end-mill with workpiece, the special micro-end-mill with a chisel is fabricated and used in micro-milling experiments. A paramagnetic material aluminum alloy is employed as workpiece material. The experimental results indicated 17% and 27 % reductions in maximum minor flank wear width and chisel edge wear area of micro-end-mill after pulsed magnetic treatment, respectively. However, the surface roughness and morphology of machined aluminum alloy have no obvious changes with or without pulsed magnetic treatment. Consequently, the reduction of tool wear during milling aluminum alloy can be mainly attributed to the improvement of mechanical properties of carbide tool materials after pulsed magnetic treatment.

Experimental Study on High-Speed Turning of Free-Cutting Steel AISI 12L14 Using Multi-Layer Coated Carbide Tools

AISI 12L14 as a typical free-cutting steel has been widely employed in machinery, energy and metallurgy fields due to its excellent machinability. This research was concerned with the experimental investigation on high-speed turning of AISI 12L14 in terms of cutting force and tool wear with multi-layer (Al2O3/TiCN) CVD coated carbide tool. Results showed that: Depth of cut ap had the dominant effect on the main cutting force, and feed rate f followed. Increase of cutting speed vc was observed to decrease the turning forces. Optimal factor level combination (vc=500m/min, f=0.05mm/r and ap=0.5mm) was obtained through the method of extremum difference analysis. The cutting tool was observed to form sulfide lubricant zone along its rake and flank faces. Ascribed to the presence of sulfide lubricant zone the tool can obtain excellent protection and minor flank wear in the entire turning process. Crater wear was observed occurring on tool rake face and no BUE was found along the cutting edge. In addition, tool flank face suffered abrasive wear and adhesive wear.

Tool Wear Length Estimation with a Self-Learning Fuzzy Inference Algorithm in Finish Milling

The geometric accuracy and surface roughness are mainly affected by the flank wear at the minor cutting edge in finish machining. A genetic algorithm-based fuzzy estimator obtained by a fuzzy inference algorithm to evaluate the minor flank wear length in finish milling is introduced. The fuzzy inference rules are trained by genetic algorithms (GA) through practice. Fuzzy membership functions and rules are usually decided upon subjectively. In this paper, the performance of the fuzzy estimator may be improved if the fuzzy inference model is supplemented by a genetic-based learning mechanism. The features sensitive to minor flank wear are extracted from the dispersion analysis of a time series AR model of the feed directional acceleration of the spindle housing. Linguistic rules for fuzzy estimation are constructed using these features, and then fuzzy inferences are carried out with test data sets under various cutting conditions. The proposed system turns out to be effective for estimating minor flank wear length, and its mean error is less than 13%.

In-process Evaluation of the Overall Machining Performance in Finish-Turning via Single Data Source

Sensor fusion often uses multiple sensors to evaluate a single quantity. The work presented in this paper attempts to use information from a single sensor to estimate overall machining performance (characterized by cutting forces, chip breakability, surface roughness, and dimensional deviation due to tool wear). In particular, the performance is aimed at reflecting the in-process changes of the above-named quantities with respect to tool wear progression (major flank, crater and minor flank wear). 3-D cutting force measured by a tool dynamometer is fully utilized by aggregating multivariate time series models and neural network techniques. Dispersion analysis is used to extract signal features which correlate well with progressive tool wear. The results have shown the effectiveness of the proposed method which also has the obvious merit of simplicity.

Machinability Parameters in Finish Face Milling of Low Alloy Cr-Ni Steel with THR K30 Carbide Tool Part I: Cutting Forces, Specific Cutting Energy and Temperatures.(Dept.M)

It is necessary to ware of the surface alterations that can be produced by grinding operations. This work deals with finish face milling of low alloy steal in its hardness conditions with view to replace surface grinding. This paper is the first of two dealing with the use of submicron grain cemented carbide with low percentage of cubic cabides of 2%. Three major machinability parameters were investigated; cutting force, specific cutting conditions and the minor flank wear on the machinability parameters are investigated. Further, the behaviour of shear angle and normal and shear stresses as well as contact condition on the minor cutting edge were examined. The THR K30 tools were found to be capable of operating at cutting speed up to 176 m/min. Forces with the THR tools are relatively lower than TTM tools at higher cutting speeds. It was also found that the cutting ratio is almost constant at worn minor flank wear of value between 50 to 200 µm. The substantial increase in vertical component Fz, was attributed to the low coefficient of friction of approximate value of 0.4. Descripancies of the findings of the calculated temperatures are also discussed. The specific cutting energy was found to be a constant value of order 2 to 2.5 GJ/m3 at high speeds and feeds respectively. This proved that the finish face milling with THR K30 could be substituted for a vertical spindle surface grinding when judged on the basis of specific cutting energy.

Machinability Parameters in Finish Face Milling of Low Alloy Cr-Ni Steel with THR K30 Carbide Tool Part II:Surface Finish, Machined Surface. Texture, Minor Cutting Edge and Nature of Chips.(Dept.M)

The second contribution presents the results of finish face milling in which the performance of THR K30 reported in terms of surface roughness and machined surface alterations when a low alloy steel in its hardened conditions was milled. The assessment of surface finish and the mechanisms involved in particular front and back cutting were defined. Details are given corresponding to the geometry of tool, elastic deformation and feed marks transfered to surface during front curling. Also, in back cutting, the surface refining by burnishing p rocess on the trailing end culling edge was comprehensively explained. The effect of minor flank wear width on surface refining has been studied. Based on the findings, the THR K30 tool gave the least surface roughness value and the brightest surface. The surface roughness values could be the determining factor and provide the necessary inforamtions in a decession to change from surface grinding to face milling.

Experimental investigation of overall machining performance with overall progressive tool wear at different tool faces

In viewing present machining theories, the machinability database and a great number of research papers on the analysis and prediction of machining performance, including surface roughness, cutting forces and chip breakability, almost all of them assume an ideal machining condition, i.e. machining with unworn cutting tools. However, the tool wear formed at different tool faces alters the original tool configuration and thus may result in unexpected machining performance. A detailed experimental analysis of the variations of the overall machining performance with overall progressive major flank wear, crater wear, minor flank wear, nose wear and groove wear at the minor cutting edge is described in this paper. The results are expected to provide a better understanding about the complex interrelationship between the overall machining performance with the progressive development of overall tool wear at different tool faces, and thus a more realistic optimization of machining operations may be achieved.

Estimation of tool wear length in finish milling using a fuzzy inference algorithm

The geometric accuracy and surface roughness are mainly affected by the flank wear at the minor cutting edge in finish machining. A fuzzy estimator obtained by a fuzzy inference algorithm with a max-min composition rule to evaluate the minor flank wear length in finish milling is introduced. The features sensitive to minor flank wear are extracted from the dispersion analysis of a time series AR model of the feed directional acceleration of the spindle housing. Linguistic rules for fuzzy estimation are constructed using these features, and then fuzzy inferences are carried out with test data sets under various cutting conditions. The proposed system turns out to be effective for estimating minor flank wear length, and its mean error is less than 12%.

Assessment of chip forming patterns with tool wear progression in machining via neural networks

This paper presents a new method of employing techniques of neural networks to quantify the complicated interrelationship between the change of chip breakability and that of comprehensive wear states, including major flank, crater and minor flank wear. Chip breakability under unworn cutting tools is first predicted through a fuzzy rating system, then updated dynamically as tool wear develops. Change in surface finish with tool wear progression is assessed via the neural networks and finish conditions were used where both chip breakability and surface finish are primary concerns. Both training and testing results show that the method is not only valid and effective, but also provides a feasible means for in-process prediction of chip breakability and surface finish in automated finish-machining systems.

Modelling of multivariate time series for tool wear estimation in finish-turning

In finish-turning, the traditional flank or crater wear estimation alone is no longer adequate, whilst the wear at the minor cutting edge is of primary concern since it directly affects the surface quality and dimensional accuracy of a finished product. This paper describes the development of an overall tool wear monitoring strategy in finish-turning. To estimate various types of wear developing at the different faces of a tool insert, multidimensional force and vibration signals are used, and a stochastic technique, based on multivariate autoregressive moving average vector models (ARMAV), is used to quantify the process dynamics embedded in the signals. Based on that, a dispersion analysis is carried out to discriminate among signal ingredients each of which is sensitive to a particular type of wear. Experimental results show that the groove wear at the minor cutting edge, once formed, dominates the finishing-tool life, while in the case of no groove formation at the minor cutting edge, the minor flank wear reaches its critical point earlier than the major flank or crater wear does. The results also show that the method derived from the dispersion analysis is a feasible approach to on-line tool wear estimation in finish-turning.

Comprehensive Tool Wear Estimation in Finish-Machining via Multivariate Time-Series Analysis of 3-D Cutting Forces

Summary In finish-machining, geometric accuracy and surface quality are adversely affected by the tool wear at the minor flank and nose area. This paper describes an investigation into “comprehensive” tool wear estimation, including flank-, crater-. Minor flank-, and nose-wear, based on an analysis of dynamic cutting force in oblique machining. The force, measured in terms of its three orthogonal components, was used to develop trivariate Autoregressive Moving Average Vector (ARMAV) time series models. Based on these, dispersion analysis (DA) was used to extract features sensitive to the rate of various types of wear. The results show that minor flank wear reaches a critical value first in finish-machining, so that optimum cutting conditions or an appropriate tool change strategy must be determined on the basis of minor flank wear. The results also show that the method is a feasible means for on-line tool wear monitoring in finish-machining.