Powder Compaction Process Research Articles

New Die-Compaction Equations for Powders as a Result of Known Equations Correction—Part 3: Modernization of Plasticity Equations for a Porous Body

Equations of plasticity of a porous body proposed by different authors and obtained under the condition that the yield surface of a porous body has the shape of an ellipsoid of revolution are considered in this paper. Such equations have two independent parameters which are the functions of relative density. Various theoretical dependences of these parameters on the relative density and, as a result, various equations for describing the die-compaction of powders are presented. It is shown that the correction of two density-dependent parameters, taking into account the initial density, makes it possible to significantly increase the accuracy of approximation of experimental data on the powder compaction process (PCP) of various powders. Among the considered “continuum” equations of powder die-compaction, the PCP to a density of 0.95 is the most accurately described by the equation in which the corrected Skorokhod’s theoretical density functions are used and which contains one constant as a result. Another equation which contains four constants allows one to accurately (R2 > 0.9990–0.9999) describe the PCP to a density of >0.95. This equation is obtained by replacing one of two independent parameters in the traditional continuum equation with the lateral pressure coefficient followed by substituting, instead of those parameters, their dependencies on the density in the form of power function. The adequacy of the PCP description by this equation was verified by approximating experimental data on the die-compaction of iron powders to a relative density greater than 0.95, as well as highly plastic powders with a final density of ~1.0.

The mesoscale mechanics of compacted ductile powders under shear and tensile loads

A discrete numerical analysis of the yield and damage properties associated with a cohesive granular system composed of ductile particles is hereby presented. Such a modelling approach aims at better understanding damage mechanisms which are often encountered during the powder compaction process, widely used in the metallurgical and pharmaceutical fields. The analysis was based on the micromechanical modelling of an idealised granular system in the framework of the multi-particle finite element method, in which particle deformation was fully taken into account. An adhesive interaction law, presented in Audry et al. (2024), was used in the purpose of estimating the averaged mechanical properties associated with the modelled elementary volume. The focus was put on tensile and highly deviatoric loadings, which are usually related to the failure of powder compacts. The specific contact area developed through inter-particles contacts was used as an indicator of the mechanical strength of the elementary volume. Threshold surfaces corresponding to yielding and contact decohesion mechanisms were plotted in the stress space.

Numerical modelling of contact adhesion in a random assembly of elastic–plastic particles

The prediction of tensile strength properties of powder compacts remains an important industrial issue. In particular, one of the main problems of the powder compaction process is the failure of compacts. Indeed, some powder compacts exhibit cracks which appear during compaction. Such defects occur due to localised tensile or shear stresses, for example close to geometrical singularities. They are also related to the ability of a powder to create enough adhesion at contacts between particles to withstand tensile stresses. Therefore, cracks are a consequence of phenomena occurring at the particle scale and below, down to the molecular scale. To help understanding this mechanism, a particle-scale, numerical method called the multi-particle finite-element method was developed using the finite-element software suite Abaqus (Abaqus 6.14 Documentation, 2016). Such a method allowed to explicitly model the microstructure of a granular media idealised as an assembly of elastic–plastic spheres. The particles were meshed such that their deformations were fully taken into account, using a continuum-mechanics-based material model. The interactions between particles were managed using finite-element contact formulations. A multi-scale, adhesive contact model was developed based on the literature and implemented into the multi-particle finite-element code. The contact model was based on a surface energy formulation weighted by the roughness model developed by Pullen and Williamson (1972). It introduced a novel aspect, the development of adhesion under the effect of external mechanical loads, which is consistent with the cold compaction process. This model was then applied to predict the mesoscopic properties of a packing of spheres, i.e. its response to mechanical stresses of any type, in particular strongly deviatoric stress paths. Such a method intends to be a help toward the development of an efficient continuum model for the modelling of the powder compaction process.

Digital twin enhanced quality prediction method of powder compaction process

During the powder compaction process, process parameters are required for product quality prediction. However, the inadequacy of compaction data leads to difficulties in constructing models for quality prediction. Meanwhile, the existing data generation methods can only generate required data partially, and fail to generate data for extreme operating conditions and difficult-to-measure quality parameters. To address this issue, a digital twin (DT) enhanced quality prediction method for powder compaction process is presented in this paper. First, a DT model of the powder compaction process with multiple dimensions is constructed and validated. Then, to solve the data inadequacy problem, data of process parameters are generated through an orthogonal experimental design, and are imported into the DT model to generate quality parameters, so as to obtain the virtual data. Finally, the quality prediction for the powder compaction process is achieved by the generative adversarial network-deep neural network (GAN-DNN) method. The effectiveness of the generated virtual data and the GAN-DNN method is verified through experimental comparison. On top of point-to-point validation, a quality prediction system applied in a powder compaction line is developed and implemented to demonstrate the end-to-end practicability of the proposed method.

New Die-Compaction Equations for Powders as a Result of Known Equations Correction: Part 2—Modernization of M Yu Balshin’s Equations

Based on the generalization of M. Yu. Balshin’s well-known equations in the framework of a discrete model of powder compaction process (PCP), two new die-compaction equations for powders have been derived that show the dependence of the compaction pressure p on the relative density ρ of the powder sample. The first equation, p=w(1−ρ0)(n−m)·(ρ−ρ0)n(1−ρ)m, contains, in addition to the initial density ρ0 of the powder in die, three constant parameters—w, n and m. The second equation in the form p=H1−ρ0b−c·ρ−ρ0b1−ρ0c−aρ−ρ0c also takes into account the initial density of the powder and contains four constant parameters H, a, b, and c. The values of the constant parameters in both equations are determined by fitting the theoretical curve according to these equations to the experimental powder compaction curve. The adequacy of the PCP description with these equations has been verified by approximating experimental data on the compaction of various powders, including usual metal powders such as iron, copper, and nickel, highly plastic powders such as tin and lead, a mixture of plastic powder (Ni) with non-plastic powder (Al2O3), nickel-plated alumina powder, as well as powder of a brittle compound, in particular titanium carbide TiC. The proposed equations make it possible to describe PCP with high accuracy, at which the coefficient of determination R2 reaches values from 0.9900 to 0.9999. The four-constant equation provides a very accurate description of PCP from start to finish when the density of the samples stops increasing once the pressure increases to an extremely high level, despite the presence of porosity.

New Die-Compaction Equations for Powders as a Result of Known Equations Correction: Part 1–Review and Analysis of Various Die-Compaction Equations

The well-known equations for the powder compaction process (PCP) in a rigid die published from the beginning of the last century until today were considered in this review. Most of the considered equations are converted into the dependences of densification pressure on the powder’s relative density. The equations were analyzed and their ability to describe PCP was assessed by defining the coefficient of determination when approximating experimental data on the compaction of various powders. It was shown that most of the equations contain two constants the values of which are determined by fitting the mathematical dependence to the experimental curve. Such equations are able to describe PCP with high accuracy for the compaction of powders up to a relative density of 0.9–0.95. It was also shown that different equations can describe PCP in the density range from the initial density to 0.9 with the same high accuracy, but when the process of compaction is extrapolated to higher values of density, the curves diverge. This indicates the importance of equations that can unambiguously describe PCP to a relative density equal to or close to 1.0. For an adequate description of PCP for relative density greater than 0.95, equations containing three or four constants have proven useful.

Automatic trajectory adaptation for the control of quality characteristics in a powder compaction process

The manufacturing process of sintered components requires the compaction of powder in a rigid die and the sintering of the resulting green parts. To produce green parts of the same constant quality over a long period of time, regular quality checks and trajectory adjustments are needed to account for changing operating conditions due to e.g. varying temperature, humidity, stroke rate, or powder quality. Also the first setup of the machine requires manual measurements and iterative adjustments of trajectory key points. To overcome these labour-intensive, manual measurements and adjustments, we propose an algorithm for the automatic adaptation of trajectory key-points that for the first time allows bringing and keeping more than one quality characteristic (mass and dimensions) fully automatically within predefined intervals. To safe costs, we further present two real-time capable, model-based solutions by employing grey-box and black-box models for the online estimation of the workpiece mass and height instead of their direct measurement. The grey-box model combines a filling and analytical compaction model and allows estimating mass and height rather than density as typically investigated in literature. The black-box model based on neural networks represents a complete novelty in the field as no similar data-driven approach could be found that aims at estimating mass and dimensions of green compacts. We finally compare the performance of these models to the baseline of sensor measurements as well as study their effect on the overall control performance. Results indicate that for both sensor-based and model-based solutions it is possible to reach and keep aforementioned quality characteristics within desired intervals. While overall the sensor-based approach performed best, also for the model-based approaches a good estimation performance is observed with the black-box model based on neural networks outperforming the grey-box model. While the black-box approach is fully data-driven and thus allows to widely avoid manual modelling activities, it still requires the presence of expensive sensors for capturing training data. The proposed grey-box approach, on the other hand, requires some manual modelling and model calibration activities, but provides a cost-effective solution to the problem and represents an alternative to more expensive, sensor-based implementations.

Reduced-order hybrid modelling for powder compaction: Predicting density and classifying diametrical hardness

Drawing on machine learning (ML) techniques and physics-based modelling, two feature-based reduced-order models are presented: one for the quantitative prediction of density and another for the classification of the diametrical hardness of pellets from a powder compaction process (pelleting). For interpretability, the models use as input only the parameters from a modified Drucker–Prager Cap (DPC) model calculated from process data monitoring and the applied maximal compression force. For quantitative density prediction, 8 features linked to first-principles models of powder compaction are generated, and the final model uses only 2. A critical part of the modelling, and also one of the main contributions, is a data augmentation step for the primary data set of this study by leveraging much smaller supplementary data sets that have measurements not present in the primary data set.The final results imply a significant reduction in the quantity of data needed for model input and cut down the cost of data acquisition, storage, and computational time. Additionally provided is a detailed analysis of the impact and relevance of the generated features on the model performance.The density prediction model, using only 2 features, reaches a mean absolute scaled error (MASE) of 12.9% and a mean absolute error (MAE) of 0.10 (where r2=0.975). The scaled (diametrical) hardness classifier has an F1 score of 0.915 using 4 features.

A multiscale framework for atomistic–continuum transition in nano-powder compaction process using a cap plasticity model

In this paper, a computational atomistic-continuum multiscale framework is presented for the simulation of the nano-powder compaction process using a cone-cap plasticity model. The atomistic representative volume element (RVE) comprises of nano-powder particles that is used to perform the molecular dynamics analysis in order to capture the mechanical behavior of nano-powder material. The periodic boundary condition is applied over the atomistic RVE to satisfy the inter-scale kinematic compatibility, and the stress tensor is derived according to the inter-scale energetic consistency principals from the nanoscale at each material point of the powder component. A multiscale framework is performed using the constitutive law of the coarse-scale domain enhanced by the molecular dynamics results of the fine-scale domain. The coarse-scale constitutive law is conformed to the cone-cap plasticity model as a robust and capable constitutive relation in modeling the powder compaction process, in which the cap plasticity parameters are determined using the data derived from the molecular dynamics simulations. The mechanical response of nano-powder particles within the RVE is obtained from the confining pressure test and true-triaxial test, where a sensitivity analysis is accomplished on the computed parameters of the cone-cap plasticity model. The enhanced cap plasticity model is then employed to simulate various industrial nano-powder components that illustrates the performance and efficiency of the proposed multiscale computational homogenization method.

Low-carbon footprint approach to produce recycled compacted concrete

Achieving a closed-loop recycling process with low CO2 emissions remains a challenge for the concrete industry. To improve the recycling of concrete debris, a powder compaction process for concrete waste was designed to obtain recycled compacted concrete (hereinafter referred to as compact) and thermal treatment was proposed to be utilized to improve its strength. However, non-specific investigations of treatment parameters, like-treatment temperature, and duration, do still exist, and the required high production pressure (100 MPa) is impracticable. Therefore, this study aims to evaluate the effectiveness of two novel treatments on compact in improving its strength and reducing its carbon footprint. First, the heat treatment process used in a previous study [1] was expanded by varying immersion durations and treatment temperatures. Second, autoclaving was employed to obtain a stronger compact with different treatment settings. Additionally, in both treatment processes, the efficacy of low production pressure (<100 MPa) was evaluated. For this, eighteen different concrete wastes, having different industrial wastes, like-fly ash, slag, were collected, crushed, and powdered to produce compacts. The treated compacts were characterized based on both compressive strength and carbon footprint to compare the environmental performance of a compact prepared via thermal treatments in the production phase. The test results revealed that increasing water immersion duration (to 48 h) during the heat treatment process improved the compact strength to up to 48 MPa, and autoclaving at higher temperatures (at 220 °C) resulted in a compact strength of up to 98 MPa. Additionally, a strength of 30 MPa was attained even at a low production pressure (10 MPa) after autoclaving. The estimated CO2 emissions of the compact production process developed in this study were as low as 70.6 kg/m3 of compact. At the present stage of the study, it can be deduced that the compact manufactured possesses potential for implementation in various non-structural applications, including the production of pavement blocks and bricks, with lower CO2 emissions.

粉体成形プロセスのデジタルツイン構築に向けた粉体シミュレーションの基盤技術の開発

粉体成形プロセスのデジタルツイン構築に向けた粉体シミュレーションの基盤技術の開発

Influence of the drug deformation behaviour on the predictability of compressibility and compactibility of binary mixtures

Various studies investigate the predictability of the compressibility and compactibility of tablet formulations based on the behaviour of the pure materials. However, these studies are limited to a few materials so far probably because of the complexity of the powder compaction process. One approach preventing the excessive increase in complexity is the extension of the investigations from pure materials to binary powder mixtures. The focus of this study is on the predictability of the compressibility and compactibility of binary mixtures consisting of an active pharmaceutical ingredient (API) and the excipient microcrystalline cellulose. Three APIs with markedly different deformation behaviour were used. The API concentration and type are systematically varied. For all three material combinations it is found that the in-die compressibility of the binary mixtures can be precisely predicted based on the characteristic compression parameters of the raw materials using the extended in-die compression function in combination with a volume-based linear mixing rule. Since the tablet porosity (out-of-die) also follows a linear mixing rule, the predictability can be further extended using the method of Katz et al. In contrast, the influence of the API concentration on compactibility or rather on tablet tensile strength is non-linear and strongly dependent on the deformation behaviour of the API, making the predictability more difficult. Neither the approach of Reynolds et al. nor this of Kuentz and Leuenberger are able to predict the compactibility when clear deviations from a linear mixing rule appear.

Experimental and numerical investigations on electromagnetic powder compaction of Aluminium 6061 alloy powder

The present research's objective is to investigate the electromagnetic radial powder compaction process and its effect on the densification, microstructure and mechanical properties of the Al 6061 alloy powder. Cylindrical product has been prepared from Al 6061 powder using the electromagnetic powder compaction method. In this method, electromagnetic force shrinks the packing tube and utilises the deformation of the tube to compact the Al 6061 powder. The electromagnetic forces were generated between the field shaper's inner cylindrical surface and the outer surface of the packing tube when a high voltage current is flowing through the solenoid coil. In this study, the Al 6061 powder is compacted at various discharge voltages such as 13 kV, 14 kV, 15 kV and 16 kV using a 20 kV and 40 kJ capacity electromagnetic forming machine. Sintering is performed on the compacted samples at 620 °C for 1 h in an N2 tubular furnace. The simulation was carried out using loosely coupled multi-physics software, and simulated results were validated with the experimental results. Ansys Maxwell is used to analyse the electromagnetic field, and Ls-Dyna is used for structural analysis. To describe the deformation behaviour of the packing tube, the Cowper –Symonds model was used. The deformation in the compact and stress-strain variation was analysed using simulation results and experimental results. The effect of field shaper on powder compaction is investigated using the magnetic field analysis of the Ansys Maxwell results. The velocity of the packing tube is analysed for various input discharge voltages. The Vickers micro-hardness of electromagnetic powder compacted samples increases with compaction voltage. Finally, the results predicted by numerical simulation were verified with experimental results and found in good agreement.

Effect of Pressure Load on the Physical Properties of ZTA-TiO&lt;sub&gt;2&lt;/sub&gt;-Cr&lt;sub&gt;2&lt;/sub&gt;O&lt;sub&gt;3&lt;/sub&gt;

ZTA is considered as one of the most popular ceramic composites that are used for cutting tools due to their excellent properties. Consistent efforts should be expanded to achieve improvements in toughness and strength, and thus help them achieve a longer tool life. However, powder compaction process has been found to be a limiting factor in the production of a defect-free ceramic pellet where the green product often ruptures immediately after the compaction process or sintering process. This may be contributed by uneven distribution of pressure load, thus affecting the particles packing and properties of final product. As a solution, the present work aims to study the effect of different compaction pressure on the physical properties of ZTA-TiO2-Cr2O3 ceramic composite to establish a defect-free cutting insert. The samples were fabricated by solid state processing, subjected to pressure loads varied from 200 MPa-350MPa, followed by sintering at 1600°C for 1 hour. The sintered samples were characterized accordingly. The results showed significant enhancement in density and hardness with increasing compaction pressure from 200 MPa to 300 MPa. On the other hand, further increment of pressure deteriorates the properties of the samples. These were due to the excessive external pressure which caused a very tight compaction in the mold, resulted in elastic expansion of the compact and sliding of particles as the pressure is removed. In conclusion, ZTA-TiO2-Cr2O3 subjected to 300 MPa compaction pressure showed the most optimal properties with the highest density (4.58 g/cm3) and hardness (2001 HV).

Predicting impact strength and hardness of aluminium & tungsten carbide nano-composite synthesized by PM

This Study deals with mechanical and microstructural properties with pure aluminum and tungsten composite fabricated by powder compaction process. The scope of the research work is the production and characterization of Al matrix composites reinforced with WC ceramic nanoparticles. The synthesis process was powder metallurgy. Compacted specimens of Aluminum with varying tungsten carbide percentages and varying APS are tested using impact testing machine. Simulations for the impact tests were performed on composite specimens prior to actual fabrication and mechanical testing. Good correlation was observed between simulated specimens and fabricated specimens. Significant differences in the impact strength values were observed.

Upotreba simulatora kompaktiranja za karakterizaciju kompresije praškova - prednosti i ograničenja

Compaction simulators are designed as machines which can provide an in-depth analysis of the powder compaction process. Characterization of the powder compression and compaction process, as well as material characterization, play an important role in the formulation and manufacturing process design and development, as well as in creating a strong knowledge basis for the scale-up of the tablet compression and troubleshooting in further stages of the product lifecycle. Although compaction simulators are designed to simulate the compression process on high-speed tablet-presses, with the advantages of a small quantity of material needed and highly sophisticated instrumentation, there are certain limitations in the extrapolation of the process parameters from these machines to high-speed rotary tablet presses. However, the advantage of the use of compaction simulators for studying basic compression and compaction mechanisms, identification of critical material attributes and critical process parameters ranges, and their relations with tablet characteristics and critical quality attributes of pharmaceutical products is clear, compared to the use of small excentre tablet presses, and complementary to the use of small rotary tablet presses. This scientific paper provides an overview and examples of the different advantages provided by the instrumentation of compaction simulators, including certain limitations in their exploitation.

Non-coupled finite element modelling of electromagnetic compaction of Al 6061 powder in Al 6063 tube

Electromagnetic powder compaction is considered a high strain and high-speed powder forming technique. The method uses the Lorentz forces for compacting powder to obtain near net shape and high strength compact through the PM route. This process can be classified as a contactless powder compaction technique since no physical punch is used to form powder for compaction. All kinds of materials, irrespective of the powder particle's hardness and size distribution, can be compacted using this technique. Few materials are tough to compact due to their higher hardness as well the frictional forces are very high during the compaction of Nanosized metallic powder. These barriers can be easily overcome by using high velocity and energy, such as the electromagnetic forming technique. In this paper, a non-coupled finite element model is developed to simulate the electromagnetic powder compaction process of pure Aluminium. ANSYS-Maxwell is used to investigate the electromagnetic field distribution in electromagnetic powder compaction tooling setup. The Geologic Cap model was used in the LS-Dyna Multi-physics solver to describe powder deformation during the compaction process. The Johnson-Cook plasticity model describes the deformation behaviour of the Al 6063 packing tube. Finally, the developed simulation model is validated with experimental results of aluminium powder compacts at 12 kV and 13 kV. The powder compaction experiments were carried out using a 40 kJ capacity electromagnetic forming machine. It found that the simulation results agreed with experimental data results. The comparison is made between the final diameters of the compact obtained through simulation and experiments.

Evaluation and parameter analysis of compaction equations applied to titanium powder

ABSTRACT Titanium is widely used in the fields of medicine, industry, and biological science due to its excellent properties. In addition, titanium powder metallurgy (PM) is widely used in production because it could considerably reduce the cost. The most critical step in PM is powder compaction. Thus, the compaction equation is highly important in the prediction and analysis of powder compaction process. In this paper, the experimental data of titanium hydride powder and hydrogenated-dehydrogenated titanium powder were fitted using different compaction equations, and all the equations could obtain a high fitting degree (R 2 > 0.99) and a small error. The linear compaction equation could distinguish the powder type and different particle size distribution forms in the same type of powder through fitting parameters. The nonlinear compaction fitting equation could also analyse the contribution of powder densification mechanism through parameter calculation.

The mechanical response of micron-sized molecular crystals

Microstructures and corresponding properties of compacted powders ultimately depend on the mechanical response of individual particles. In principle, computational simulations can predict the results of powder compaction processes, but the selection of appropriate models for both particle–particle interactions and particle deformations across all relevant length scales remain nontrivial tasks, especially in material systems lacking detailed mechanical property information. The work presented here addresses these issues by conducting uniaxial compressions in situ inside of a scanning electron microscope to characterize the mechanical response of individual micron-sized particles of a molecular crystal, hexanitrohexaazaisowurtzitane (CL-20). This experimental approach enabled the collection of quantitative force and displacement data alongside simultaneous imaging to capture morphology changes. The results reveal information about elastic deformation, yield, plastic deformation, creep, and fracture phenomena. Accordingly, this work demonstrates a generalizable approach for assessing the mechanical response of individual micron-sized molecular crystal particles and utilizing those responses in particle-level models.Graphic abstract

Correlation mechanism between force chains and friction mechanism during powder compaction

The relation between friction mechanism and force chains characteristics has not yet been fully studied in the powder metallurgy research area. In this work, a uniaxial compression discrete element model is established based on the compaction process of ferrous powder. Furthermore, the correlation mechanism between force chains and the friction mechanism during powder compaction is investigated. The simulation results reveal a strong correlation between the variation of the friction coefficient and the evolution of force chains. During the powder compaction, the friction coefficient would eventually tend to be stable, a feature which is also closely related to the slip ratio between particles. The side wall friction and the friction between particles would have an important effect on the direction of force chain growth in about one-third of the area near the side wall. The research results provide theoretical guidance for improving the densification process of the powder according to the force chain and friction.