Influence of Flank Wear on the Microstructure Characteristics of the GH4169 Metamorphic Layer under High-Pressure Cooling

Since the flank has an important influence on the surface of a workpiece, and as microstructure flaws of the surface metamorphic layer are a key factor that affects the service performance of a part, this work studied the influence of flank wear on the microstructure characteristics of the metamorphic layer under the conditions of high-pressure cooling. First, Third Wave AdvantEdge was used to create a simulation model of cutting GH4169 using tools with different flank wears under high-pressure cooling. The simulation findings emphasized the impact of flank wear width (VB) on the cutting force, cutting temperature, plastic strain, and strain rate. Second, an experimental platform was established for cutting GH4169 under high-pressure cooling, and the cutting force during the machining process was recorded in real time and compared with the simulation results. Finally, an optical microscope was used to observe the metallographic structure of the GH4169 workpiece section. The microstructure characteristics of the workpiece were analyzed using a scanning electron microscope (SEM) and electron backscattered diffraction (EBSD). It was discovered that, as the flank wear width increased, so did the cutting force, cutting temperature, plastic strain, strain rate, and plastic deformation depth. The relative error between the simulation results of the cutting force and the experimental results was within 15%. At the same time, near the surface of the workpiece, there was a metamorphic layer with fuzzy grain boundaries and refined grain. With an increase in flank wear width, the thickness of the metamorphic layer increased from 4.5 μm to 8.7 μm and the grain refinement intensified. The high strain rate promoted recrystallization, which caused an increase in the average grain boundary misorientation and high-angle grain boundaries, as well as a reduction in twin boundaries.

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.

Fundamental Investigation into Tool Wear and Surface Quality in High-Speed Machining of Ti6Al4V Alloy

This paper reports a fundamental investigation consisting of systematic trials into the response of Ti6Al4V alloy to high-speed machining using carbide inserts. It is a useful extension to work previously published, and aims at assessing the impact of the process parameters, depth of cut, cutting speed and feed rate in addition to cutting length, and their interrelations, on observed crater and flank wear and roughness of the machined surface. The results showed that abrasion was the most important flank wear mechanism at high speed. It also showed that increased cutting length accelerated crater wear more than exhibited flank wear and had considerable effect on surface roughness. In particular, crater wear increased by over 150% (on average), and flank wear increased by 40% (on average) when increasing cutting length from 40 to 120 mm. However, cutting the same length increased surface roughness by 50%, which helps explain how progression of tool wear leads to deteriorated surface quality. ANOVA was used to perform statistical analyses of the measured data and revealed that cutting length and depth of cut had the greatest effect on both crater and flank wear of the cutting tool. These results confirm that high-speed machining of Ti6Al4V alloy is a reliable process, with cutting speed identified as having a relatively small influence on the tool wear and resultant roughness of the machined surface relative to other parameters.

Investigation of the Wear Performance of TiB2 Coated Cutting Tools during the Machining of Ti6Al4V Alloy

The machining of Ti6Al4V alloy, especially at low cutting speeds, is associated with strong Built-Up Edge (BUE) formation. The PVD coatings applied on cutting tools to machine such materials must have the necessary combination of properties to address such an underlying wear mechanism. The present work investigates and shows that TiB₂ PVD coating can be designed to have certain mechanical properties and tribological characteristics that improve machining in cases where BUE formation is observed. Three TiB₂ coatings were studied: one low hardness coating and two high hardness coatings with varied coating thicknesses. Wear performances for the various TiB₂ coated carbide tools were evaluated while rough turning Ti6Al4V. Tool wear characteristics were evaluated using tool life studies and the 3D wear volume measurements of the worn surface. Chip morphology analyses were done to assess the in-situ tribological performance of the coatings. The micro-mechanical properties of the coatings were also studied in detail to co-relate with the coatings’ performances. The results obtained show that during the rough turning of Ti6Al4V alloy with intensive BUE formation, the harder TiB₂ coatings performed worse, with coating delamination on the rake surface under operation, whereas the softer version of the coating exhibited significantly better tool life without significant coating failure.

Optimization and Analysis of Surface Roughness, Flank Wear and 5 Different Sensorial Data via Tool Condition Monitoring System in Turning of AISI 5140

Optimization of tool life is required to tune the machining parameters and achieve the desired surface roughness of the machined components in a wide range of engineering applications. There are many machining input variables which can influence surface roughness and tool life during any machining process, such as cutting speed, feed rate and depth of cut. These parameters can be optimized to reduce surface roughness and increase tool life. The present study investigates the optimization of five different sensorial criteria, additional to tool wear (V_B) and surface roughness (Ra), via the Tool Condition Monitoring System (TCMS) for the first time in the open literature. Based on the Taguchi L₉ orthogonal design principle, the basic machining parameters cutting speed (v_c), feed rate (f) and depth of cut (a_p) were adopted for the turning of AISI 5140 steel. For this purpose, an optimization approach was used implementing five different sensors, namely dynamometer, vibration, AE (Acoustic Emission), temperature and motor current sensors, to a lathe. In this context, V_B, Ra and sensorial data were evaluated to observe the effects of machining parameters. After that, an RSM (Response Surface Methodology)-based optimization approach was applied to the measured variables. Cutting force (97.8%) represented the most reliable sensor data, followed by the AE (95.7%), temperature (92.9%), vibration (81.3%) and current (74.6%) sensors, respectively. RSM provided the optimum cutting conditions (at v_c = 150 m/min, f = 0.09 mm/rev, a_p = 1 mm) to obtain the best results for V_B, Ra and the sensorial data, with a high success rate (82.5%).