Tool Life Research Articles

Prediction of Tool Wear in Fine Blanking Punch with PVD Coating with TiCN for JIS.SKH51 High Speed Tool Steel Using Archard Wear Model

The aim of this study is predict tool wear in the fine-blanking process using a tribometer tester with ASTM G99-17 standard. Then, the result of wear volume and tool life were confirmed with finite element simulation and experiment. The punch material used in fine blanking process was selected to be hight speed steel JIS.SKH51 with surface coating thickness 4 µm of TiCN, the work piece material was used as hot-rolled steel JIS.SPHD P/O, with a thickness of 8 mm. The experimented and simulated results were found that the pressure, and sliding velocity were increase in term of linear curve with slope K = 2.09x10-6 and K = 2.07x10-6 ,respectively, and the hardness of material was increase in term of power at 1.983 and slope of K = 2.14 x10-6. These three factors were effect to the wear volume and tool life, simultaneously, the summation of three factors will average as K = 2.10 x10-6. From comparison of the applied wear equation model with tribology tester the simulated and experimented results were similarly equal with 0.05 by significance at 95% reliability confident. The resulted were precisely confirmed according to the previous research.

Enhancing tool dynamics and stability in internal turning with an adjustable clamping device under variable cutting conditions

This paper presents a novel method for suppressing the vibration of internal turning tools by adjusting clamping conditions. First, an adjustable device, incorporating multiple clamping modes, is developed to shift the tool frequency and improve the tool stiffness and damping. A multitude of clamping schemes can be generated by combining different clamping modes, and these schemes are subsequently quantitatively characterized as a group of multi-sourced boundary constraints. Building upon this foundation, the dynamical model for slender turning tools equipped with the designed device incorporates the effect of flexible boundary constraints. This incorporation is achieved through an inversion method that considers the uniqueness of the solution, facilitating accurate identification. Then, a cutting conditions-dependent adjustment strategy is developed to enhance tool dynamics and turning stability. The simulation results clearly illustrate the device’s capability to continuously and effectively adjust tool dynamics over a wide range. Consequently, the optimized clamping scheme can constantly adapt to the variable cutting conditions and the tool stability domain is further improved. Finally, a series of internal turning tests are carried out on difficult-to-machine materials. The experimental results demonstrate the effectiveness of the clamping device and the corresponding adjustment strategy in suppressing tool vibration stemming from various sources, no matter what tool structures and cutting parameters are pre-selected. As a result, the surface quality is improved, and the tool life is extended.

A New Semi-supervised Tool-wear Monitoring Method using Unreliable Pseudo-Labels

Tool-wear monitoring plays a crucial role in high-speed cutting machining as it ensures the accuracy of the machining surface, improves tool utilization, and extends the life of machine tools. However, effectively selecting and processing data from each stage of the feed-path and leveraging the vast amount of unlabeled data associated with different processing parameters present considerable challenges in practical scenarios. To deal with the above problems, this study proposes the tool-wear monitoring method using unreliable pseudo-labels (TWM-U2PL), comprising both a teacher model and a student model. Within TWM-U2PL, the teacher model encompasses two independent classifiers that facilitate the extraction and categorization of tool-wear features, additionally assigning labels to certain unlabeled data as either anodic or cathodic samples. The student model achieves accurate tool-wear monitoring by dynamically adjusting marginal and conditional distribution. The experiments on a tool-wear dataset confirmed the effectiveness of TWM-U2PL, which achieved an outstanding accuracy of 87.25%, surpassing the well-known models such as CNN, CHMM, and FE-PCA-SA.

Tool life prediction of dicing saw based on adaptive golden jackal optimizing GRU

Tool life prediction of dicing saw based on adaptive golden jackal optimizing GRU

MODELING OF THE TOOL LIFE FUNCTION OF A HOB MILLING TOOL USING GENETIC PROGRAMMING

The tool life of a hob milling tool and its cutting parameters have the greatest impact on gear cutting costs. The aim in this research was to model the tool life function of a hob milling tool, taking into account its impact on production costs. Experimental research of the tool life of a model single-tooth hob milling tool was carried out. On the basis of the obtained measurement results and by applying genetic programming, the tool life function of the hob milling tool was modelled. The paper presents a new model of the tool life function of the model single-tooth hob milling tool depending on the input cutting parameters, which include the cutting speed, axial feed and tangential feed.

Моделирование рабочих характеристик и мультикритериальная оптимизация при токарной обработке нержавеющей стали AISI 304 (12Х18Н10Т) резцами с износостойким покрытием и с износостойким покрытием, подвергнутым микропескоструйной обработке

Introduction. High-speed machining of stainless steel has long been a focus of research. Due to characteristics such as low thermal conductivity and work hardening, AISI 304 is considered to be a difficult material to cut. Machinability indicators provide important information about the efficiency and effectiveness of the machining process, enabling manufacturers to optimize their operations for increased productivity and precision. The purpose of the work. Coated carbide tools are most often used for machining AISI 304 stainless steel. Few studies, meanwhile, have examined the effects of pre-and post-treated coated carbide tools when turning these alloys at high speeds. In addition, only a small number of studies have simultaneously optimized the cutting parameters while employing pre-and post-treated tools. The methods of investigation. The present work comparatively evaluates the performance of coated and coated-microblasted tools during the turning of AISI 304 stainless steel. The tools were PVD-AlTiN coated, PVD-AlTiN coated with microblasting as a post-treatment (coated-microblasted), and MTCVD-TiCN/Al2O3 coated (MTCVD). The experimental-based mathematical models were developed to predict and optimize the turning performance. Results and Discussion. In this study, it is found that PVD-AlTiN coated tools have the lowest cutting forces and surface roughness, followed by PVD-AlTiN coated-microblasted and MTCVD-TiCN/Al2O3 coated tools. However, there is no significant difference observed in these responses for coated and coated-microblasted tools. It is found that the cutting forces increased with feed and depth of cut while decreasing with cutting speed. However, this effect is significant for MTCVD-coated tools. On the other hand, higher tool life is observed with MTCVD-TiCN/Al2O3 coated tools, followed by PVD AlTiN coated-microblasted and PVD-AlTiN coated tools. Tool life was largely affected by cutting speed. However, PVD-AlTiN coated tools exhibited this effect more noticeably. The models, with correlation coefficients found above 0.9, can be utilized to predict responses in turning AISI 304 stainless steel. The optimization study revealed that turning AISI 304 stainless steel with MTCVD-TiCN/Al2O3 coated tools incurs lower cutting forces of 18–27 N, produces a minimum surface roughness of 0.3–0.44 μm, and has a better tool life of 36–51 min compared to PVD-AlTiN coated (C) and PVD-AlTiN coated-microblasted (CMB) tools.

Modelling and experimental study of laser-assisted milling of fibre reinforced SiC/Ti-6Al-4V metal matrix composite

Metal matrix composites (MMCs) offer unique advantageous mechanical properties by strengthening a ductile metal matrix with a ceramic reinforcement (e.g., Ti6Al-4 V/SiCf). However, their heterogeneous composition poses machining challenges including fibre pullout, matrix cracking, and increased tool wear. Whilst pre-heating via laser-assisted machining (LAM) shows promise for improving machinability, traditional LAM implementations with a fixed laser spot size and straight laser path prevent uniform heating. By introducing spatially and temporally controlled LAM that generates homogeneous heating by varying the laser scanning velocity, a technique called fully inverse LAM can be applied for MMCs. This involves calculating separate temperature fields for the matrix and reinforcement to minimise thermal mismatch stresses. The fully inverse LAM decreases subsurface cracks and delamination resulting from conventional milling, whilst localised matrix softening reduces cutting forces by over 62 %. Flank tool wear is also diminished, increasing tool life by 120 %. Material analysis reveals reduced machined surface damage, lower surface roughness, and less formation of intermetallic compounds (Ti2C) compared to traditional LAM.

Wear of Carbide Plates with Diamond-like and Micro-Nano Polycrystalline Diamond Coatings during Interrupted Cutting of Composite Alloy Al/SiC

The complexity of milling metal matrix composite alloys based on aluminum like Al/SiC is due to their low melting point and high abrasive ability, which causes increased wear of carbide tools. One of the effective ways to improve its reliability and service life is to modify the surface by plasma chemical deposition of carbon-based multilayer functional layers from vapor (CVD) with high hardness and thermal conductivity: diamond-like (DLC) or polycrystalline diamond (PCD) coatings. Experiments on an indexable mill with CoroMill 200 inserts have shown that initial tool life increases up to 100% for cases with DLC and up to 300% for multilayered MCD/NCD films at a cutting speed of 800 m/min. The primary mechanism of wear of a carbide tool in this cutting mode was soft abrasion, when wear on both the rake and flank surfaces occurred due to the extrusion of cobalt binder between tungsten carbide grains, followed by their loss. Analysis of the wear pattern of plates with DLC and MCD/NCD coatings showed that abrasive wear begins to prevail against the background of soft abrasion. Adhesive wear is also present to a lesser extent, but there is no chipping of the base material from the cutting edge.

Tool condition monitoring of diamond-coated burrs with acoustic emission utilising machine learning methods

AbstractWithin manufacturing there is a growing need for autonomous Tool Condition Monitoring (TCM) systems, with the ability to predict tool wear and failure. This need is increased, when using specialised tools such as Diamond-Coated Burrs (DCBs), in which the random nature of the tool and inconsistent manufacturing methods create large variance in tool life. This unpredictable nature leads to a significant fraction of a DCB tool’s life being underutilised due to premature replacement. Acoustic Emission (AE) in conjunction with Machine Learning (ML) models presents a possible on-machine monitoring technique which could be used as a prediction method for DCB wear. Four wear life tests were conducted with a $$\varnothing $$ ∅ 1.3 mm #1000 DCB until failure, in which AE was continuously acquired during grinding passes, followed by surface measurements of the DCB. Three ML model architectures were trained on AE features to predict DCB mean radius, an indicator of overall tool wear. All architectures showed potential of learning from the dataset, with Long Short-Term Memory (LSTM) models performing the best, resulting in prediction error of MSE = 0.559 $$\mu $$ μ m$$^{2}$$ 2 after optimisation. Additionally, links between AE kurtosis and the tool’s run-out/form error were identified during an initial review of the data, showing potential for future work to focus on grinding effectiveness as well as overall wear. This paper has shown that AE contains sufficient information to enable on-machine monitoring of DCBs during the grinding process. ML models have been shown to be sufficiently precise in predicting overall DCB wear and have the potential of interpreting grinding condition.

A multi-domain mixture density network for tool wear prediction under multiple machining conditions

Accurate tool wear prediction is an essential task in machining processes because it helps to schedule efficient tool maintenance and maximise the tool's useful life, thus contributing to sustainable production via zero defect manufacturing (ZDM). However, there are limitations to existing methods; these cannot be used under multiple machining conditions, which is common practice. This problem not only hinders accurate tool wear monitoring but also necessitates the use of multiple models, which increases operation and modelling costs. Therefore, the multi-domain learning problem should be addressed to enable tool wear prediction under various machining conditions. To this end, this work presents a novel method, a multi-domain mixture density network (MD2N). In particular, a Bayesian learning-based feature extractor is proposed to learn domain-invariant representations. Additionally, an adversarial learning approach is developed to lead the predictive model in learning domain-invariant features. Lastly, a mixture density network-based predictor is used to generate probabilistic tool wear outputs. Experiments that use datasets from real-world milling processes under multiple conditions prove the proposed method's promising efficacy, with the best mean absolute error (MAE), root mean squared error (RMSE), and mean absolute percentage error (MAPE) of 2.1748, 5.6422, and 0.0350, respectively, indicating the ability to learn multi-domain representations.

Effect of the drag-finishing of cutting blades made of sintered carbides on tool life in particleboard machining

ABSTRACT It is currently known that in certain circumstances pre-rounding of cutting blades can significantly increase tool life. Despite many data on the beneficial effect of drag-finishing on the durability of metalworking tools, it is not entirely clear whether similar benefits appear when machining wood-based panels. The results of some pilot study are quite promising but the real impact of cutting blades pre-rounding (it is about blades made of various standard cemented carbides), on tool life in particleboard milling are very rarely studied. The study aims to fill this gap in the knowledge system. The experimental research was carried out using a CNC milling machine equipped with a single-blade milling head with replaceable blades. It turned out that the positive effect of the drag-finishing of cutting blades on tool life in particleboard machining depends on the structure and hardness of carbide. A significant extension of the tool life (about 50%) was observed only in the case of particularly hard carbide (2240 HV10). There was no significant advantage for the softer type of carbide (1800 HV10).

Machinability of CFRP/Ti6Al4V stacks with low-frequency-vibration assisted drilling under different cooling strategies

Carbon fiber reinforced plastic (CFRP)/Ti6Al4V stacks are widely used in the aircraft industry, and drilling these stacks is essential during the assembly process. To solve the problem of high drilling temperatures in CFRP/Ti6Al4V stacks, which lead to poor tool life and hole quality, the effects of three cooling strategies compose minimum quantity lubrication (MQL), water-based coolant, and internal air cooling, were investigated in this study. Tensile/compressive strength and fatigue-life tests were conducted to evaluate the applicability of the cooling medium before drilling. Then, low-frequency vibration-assisted drilling of CFRP/Ti6Al4V stacks was performed to investigate and analyze their machinability under the three cooling strategies by analyzing the drilling temperature, thrust force, tool wear, chip removal capacity, and hole quality. The results show that the selected cooling media, including Rhenus XT46 and Accu-Lube LB2000, are applicable in CFRP drilling, whereas the adopted media, compared with water, have little influence on the tensile/compressive strength and fatigue life of the CFRP. Compared with internal air cooling and MQL, water-based coolant can more effectively improve the machinability of CFRP/Ti6Al4V stacks, decreasing the CFRP drilling temperature by 41.6 % and 40.1 %, respectively, while the reductions in the Ti6Al4V drilling temperature are 76.7 % and 57.4 %, respectively. Meanwhile, under water-based coolants, the thrust force reductions in the drilling of CFRP are 13.1 % and 11.7 %, whereas those in the drilling of Ti6Al4V are 11.0 % and 7.8 %, respectively, compared with the internal air and MQL. In addition, under the water-based coolant condition, the tool wear rate is the slowest and the hole quality is the best among the three cooling strategies, whereas a high injection pressure further decreases the VBmax value. Furthermore, under the water-based coolant conditions, the Ti6Al4V exit burr height and CFRP exit delamination are the lowest. These findings provide useful insights into improving the machinability of CFRP/Ti6Al4V stacks in the aerospace industry, particularly for drilling that requires high-quality holes and a long tool life.

OP100 Patient Perspectives In Value Assessment Frameworks: The Asia Pacific Perspective

IntroductionThe importance of patient centricity in healthcare decision making has been recognized and advocated for decades. However, approaches for including the patient perspective are diverse, and progress varies among countries. Some reimbursement bodies acknowledge the importance of patient preferences in health technology assessment (HTA) and funding decision processes. However, patients’ perspectives are not yet systematically and transparently included in value assessment frameworks globally, and even less so in the Asia-Pacific (APAC) region. This systematic review aimed to investigate how patients’ perspectives are used to inform pricing and reimbursement decisions in the APAC region.MethodsA systematic review is ongoing that utilized a search of 12 databases, including MEDLINE and Embase, to identify publications on the consideration of patient perspectives in health policy decision-making published to November 2022. Conference abstracts published in the last five years from ISPOR and Health Technology Assessment International (HTAi) were screened, along with gray literature and government websites from Australia, China, Japan, Malaysia, New Zealand, the Philippines, Singapore, South Korea, Taiwan, and Thailand. Publications were included if the impact of either one or more of the following on HTA decision-making was assessed: active participation of patients or patient advocacy groups; type, extent, and evolution of patient-reported outcomes; health-related quality of life or quality of life tools; and themes where the impact of patients’ perspectives on value assessment was the primary outcome. Countries were characterized into archetypes based on similarities or differences in the weight and value assigned to patient perspectives in decision-making.ResultsA total of 6,438 retrieved citations will undergo the systematic review process. Additionally, 758 conference abstracts from ISPOR, 1,312 from HTAi conferences and 73 records from gray literature will be screened.The results of the systematic review will be consolidated into country archetypes, examples, and learnings. Gaps and opportunities will also be identified.ConclusionsThe research will provide recommendations to increase shared decision-making and support the development of decision-making frameworks that systematically incorporate patients’ perspectives in value assessment across APAC countries.

Temperature and distortion in laser melt injection of MMC wear-resistant coatings in a copper beryllium alloy

Wear-resistant coatings made of MMC materials (metal matrix composites) are ideal for increasing the service life of tools subjected to high abrasive stresses. Such MMC surfaces can be produced by laser melt injection during the manufacturing process of the tools or subsequently as a retrofit near-net-shape. However, during laser melt injection (LMI) thermally induced residual stresses can be introduced into the MMC surfaces. These can have a detrimental effect on the service life of these surfaces and thus reduce the positive effect of wear resistance.In order to determine the influence hard particles injected during LMI have on residual stresses within the surface layer the distortion of the surface layer was evaluated. MMC layers consisting of a copper beryllium matrix and fused tungsten carbide hard particles were created by LMI. The MMC layers are compared to parts with remelted surfaces. Laser power and process velocity were varied to examine their influence on distortion. The process temperature was recorded on the melt pool by a two-color pyrometer. After the process the top layer of the MMC surface was cut off by wire EDM and then measured with a coordinate measuring machine. It is shown that an increase of incorporated powder mass per unit length and process temperature lead to higher distortions.

Eddy current testing in drill-bit tools

Machining technology plays a major role in modern manufacturing industries due to the growing demand for equipment and products for aerospace, automotive, precision machinery sectors etc. A key issue associated with any type of machining operation is the accelerated tool wear which leads to shorter tool life, thus to low machining precision and decreased productivity. In this paper an electromagnetic Non-Destructive Testing method (NDT), and in particular Eddy Current Testing (ECT), is used to detect the wear of used cutting tools vs a new one.

Metallurgical Microstructure Evolution of Friction Drilling With AL6061-T6 at Various Regions of Bushing Formation

Friction drilling is one of the non-conventional holes making process, it is a clean and chip-less operation which uses the frictional heat to create the hole on base materials. In any kind operations like machining of metal and mining of fuels the microstructure is composed with its various phases of size, variable form, and distribution (dendrites, grains, lamellae, precipitates, spherulites, pores, etc). Friction stir drilling technology is specifically designed for mining operations. The improved microstructure of the drilled holes ensures better load distribution and resistance to wear and tear. This translates into longer tool life, increased operational efficiency, and ultimately higher profitability for mining companies. The microstructure of metals plays a crucial role in the mining industry, primarily in two main aspects- extraction and processing of ores. In this microstructure of friction drilling hole of brittle cast materials like Al6061-T6, has been investigate with the help of optical microscope at various regions like Stirring Zone (SZ), Thermo Mechanical Affected Zone (TMAZ)and Heat Affected Zone (HAZ). Those zones are divided based on tool contact with work piece. It is observed that Al and Si particles are recrystallized structure. Due to thermal energy and forces acting on the material drilled hole contains few adhered at walls. At when compared with the HZA and TMAZ, SZ zone contains smaller mean particles are observed.

Study on tool wear mechanism and chip morphology during turning of Inconel 713C by textured inserts

The present study aims to analyze the tool wear mechanism and chip morphology during dry (D) and graphene solid-lubricant (S), turning of Inconel 713C with a new novel textured (honeycomb (T2) and rectangular(T3)) and further compare with the textured dimple tool (T1). In addition, the performances were compared with the untextured tool (T0). The machining tests for all conditions were carried out at different levels of cutting speeds (75 m/min and 150 m/min), feed rate (0.1 mm/rev and 0.2 mm/rev), and a constant level of depth of cut (0.5 mm). Honeycomb-textured cutting tools performed better. Improvements of 33.3 % (T1D), 50 % (T3D), and 75 % (T2D) without graphene and 66.6 %(T1S), 75 % (T3S), and 100 %(T2S) with graphene are observed compared to T0. The primary mechanism for the better performance of T2S was the reduced tool chip contact length (8–50 %), chip width (30.4 %), friction coefficient (57.4 %), chip thickness (17.8 %), and higher shear angle (14.2 %) compared to dry textured and untextured tools at the end of tool life. Additionally, the T2S (solid lubricant-impregnated honeycomb) demonstrates a decrease in equivalent chip thickness (19.8 %) and an increase in shrinkage factor (17.2 %) at worn-out tool life conditions at high cutting speed and feed rate. Under the same conditions, T2S has 27.3 % lower cutting force and 36.2 % lower surface roughness of machined workpieces compared to the untextured tool at the end of tool life. The chip micrograph reveals the chips are shorter, and the chip radius is lower for T2S tools with smooth friction tracks and fine deformed lamella on the free surface of the chip. Under SEM, flank wear, adhesion materials, abrasion, micro-chipping coating peeling, and BUE were dominant wear mechanisms. However, T2S tools effectively reduce Ni elements' diffusion and suppress the built-up edge's adhesion by improving friction characteristics at the tool-chip interface region. Lastly, the outcomes of experimental results suggest that the honeycomb texture for dry machining of Inconel 713C.

Development of a Cutting Fluid with Abrasive for Increasing a Tools Life During Milling

Development of a Cutting Fluid with Abrasive for Increasing a Tools Life During Milling

Life cycle comprehensive performance assessment of the TiAlN coated tool based on surface treatment

The optimal surface treatment process can availably improve tool surface properties, and meet the requirements of low-carbon manufacturing. In this work, based on tool surface modification technology and tool life cycle carbon emission system, TiAlN coated tools are carried out micro-blasting treatment (MBT), cryogenic treatment (CT) and heat treatment (HT). The effects of surface treatment processes on the surface integrity (morphology, roughness, micro-hardness, residual stress) of the coated tool are studied. The high-speed dry finishing turning experiments of cobalt-based superalloy are carried out to investigate the tool wear morphology and wear mechanism. The carbon emissions of the tool life cycle are analyzed. Finally, the comprehensive performance of the coated tool within life cycle is evaluated. The results show that the highest level of surface integrity of coated tool is achieved by MBT, while the lowest carbon emission of environmental is impacted by HT. Compared with the untreated (UT) tool, the micro-blasted tool has the most significant improvement in surface roughness with a 28.6% reduction. The cryogenic treated tool has the greatest improvement on the surface hardness which is increased by 44.4%. The effect of HT on the surface residual stress is the most obvious. The surface stress of the heat-treated tool has increased by 59.4%. Moreover, the flank wear VB of the micro-blasted tool, cryogenic treated tool and heat-treated tool is reduced by 25.17%, 24.50% and 32.12%, respectively. The main wear mechanisms of the treated tool are adhesive wear, oxidation wear and abrasive wear. According to comprehensive performance assessment, the performance of surface treatment process during the coated tool life cycle is: HT > MBT > CT > UT.

Improved STFT analysis using time-frequency masking for chatter detection in the milling process

In the field of machining, the purposeful increase in cutting depth and rotation speed can potentially cause chatter vibration. Chatter lowers surface quality, tool and spindle life, and produces excessive noise, which limits the productivity of the machining process. In this paper, an improved Short-Time Fourier Transform (STFT) involving time–frequency masking and adaptive thresholding is proposed. Initially, hammering tests were undertaken to ascertain the inherent natural frequency of the cutting system. Subsequently, milling tests were conducted across varied conditions utilizing an accelerometer sensor and a microphone (capturing sound signals) to acquire the requisite experimental data. A 3-level Variational Mode Decomposition (VMD) was used for pre-processing due to its inherentcapabilities for noise reduction. The chatter threshold is established by averaging the total intrinsic mode function (IMF) energy levels that have been selected. To demonstrate the efficacy of the proposed method, root mean square (RMS) and skewness were calculated as chatter indicators. The improved STFT time–frequency representation (TFR) was compared to the conventional TFR. Notably, both indicators demonstrate effectiveness and chatter sensitivity, while the improved STFT offers greater time–frequency resolution than its conventional counterpart and can be successfully used for monitoring the milling process.