Tool Wear Progression Research Articles

Autoencoder based Wear Assessment in Sheet Metal Forming

The amount of information contained in process signals such as acoustic emission and force signals has proven vital for the detection of changes in physical conditions or quality feature prediction in sheet metal forming applications. Both signal types have also been researched in the context of wear detection, yet systems that reliably identify the wear state at a given time in sheet metal forming processes based on these signals do not exist. This paper proposes an architecture to assess the wear increase within a given time frame in an experiment based on an autoencoder. The ability of autoencoders to encode and decode signals has been widely studied and this approach leverages the fact that autoencoders are more likely to learn representative encodings on stable and homogeneous signals than on heterogeneous signals with high fluctuations. This approach utilizes the circumstance that high tool wear leads to changes in the signal and signal fluctuation. In consequence, autoencoders can be utilized to track tool wear progression without the need for labelled data. The findings show a strong similarity to physical models for the wear progression of tool components, indicating the validity of this approach. Additionally, an analysis of the signals yields characteristic effects of the considered force signals that could specifically represent wear resistance.

Extraction of tool wear indicators in peck-drilling of Inconel 718

This paper presents an experimental method for predicting tool wear in drilling Inconel 718 superalloy. The method combines analysis of drilling force signals and tool wear progress. Force characteristics were studied both in time and frequency domains (power spectrum and wavelet decomposition) in order to find best correlation with tool wear progress. These analyses show that the mean value of the thrust force component, the high frequency component of the force, the frequencies that arise during drilling, and the evolution of the wavelet decomposition details are all sensitive to tool wear progress. Therefore, these characteristics can be employed as indicators for drill failure prediction. Among all those indicators, the mean value of the thrust force and the standard deviation of high frequency components of that force have shown the greatest sensitivity to drill wear.

Study of the Effects of Initial Cutting Conditions and Transition Period on Ultimate Tool Life when Machining Inconel 718.

Rapid tool wear and limited tool life are major problems when machining Inconel 718, which still need further attention. Amongst the reported strategies, limited studies have been reported on optimizing initial cutting conditions by means of tool life improvement. Therefore, in this work, the tool wear progress and tool life were investigated by varying the initial conditions in the transition period, which was set at four seconds. The transition point was discovered by previous works by the authors. After the transition point, similar cutting conditions were used as the reference condition. The tool wear morphology and size were recorded and analyzed in each condition. It was revealed that applying a lower cutting speed and feed rate in the transition period led to improved tool life as compared to the reference condition. In other words, the use of optimum levels of cutting parameters in the transition period of the cutting process may enhance tool life at higher cutting time. For instance, initial feed rate (0.15 mm/rev) and cutting speed (25 m/min) led to the improvement in the ultimate tool life by about 67% and 50%, respectively. Besides, applying the lower initial cutting speed, i.e., 25 m/min, increased the tool life by about 50% when the insert reached the maximum flank wear (vBmax) of 300 µm in comparison with those at higher initial cutting speeds. This phenomenon may lead to better insight into the effect of the influence of the initial cutting conditions in the transition period on tool life when machining hard-to-cut materials. Moreover, the built-up edge (BUE) was exhibited as the primary wear mode in all cutting conditions.

Spatially Resolved Tool Wear Prediction in Finish Milling

Tool wear is a cost driver in the metal cutting industry. The development of tool wear is mostly unknown during process planning of a finish milling operation. This study investigates a tool wear prediction method based on a dexel-based engagement simulation and cutting experiments. With this modelling approach, progression of tool wear is spatially resolved along the cutting edge of the tool. This paper contributes to the perspective of transparent process planning in milling. In particular, the ability to plan tool changes and to distribute wear uniformly along the cutting edge helps to improve surface quality and reduce tool cost.

Anisotropy effect on Laser Powder Bed Fused Ti6Al4V machinability

Final machining steps are commonly requested on parts obtained via additive manufacturing to ensure the required surface finish and geometrical tolerances. When machining additive manufactured workpieces, their typical microstructural anisotropy is rarely taken into consideration. In this work, the influence of the build-up orientation of Ti6Al4V parts obtained via laser powder bed fusion on machinability is studied. Ti6Al4V blocks with horizontal and vertical development were additively manufactured and then milled. Tool wear progression was monitored and its effect on surface quality investigated. The cutting tool that machined the horizontally oriented sample showed a tool life 66% higher than the one that machined the vertically oriented one. This study demonstrates the strong correlation between the build-up orientation of additive manufactured components and their machining response.

Tool wear progression of SiAlON ceramic end mills in five-axis high-feed rough machining of an Inconel 718 BLISK

The machining of heat-resistant super alloys such as Inconel 718 is still challenging. Processes are characterized by low productivity and high tool costs compared to the machining of steel or titanium materials. SiAlON ceramics offer potential for productivity increases, but are rarely used in industrial application due to uncertainties regarding the correct machining parameters or applicable tool life criteria. In this study, a complex miniaturized high-pressure compressor blisk component was machined using ceramic end mills for the roughing operation. Based on these experiments, the productivity increase of SiAlON ceramic roughing tools was compared to conventional cemented carbide tools. Additionally, a detailed tool wear analysis was conducted. Thereby, a wear-related tool radius decrease could be observed over the machined volume and a linear approximation could be made. Multiple tools exhibited similar tool wear progression.

In-process monitoring and empirical modeling of the tool wear in turning of aluminum alloys using thermoelectric signals

Tool wear is an important criterion for economic machining. It does not only determine the tool life, but also affects the surface layer properties of metallic components and thus their performance. In addition to the machining parameters, there are numerous other influencing factors like batch variations, workpiece inhomogeneities, process vibrations, or the formation of built-up edges that can impact the wear progression. Consequently, it is difficult to predict the tool wear analytically. Therefore, the determination of the tool condition during machining is of great importance. The tool-workpiece thermocouple enables the in-process measurement of a thermoelectric voltage and current during machining generated by the Seebeck effect at the interface between two electrically conductive materials. Thus, the thermoelectric signals are sensitive for the changing contact interface between the tool and the specimen. To allow for an in-process characterization of the tool wear, finding an empirical relationship between the flank wear land width of cemented carbide indexable inserts and the thermoelectric signals in turning is aspired. To vary the flank wear land width in a reproducible manner, tools with a flank face chamfer resulting in a clearance angle of 0° and five different flank face land widths (80 µm – 280 µm) are used. These geometrical properties are measured with a 3D laser scanning microscope. Afterwards, cylindrical specimens of the aluminum alloy EN AW-2017 are machined by turning applying the modified tools and cutting speeds in the range of 300 m/min to 550 m/min. The depth of cut (0.4 mm) and the feed (0.04 mm) are kept constant. Besides the tool-workpiece thermocouple, the components of the resultant force are measured by a dynamometer. The geometrical properties of the machined surfaces are characterized using a stylus measurement instrument.The experimental investigations show an increase of the temperature and the components of the resultant forces with increasing flank wear land width, which impacts the geometrical properties of the surface. An empirical regression model derived from the in-process measurement results depicts the relationship between the thermoelectric signals, the force components, and the changing area of the tool which is in contact with the specimen. Consequently, the combined in-process measurement of the process forces and thermoelectric signals allows for an in-process determination of the tool wear progression and therefore enables the prevention of a strong impairment of the surface-layer properties by a timely tool change or a controlled adjustment of the machining parameters.

Kajian Simulasi Fem 3D : Keausan Pahat Twist Drill pada Pemesinan Bor Mikro Material Ti-6Al-4V

Titanium is a material that has a good strength to weight ratio, excellent corrosion resistance, and resistant to high or low temperatures Titanium alloys that are used in various industrial fields, one of them is the Ti6Al4V alloy. Micro drilling has a high rotational speed which results in tool wear, high temperatures, and surface roughness. This research uses The Finite Element Method (FEM) simulation. The application used is DEFORM 3D based on parameters from previous studies. The purpose of this research is to identify the progress of tool wear in a simulated manner on the Ti6Al4V alloy micro-dilling and analyze the tool wear on the Ti6Al4V alloy micro-drilling under dry machining conditions. Machining trials used CNC micro-drilling at various of cutting parameters such as cutting speed of 10.000 and 15.000 rpm. The results showed that the tool wear progress at the 5th hole was 0.00346 mm, the tool wear progress at the 10th hole was 0.00462 mm and the tool wear progress at the 15th hole was 0.00525 mm. Analyzing tool wear in simulated machining and experimental machining in dry conditions has a high wear value. Tool wear is simulated by measuring the radius of the tool in the 15th hole valued at 0.09973 mm. Tool wear is experimentally measured from the tool radius in the 15th hole valued at 0.0101 mm. The tool mesh is changed due to the tool wear. The tool mesh in the 5th hole is worth 17372 mesh. The tool mesh in the 10th hole is 15662 mesh. The tool mesh in the 15th hole was highly reduced by 13021 mesh. Tool wear affects the change in tool mesh. With increasing tool wear then tool mesh is reduced. The next cause of tool wear is the tool temperature in the machining process.

Use of image processing to monitor tool wear in micro milling

Micro milling is a versatile machining process owing to its capability to machine, by material removal, micro-sized components with complex geometrical features. However, micro milling tools wear quickly, being a key issue to determine tool wear condition in order to prevent excessive tool wear or a sudden tool breakage while machining, which would waste the workpiece. Due to the small size of micro milling tools, direct measurement of the worn tool is not possible. In order to overcome this drawback, this paper presents a new method based on digital image processing where image captures of the micro tool and subsequent analysis provides a valuable information to determine the progression of tool wear. Tool wear is measured in flank wear, crater wear and tool radius reduction. Different approaches are compared so as to determine the best option for every set of images. These methods are based on the use of morphological operations, k-means clustering and Otsu Multilevel algorithm. Results show a good performance with differences of 5% between predicted and actual worn area, which satisfies the industrial requirements. This procedure can be transferred to industrial environments and implemented in collaborative robots, increasing the level of automation and facilitating the decision-making process.

Tool wear progression and its effects on energy consumption and surface roughness in cryogenic assisted turning of Ti-6Al-4V

This work evaluates the machinability improvements in vastly used titanium alloy (Ti-6Al-4V) using alternate turning techniques. Detailed examination of flank and crater faces of inserts is carried out in this work to analyze tool wear under dry, wet, and cryogenic environments. Critical responses such as crater wear and energy consumption decide the machinability of materials, but these responses are less explored in the past using altered cutting conditions. This investigation analyzes the machinability in terms of industry-relevant responses such as tool wear, energy consumption, chip reduction coefficient, and average surface roughness under altered cutting conditions. Outcomes of this investigation show increase in tool life by 200% and 80% using cryogenic turning than in dry and wet turning techniques, respectively. Moreover, the findings of the study show up to 9% and 61% decline in energy consumption using cryogenic turning than in dry and wet turning, respectively. Surface roughness values also show a reduction by up to 71% and 64%, under cryogenic environment than in dry and wet environments, respectively. The results of this study advocate the suitability of cryogenic turning at industry-relevant parameters to establish this technique as a viable alternative to replace inefficient conventional turning techniques.

Tool Wear Progression and Optimization in End Milling of AISI 316 Stainless Steel

The high-performance machining of difficult-to-cut stainless steel (AISI 316) demands the development and optimization of high-performance tools that can withstand tool load without compromising the surface quality of the components been produced. To justify the optimization feasibility of coated carbide tool in end milling application for good surface quality, a material removal and Productivity approach by evaluating the tool life under optimized cutting condition were carried out in this current research. The objective of this study is to optimize flank tool wear in end milling of AISI 316 using Design of Experiment and box-Behnken method. Tool wear value of 0.174mm was achieved through optimization at low values of feed, speed, and depth of cut. However, an increased feed, depth of cut and speed promised to yield better volume removed in return making tool life to be truncated faster.

Initial tool wear behavior in high-speed turning of Inconel 718

Three distinctive regions of tool wear, known as initial wear, steady-state wear, and accelerated wear, are well understood. However, the effects of cutting parameters on the initial tool wear mechanism, morphology, and size have received less attention as compared to the other two regions. Knowing that adequate control of initial tool wear may lead to extended tool life, in particular in hard-to-cut metals such as superalloys, this topic has become a source of attention. Amongst superalloys, Inconel 718 is considered as one of the most difficult to cut materials, which has a wide range of industrial applications. This study intends to evaluate the effects of cutting parameters on initial tool wear, as well as tool wear progression, when turning Inconel 718. Therefore, microstructural evaluation of the initial tool wear mode under various cutting conditions, as well as tool wear measurements, were conducted. It was observed that certain elements of the workpieces were migrated to the insert flank face. This is evidence of adhesion at the initial moments of the cutting process. In contrast to many other easy-to-cut materials, the steady-state wear period when turning Inconel 718 is significantly short under a higher level of cutting speed and feed rate.

Reliability analysis of the cutting tool in plasma-assisted turning and prediction of machining characteristics

ABSTRACT Heat-assisted machining (HAM) is an alternative method for the successful machining of difficult-to-cut aerospace superalloys. However, the tool wear progression in HAM has been substantially affected by the workpiece external heating temperature along with the machining parameters. It is of great importance to precisely estimate the tool wear progression and reliability of the cutting tool operated in HAM to enhance the machining efficiency and economics. Hardened AISI4340 alloy steel was machined under plasma-arc heating conditions with WC cutting tools. The experimental results reviled that for 200°C of preheating temperature, the surface roughness noted as 2.03µm and tool life as 870s. While at 600°C, the surface roughness as 1.68µm, and tool life extended to 1885s to reach the set threshold value of 0.4mm flank wear. Notch wear as dominant tool wear mechanism at 200°C and 400°C, while it is diffusion wear at 600°C. On the establishment of stochastic tool life distribution and reliability models, tool lives measured at all heating conditions followed a Weibull distribution. Empirical models for tool wear, surface roughness, and material removal rate were postulated and validated statistically as-well-as experimentally. The derived reliability and empirical models can be used to predict the machining characteristics to enhance its performance.

Tool Wear Characterization and Monitoring with Hierarchical Spatio-Temporal Models for Micro-Friction Stir Welding

Abstract Tool condition in manufacturing plays a significant role on process dynamics and part quality. Effective modeling and monitoring of tool condition deterioration can provide the technical basis for maintaining production efficiency and quality. Inspired by the need of tool condition monitoring in joining dissimilar materials, especially the micro friction stir welding (μFSW) process, this paper aims to model and monitor the spatial and temporal patterns in the dynamic tool wear propagation in μFSW. A hybrid hierarchical spatio-temporal model is developed for the time-ordered, high-dimensional tool surface measurement images to characterize the dynamic tool wear propagation in μFSW. The model is developed in a hierarchical Bayesian structure with the first level being a data-driven regression model for the high-resolution tool pin profile images and the second level being a physics-based advection-diffusion model for the welding temperature distribution. Kalman filter is adopted to estimate the posterior distributions of the state variable (temperature distribution) and the error between the measured tool surface image and the predicted images. Regularized Mahalanobis distance is proposed to monitor tool wear progression. Numerical studies on three abnormal tool wear progression patterns demonstrate the effectiveness of the proposed spatio-temporal modeling method, as well as the timeliness, confidence, and power of detection. Results show that abnormal tool wear progression can be detected within 2 time-steps, the detecting accuracy of abnormal tool wear progressions can reach 99%, and the Type II error rates remain at 0. The method developed in this paper is expected to facilitate early detection of abnormal tool wear progressions, reduce the efforts in manual inspection, and support smart manufacturing. The proposed methods can be easily extended to other manufacturing processes with online sensing and tool measurement capabilities.

Dataset and methodology on identification and correlation of secondary carbides with microstructure, wear mechanism, and tool performance for different CERMET grades during high-speed dry finish turning of AISI 304 stainless steel.

The aim of this research is to utilize reverse engineering approach for the identification of the elements and phases available in the commercial CERMET inserts with the help of characterization techniques such as Scanning Electron Microscope (SEM), Energy-dispersive X-ray spectroscopy (EDS), and X-Ray Deposition (XRD). Four commercial CERMET inserts were investigated in this research work, and the effect of the composition and phases are related to its tool wear mechanism and performance. Each CERMET insert is used to perform a turning process on a CNC lathe for machining stainless steel (SS) under the dry condition at a fixed cutting length interval. Once it completes machining for a fixed cutting length, the CERMET insert is taken out to investigate its wear mechanism with the help of SEM, EDS, XRD and using a focus-variation microscope (Alicona). A correlation analysis is performed to relate progressive tool wear mechanisms with elements and their relevant phases of various carbides. The approach of correlating wear property with the phase content will contribute to the understanding of the wear mechanism under such extreme machining conditions. It will serve as a reference for the improvement of the performance of these CERMET inserts for such harsh machining conditions by the development of protective coatings for these CERMET inserts based on the identification of the composition and phases that improves tool life and reduces wear. The data related research work can be found at “https://doi.org/10.1016/j.wear.2020.203285” [1].

Effect of the Fiber Orientation and the Radial Depth of Cut on the Flank Wear in End Milling of CFRP

In this study tool wear during CFRP milling is experimentally investigated to explore the optimization of various cutting condition. From the test machining, it was found that CFRP milling was conducted mostly through the brittle mode machining that creates chip with powder shape. Tool wear is originated from the flank wear generated by the friction force between flank face and machined surface as well as the cutting edge wear by an impact force of fiber cutting. The flank wear is focused on a fiber orientation as well as a friction distance of the flank face in this paper. Based on the results, the tool wear progression model is suggested considering the fiber orientation and the radial depth of cut. From the results, it was found that the fiber orientation greatly affects the flank wear which arises most severely at the parallel to the tool feed direction that induces larger friction force. Also, the radial depth of cut smaller than 10% of diametric engagement accelerates the flank wear due to the increase of friction distance. Using this correlation among parameters, wear prediction model with force equations was derived and estimation results sufficiently match with the wear measurement values.

Analysis of tool vibration and surface roughness with tool wear progression in hard turning: An experimental and statistical approach

The machined surface quality and dimensional accuracy obtained during hard turning is prominently gets affected due to tool wear and cutting tool vibrations. With this view, the results of tool wear progression on surface quality and acceleration amplitude is presented while machining AISI 52100 hard steel. Central Composite Rotatable Design (CCRD) is employed to develop experimental plan. The results reported that vibration signals sensed in a tangential direction (Vz) are most sensitive and found higher than the vibrations in the feed direction (Vx) and depth of cut direction (Vy). The acceleration signals in all three directions are observed to increase with the advancement of tool wear and good surface finish is observed as tool wear progresses up-to 0.136mm. The vibration amplitude is discovered high in the range 3 kHz – 10 kHz within selected cutting parameter range (cutting speed 60-180mm/min, feed 0.1-0.5mm/rev, depth of cut 0.1-0.5mm). The investigation is extended for the development of multiple regression models with regression coefficients value 0.9. These models found statically significant and give dependable estimates between a tool vibrations and cutting parameters.

Tool wear progression of PCD and PCBN cutting tools in high speed machining of NiTi shape memory alloy under various cutting speeds

NiTi shape memory alloys are coming into prominence in various industrial applications owing to their unique shape memory effect, super-elasticity and mechanical properties. However, this material is characterized by its very poor machinability rates. One of the major reasons of this problem is the high tool wear rate, which primarily occurs due to nature of this material. The previous work reported in the literature has been limited to investigate low to medium speed machining characteristics of this material especially with carbide and coated carbide cutting tools. This paper presents the results of experimental investigation on the progressive wear behaviors of Polycrystalline Diamond (PCD) and Polycrystalline Cubic Boron Nitride (PCBN) cutting tools in turning of equi-atomic NiTi shape memory alloy. Effects of cutting speed, which varied between Vc = 70 and 250 m/min, were investigated. Periodical tool wear measurements were conducted in order to find tool life and evaluate wear mechanisms. The results show that tool wear mechanism is highly cutting speed dependent. PCD cutting tool performed better wear resistance at all of the investigated cutting speeds. The optimized cutting speed and cutting tool couple is suggested to increase productivity regarding longer tool life.

Energy consumption considering tool wear and optimization of cutting parameters in micro milling process

Micro milling process aims to manufacture complex micro/meso structures, and the reduction of material removal volume determines the possible decrease of the total energy use, which would put less pressure on the environment. However, the energy consumption of micro milling influenced by tool wear and tool run-out would be augmented and result in the drawback of more energy consumption. In order to reduce the energy consumption of micro milling process, a new analytical energy consumption model and the related optimization of cutting parameters are presented in this paper. Although the influence of tool wear is inevitable, it hasn't been thoroughly concerned in the existing energy consumption models. Therefore, the stochastic tool wear progression, which can be obtained from a probabilistic approach based on the online measured cutting forces, is integrated into the proposed energy model. In addition, the process nonlinearities caused by tool run-out and the trochoidal trajectories of cutting edge are also considered in the model. With the developed prediction model of energy consumption, a hybrid cuckoo search and grey wolf algorithm is used to determine the optimum cutting parameters for minimizing the total energy consumption. The micro milling experiments are performed to validate the accuracy and availability of the proposed energy consumption model and the optimization method. The improved optimization method based on the proposed energy model can reduce the energy consumption by 7.89% compared with the empirical selection.

BN 첨가 AISI P20 쾌삭강의 개발

As products life cycles are becoming shorter, the reduction of die and mold manufacturing cost and time is becoming more crucial in the machinery, automotive, and electronics industries. Over the past decades, many initiatives have been made to develop high performance free-machining steels without significant degradation of mechanical properties. To develop a modified AISI P20 free-machining steel, we studied the effects of B, N, and S additives on the variations of the cutting forces and metal structures such as grain size, density, and distribution of free-machining inclusions. From a set of experiments, it was observed that an appropriate addition of B and N additives reduces the resulting cutting force by approximately 6.3% and delays the tool wear progress. During the solidification B and N additives form hBN precipitates, with a layered and planar structure, within the steel matrix. The hBN precipitates’ weak shear strength results in lowering the required milling force. It is also confirmed that machinability is prominently improved when a large number of microsized hBN precipitates are distributed uniformly in the steel matrix. This study could contribute to the development of high performance BN-added free-machining steels for die and mold applications.