Strip Drawing Test Research Articles

The role of manufacturing-induced texture on the tribological performance of cold work tool steels

Manufacturing operations produce surface characteristics that, although stochastic, can significantly affect functionality, especially in forming tools, impacting contact and lubrication conditions during operation. This study investigates the influence of stochastic microtextures resulting from milling on the tribological performance of cold work tool steels with two different carbon contents (0.8 and 2 wt%). Different surface textures were observed resulting from the different C contents, with 3D roughness parameters indicating rougher surfaces for the 2.0% wt. C steel. Tribological behavior was assessed using the strip drawing test to analyze friction, wear coefficients, and wear mechanisms. Surface analysis before and after testing was executed employing SEM, EDX, and CLSM, with CLSM also used to determine 3D roughness parameters of the worn tracks. Post-test macrographic analyses and 2D roughness measurements were conducted on the pulled sheets. Tribological test data revealed lower friction and wear coefficients for the 2.0 wt% C tool steel, with susceptibility to abrasion wear, while the 0.8 wt% C tool exhibited a higher tendency towards adhesion wear. Post-test analysis suggested smoother surfaces for the 2.0 wt% C steel compared to the 0.8 wt% C steel. Macrographic analysis showed no visible wear marks on sheets tested with the 2.0 wt% C steel, contrasting with wear grooves visible on sheets pulled against the 0.8 wt% C steel. Additionally, 2D roughness measurements indicated higher roughness after pulling against the 0.8 wt% C tool compared to the 2.0 wt. C tool. Overall, the study demonstrates that manufacturing-induced textures without the need of post-manufacturing texturing influence the tribological performance of the evaluated steels, opening an avenue to be explored to improve the tribological performance of forming tools.

Tribological investigations of water-based lubricants for application in the deep drawing process

This paper describes the tribological investigation of water-based lubricants in the context of a deep drawing process. Therefore, different methods were conducted in order to determinate the suitability of these lubricants for a deep drawing process. Three lubricant manufacturers each provided their lubricants as part of this work. The sheet materials investigated are an aluminum material (AA6014) and two steel materials (DC04, DP800), each with a thickness of 1.5 mm. All sheet materials were examined in the as-delivered condition as part of this work. The hypothesis for this research proposal is that it is possible to achieve comparable tribological properties in sheet metal forming using water-based lubricants as when using mineral oil-based lubricants. The aim is to optimize a tribological system for water-based lubricants when used as additional lubrication in order to replace mineral oil-based lubricants and, as a result, to shorten the representative process chain by one process step (cleaning). In the course of this work, topographical measurements of the sheet materials were carried out in order to investigate the lubricant holding capacity of the sheet materials. Furthermore, strip drawing tests were performed to determine the friction coefficients of the different lubricant-sheet combinations. The final step was to conduct deep-drawing tests to determine the limits of use of the water-based lubricants by continuously increasing the holding-down force.

Tool surface texturing by shot peening: initial results and lessons learned

Abrasive and adhesive wear is a major issue in sheet metal forming processes. Although different solutions exist to reduce its impact, there is still room for progress. Surface texturing presents a big potential for tribological behaviour improvement by introducing oil retention voids on the surface. However, the economic efficiency of the surface functionalization is paramount for its implementation in industrial processes. In the present study, a widely known technology, shot peening, is applied for the creation of the voids. A grinding+polishing process is then applied to ensure a flat load bearing area. The textures are generated in 1.2379 tool steel blocks hardened at 60 HRc that emulate the tool. Different shot peening strategies are evaluated by carrying out strip drawing tests with AA5754H111 aluminium alloy sheets. Contact pressures up to 25 MPa are applied and the adhesive wear reduction potential is evaluated. First results point out the potential of this solution although the applied shot peening strategy needs to be carefully defined.

Lubricant savings in sheet metal forming through thermally oxidized wear protection layers

Increasing demands on quality, variety of shapes and complexity of deep-drawn components with simultaneous price stability make the development of innovative solutions in the field of deep-drawing indispensable. For ecological and economic reasons, there is a great interest in reducing the amount of lubricant required in forming processes to a minimum. In this work, tool coatings for forming tools are to be investigated and further developed in order to use their friction-reducing properties on the tribo-system and thus enable a reduction in the use of lubricants. For this purpose, in this research strip drawing tests are carried out to investigate the friction-influencing properties of different coatings and their potential for lubricant saving. Therefore, cylindrical forming heads are provided with different coating systems. Strips of aluminum sheet are drawn around the forming heads at an angle of 90°. The amount of lubricant applied is varied. Friction values are recorded and analyzed for each system. Wear mechanisms are identified, examined and evaluated macroscopically and microscopically. For this purpose, energy dispersive X-ray spectroscope (EDX) and scanning electron microscope (SEM) examinations are carried out. A statement on the potential of the investigated coatings for lubricant saving is derived from the results.

Analysis of the friction performance of deep-drawing steel sheets using network models

AbstractThis article presents the results of pilot studies on the lubrication of the blankholder zone in sheet metal forming using a pressurised lubricant. The authors invented a method and built a special tribometer for pressure-assisted lubrication. This approach reduces friction in sheet metal forming processes compared to conventional lubrication. Moreover, the artificial neural network approach combined with a force-directed Fruchterman-Reingold graph algorithm and Spearman’s correlation was used for the first time to analyse the relationships between the friction process parameters and the output parameters (the coefficient of friction and the resulting surface roughness of the sheet metal). The experimental tests were conducted utilising strip drawing on four grades of steel sheets known to be outstanding for deep-drawing quality. Different oils, oil pressures and contact pressures were used. Artificial neural network models were used for the first time to determine these relationships in a strip drawing test where every parameter is represented by one node, and all nodes are connected by edges with each other. R Software version 4.2.3 was used to construct the network using the ‘qgraph’ and ‘networktools’ packages. It was found that friction conditions had a highly significant negative correlation with coefficient of friction (COF) and a moderately significant negative correlation with the final surface roughness. However, the initial surface roughness of the as-received sheets had a negative correlation with the COF and a positive one with the resulting surface roughness of the sheet metal. The parameters most related to the COF are the strength coefficient, the ultimate tensile strength and the friction conditions (dry friction or pressurised lubrication). Spearman’s correlation coefficients showed a strong correlation between the kinematic viscosity and the friction conditions.

The Comparison of the Multi-Layer Artificial Neural Network Training Methods in Terms of the Predictive Quality of the Coefficient of Friction of 1.0338 (DC04) Steel Sheet.

Friction is one of the main phenomena accompanying sheet metal forming methods, affecting the surface quality of products and the formability of the sheet metal. The most basic and cheapest way to reduce friction is to use lubricants, which should ensure the highest lubrication efficiency and at the same time be environmentally friendly. Due to the trend towards sustainable production, vegetable oils have been used in research as an alternative to petroleum-based lubricants. The analysis of friction in sheet metal forming requires an appropriate tribotester simulating the friction conditions in a specific area of the sheet metal being formed. Research has used a special strip drawing tribometer, enabling the determination the value of the coefficient of friction in the blankholder zone in the deep drawing process. Quantitative analysis of the friction phenomenon is necessary at the stage of designing the technological process and selecting technological parameters, including blankholder pressure. This article presents the results of friction testing of 1.0338 (DC04) steel sheets using a strip drawing test. The experimental tests involved pulling a strip of sheet metal between two countersamples with a rounded surface. The tests were carried out on countersamples with different levels of roughness for the range of contact pressures occurring in the blankholder zone in the deep drawing process (1.7-5 MPa). The values of the coefficient of friction determined under dry friction conditions were compared with the results for edible (corn, sunflower and rapeseed) and non-edible (Moringa, Karanja) vegetable lubricants. The tested oils are the most commonly used vegetable-based biolubricants in metal forming operations. Multi-layer artificial neural networks were used to determine the relationship between the value of the contact pressure, the roughness of the countersamples, the oil viscosity and density, and the value of the coefficient of friction. Rapeseed oil provided the best lubrication efficiency during friction testing for all of the tested samples, with an average surface roughness of Sa 0.44-1.34 μm. At the same time, as the roughness of the countersamples increased, a decrease in lubrication efficiency was observed. The lowest root mean squared error value was observed for the MLP-4-8-1 network trained with the quasi-Newton algorithm. Most of the analysed networks with different architectures trained using the various algorithms showed that the kinematic viscosity of the oil was the most important aspect in assessing the friction of the sheets tested. The influence of kinematic viscosity on the value of the coefficient of friction is strongly dependent on the surface roughness of the countersamples.

Numerical analysis of the dependence of damage on friction during deep drawing of asymmetric geometries

The manufacturing of three-dimensional sheet metal components, such as car body parts, heavily relies on deep drawing. With the increasing demand for lightweight measures in the automotive industry due to CO2 limitation requirements, various methods are currently employed to reduce the weight of deep drawn components. However, these methods often overlook the potential for influencing the stress-strain dependent damage state within the component, even though it can greatly affect its performance in subsequent applications, and thus offers lightweight potentials. Friction between the deep drawing tools and the sheet metal is a key factor influencing the stress-strain state, and hence, represents a lever that can be utilized to manipulate the damage state in the component. This paper focuses on the numerical analysis of the dependence of damage on friction during deep drawing. Therefore, a rectangular geometry with an asymmetrical material flow is numerically investigated. A friction ratio is introduced with different constant friction coefficients for the corner of the tools and the straight sides. The established load paths at a chosen reference point are then considered in the form of selected stress and strain characteristics and the numerically predicted damage state is compared. The results are used to derive a recommended friction ratio that leads to less damage in the corner of the geometry. Afterwards strip drawing tool surfaces are modified to manipulate their friction properties using machine hammer peening. Subsequently, the influence of the structures of the strip drawing tool surfaces is quantified using strip drawing tests. The identified contact normal stress dependent friction coefficients are then implemented in the numerical simulation and the established numerical predicted damage state is examined to gain a more comprehensive understanding of how the friction ratio and the structure of the tool surfaces influence the damage state.

Application of categorical boosting to modelling the friction behaviour of DC05 steel sheets in strip drawing test

It is challenging to model the coefficient of friction, surface roughness, and related tribological processes during metal contact because of flattening, ploughing, and adhesion. It is important to choose the appropriate process parameters carefully when creating analytical models to overcome the challenges posed by complexity. This will ensure the production of sheet metal formed components that meets the required quality standards and is free from faults. This research analyses the impacts of nominal pressure, kinematic viscosity of lubricant, and lubricant pressure on the coefficient of friction and average roughness of DC05 deep-drawing steel sheets. The strip drawing test was used to determine the coefficient of friction. This work utilises the Categoric Boosting (CatBoost) machine learning algorithm created by Yandex to estimate the COF and surface roughness, intending to conduct a comprehensive investigation of process parameters. A Shapley decision plot exhibits the coefficient of friction prediction models via cumulative SHapley Additive exPlanations (SHAP) data. CatBoost has outstanding prediction accuracy, as seen by R2 values ranging from 0.955 to 0.894 for both the training and testing datasets for the COF, as well as 0.992 to 0.885 for surface roughness.

Frictional characteristics of EN AW-6082 aluminium alloy sheets used in metal forming

This article is devoted to testing EN AW-6082 aluminium alloy sheets in friction pair with NC6 (1.2063) tool steel. A special tribometer designed to simulate the friction conditions in sheet metal forming processes was used for friction testing. The research aimed to determine the influence of contact pressure, surface roughness of the tool, and lubrication conditions on the value of the coefficient of friction in the strip drawing test. Three grades of typical petroleum-based lubricants with kinematic viscosities between 21.9 and 97 mm2/s were used in the tests. The surface morphologies of the sheet metal after the friction process were observed using a scanning electron microscope. A tendency for the coefficient of friction to decrease with increasing contact pressure was observed. LHL32 and 75W-85 oils lost their lubricating properties at a certain pressure value and with further increase in pressure, the coefficient of friction value tended to increase. The 10W-40 oil with the highest viscosity reduced the coefficient of friction more intensively than the LHL32 oil.

Mechanism for friction reduction of aluminum alloy at high-pressure and ultra-low temperature

Temperature and pressure have a significant impact on friction in aluminum alloy ultra-low temperature forming. In this paper, cryogenic strip drawing test (CSDT), morphologies analysis and microstructure characterization were used for friction mechanism investigation of aluminum alloy under different temperatures and pressures. The findings indicated that the coefficient of friction (COF) first increased and then decreased as pressure increased. From 2 to 10 MPa, the lowest COF was observed at −190 °C. The formation of fine deformation microstructure enhanced surface material plasticity and resistance to deformation leading to reduced adhesive friction or plowing friction, resulting in low COF at high-pressure and ultra-low temperature. Furthermore, higher temperatures and pressures increased the adhesion, which was detrimental to prolonging the service life of die.

Analysis of Surface Topography Changes during Friction Testing in Cold Metal Forming of DC03 Steel Samples

Predicting changes in the surface roughness caused by friction allows the quality of the product and the suitability of the surface for final treatments of varnishing or painting to be assessed. The results of changes in the surface roughness of DC03 steel sheets after friction testing are presented in this paper. Strip drawing tests with a flat die and forced oil pressure lubrication were carried out. The experiments were conducted under various contact pressures and lubricant pressures, and lubrication was carried out using various oils intended for deep-drawing operations. Multilayer perceptrons (MLPs) were used to find relationships between friction process parameters and other parameters (Sa, Ssk and Sku). The following statistical measures of contact force were used as inputs in MLPs: the average value of contact force, standard deviation, kurtosis and skewness. Many analyses were carried out in order to find the best network. It was found that the lubricant pressure and lubricant viscosity most significantly affected the value of the roughness parameter, Sa, of the sheet metal after the friction process. Increasing the lubricant pressure reduced the average roughness parameter (Sa). In contrast, skewness (Ssk) increased with increasing lubrication pressure. The kurtosis (Sku) of the sheet surface after the friction process was the most affected by the value of contact force and lubricant pressure.

Effect of Process Variables on Interface Friction Characteristics in Strip Drawing of AA 5182 Alloy and Its Formability in Warm Deep Drawing

Warm forming is widely used to enhance the formability of aluminum alloy sheets. In warm deep drawing, the process variables significantly affect frictional characteristics at the tool–blank interface. It has been a conventional approach to use a constant value of friction coefficients in the finite element (FE) simulations. However, this can occasionally result in suboptimal accuracy of the predictions. In the present work, strip drawing tests were carried out on AA5182 aluminum alloy sheets to investigate the effect of important process variables, namely, temperature, contact pressure, and drawing speed, on the friction coefficient in the warm forming temperature range (100–250 °C) under lubricated condition. The results obtained from the strip drawing tests were used for defining the friction conditions in the simulation of warm deep drawing of cylindrical cups incorporating the variation of the friction coefficient with contact pressure and speed at different temperatures. The Barlat89 yield criterion was used to define the effect of anisotropy in the material. The Voce hardening law and Cowper–Symonds model were used to incorporate the effect of strain hardening and strain rate, respectively, in the simulation. Drawability and peak force were compared with the predictions when a constant friction coefficient was assumed. Warm deep drawing experiments were conducted to validate the predicted drawability and load–displacement curves. It is clearly observed that the accuracy of prediction of the limiting drawing ratio and peak load through simulations is improved by incorporating the effect of pressure and speed on friction coefficient as it captures the local variations of friction during warm deep drawing precisely, rather than assuming a constant average friction coefficient at all the tool–blank contact areas.

An Investigation into the Friction of Cold-Rolled Low-Carbon DC06 Steel Sheets in Sheet Metal Forming Using Radial Basis Function Neural Networks

This article presents the friction test results for cold-rolled low-carbon DC06 steel sheets, which are commonly processed into finished products using sheet metal forming methods. A strip drawing test with flat dies was used in the experimental tests. The strip-drawing test is used to model the friction phenomena in the flange area of the drawpiece. The tests were carried out using a tester that enabled lubrication with a pressurised lubricant. The friction tests were carried out at different nominal pressures, oil pressures, and friction conditions (dry friction and oil lubrication). Oils destined for deep-drawing operations were used as lubricants. Neural networks with radial base functions (RBFs) were used to explore the influence of individual friction parameters on the value of the coefficient of friction (COF). Under lubrication with both oils considered, the value of the COF increased with decreasing oil pressure. This confirms the correctness of the concept of the device for reducing friction in the flange area of the drawpiece. The developed concept of pressurised lubrication is most effective at relatively small nominal pressures of 2–4 MPa. This range of nominal pressures corresponds to the actual nip pressures when forming deep-drawing steel sheets. Under conditions of dry friction, the values obtained for the COF rise above 0.3, while under lubrication conditions, even without pressure-assisted lubrication, the COF does not exceed 0.2. As the nominal pressure increases, the effectiveness of the lubrication exponentially decreases. It was found that the Sq parameter carries the most information regarding the value of the COF. The RBF neural network with nine neurons in the hidden layer (RBF-8-9-1) and containing the Sq parameter as the input was characterised by an R2 of 0.989 and an error of 0.000292 for the testing set.

Analysis of the Lubrication Performance of Low-Carbon Steel Sheets in the Presence of Pressurised Lubricant

Abstract In sheet metal forming processes, friction increases the force parameters of the forming process and produces a deterioration in the quality of the surface of the components. The basic way to reduce the unfavourable impact of friction is to lubricate the sheet metal surface with commercial oils. This article presents the results of experimental studies and analysis of variance (ANOVA) of the friction of DC01 low-carbon steel sheets using a strip drawing test. For these tests, a special device was built containing countersamples with a flat surface made of 145Cr6 steel covered with a protective AlTiN coating. Lubricants of different viscosities were fed into the contact zone under forced pressure. The effect of contact pressure on the value of the coefficient of friction was also determined. The predicted R² of 0.9227 was in reasonable agreement with the adjusted R² of 0.9411 confirming that the ANOVA model was reliable. It was found that increasing the lubricant pressure had a beneficial effect in reducing the value of the coefficient of friction. The higher the contact pressure, the more effectively the pressurised oil reduced the value of the coefficient of friction.

Simulation of deep drawing of dual phase steel sheets incorporating tribological behaviour predicted by advanced friction modelling

In a deep drawing process, friction at the sheet metal-die contact interface affects the material flow in the flange as well as at the die entry affecting product quality significantly. The accuracy of predicted drawing force and thinning in deep drawing simulation strongly depends on friction modelling. The Coulomb friction model with a constant coefficient of friction is generally assumed in simulations. In reality, the actual friction coefficient depends on process variables such as local contact pressure, relative sliding velocity, and strain in the sheet material. In this work, an approach is presented for deep drawing simulation of dual phase (DP600) steel sheets incorporating the effect of these variables on the friction coefficient. Strip drawing tests under conditions similar to that exist in the flange area during deep drawing have been carried out. Deep drawing simulations have been performed using two friction models taking into consideration the variation of friction coefficient with respect to pressure and velocity. The predicted punch force and thickness variation are validated using deep drawing experiments. A considerable improvement in the accuracy of predicted results has been observed when compared to a constant coefficient of friction.

Novel tool steel for application in hot stamping

Hot stamping is a commonly used procedure to manufacture components from high strength steels, which are used for parts of car bodies. Against the background of production efficiency and costs, there is a number of factors which determine the performance of tools used in hot stamping, e.g. cycle time in production and lifetime of the tools. Main requirement is a high wear resistance, while additional properties such as high thermal conductivity can be considered being beneficial. Many steel grades, which are currently applied in hot stamping tools (e.g. hot work tool steel 1.2367) contain high amounts of alloying elements which gives them good mechanical properties, particularly at high temperatures. However, these steels in turn suffer from a rather low thermal conductivity and only moderate wear resistance. Optimization of the balance of mechanical properties, wear resistance, and thermal conductivity can lead to a better general performance of hot working tool steels used in hot stamping applications. In this study, a novel tool steel is characterized with special focus on properties relevant for hot stamping tools. Results are compared to those of reference hot work tool steels. Wear tests that were conducted in the framework of this paper include laboratory setups like ASTM G65 / G75 and high-temperature strip-drawing test setups to simulate the conditions of the process closer to reality. Results show that the novel tool steel is characterized by an increased wear resistance in combination with a higher thermal conductivity compared with common hot work tool steels. Furthermore it is approved that a wide range of desired properties can be adjusted in this alloy via heat treatment. The favourable combination of properties makes the novel tool steel suitable for application in hot stamping tools.

On the Use of Advanced Friction Models for the Simulation of an Industrial Stamping Process including the Analysis of Material and Lubricant Fluctuations

The use of numerical simulations for tool tryout and process control is becoming increasingly prevalent. In this work, the deep drawing process of a car inner door panel of DC06 mild steel is numerically analyzed and compared with industrial process results. Five batches of DC06 material were analyzed mechanically and tribologically. Diverse tribological models were developed based on experimental strip drawing tests, where a Coefficient of Friction (CoF) was obtained as a function of contact pressure, sliding velocity, and amount of lubricant. A topography analysis was defined to compare material batches and to replicate industrial tool conditions. The simulation was fed with three tribological models: constant (CoF 0.15), Filzek pressure and velocity dependent, and TriboForm with lubrication zones. Thinning, Forming Limit Diagram (FLD) and draw-in were used as indicators for the comparison. Using the industrial tool, both FLD and draw-in were measured and compared with the numerical models. The constant model predicted the most conservative strain state and also differed most from the experimental results. The P-v-dependent and TriboForm models more accurately predicted the experimental results. This work highlights the importance of considering more complex tribological models to feed numerical simulations to yield results closer to real process conditions.

Tribology in Warm and Hot Aluminum Sheet Forming: Transferability of Strip Drawing Tests to Forming Trials

For conventional sheet metal forming at room temperature, numerous tribometers have been developed in the 20th century. At the present state of the art, there are some challenges for tribometry in warm and hot forming processes of high‐strength aluminum (e.g., EN AW‐7075). Especially for nonisothermal processes with heated sheets and cooled dies, the tribological design is a major challenge, which needs to be addressed by investigations with adapted tribometers. Herein, the transferability of friction and wear behavior of three different lubricants and temperatures is investigated. Therefore, tribometer test results are compared with real forming trials in combination with thermomechanical finite element simulations. Both the behavior of different lubricant types and the characteristics of tool lubrication in sheet metal forming are discussed.

Friction Behaviour of 6082-T6 Aluminium Alloy Sheets in a Strip Draw Tribological Test.

Aluminium alloy sheets cause many problems in sheet metal forming processes owing to their tendency to gall the surface of the tool. The paper presents a method for the determination of the kinematic friction coefficient of friction pairs. The determination of coefficient of friction (COF) in sheet metal forming requires specialised devices that 'simulate' friction conditions in specific areas of the formed sheet. In this article, the friction behaviour of aluminium alloy sheets was determined using the strip drawing test. The 1-mm-thick 6082 aluminium alloy sheets in T6 temper were used as test material. Different values for nominal pressures (4.38, 6.53, 8.13, 9.47, 10.63, and 11.69 MPa) and different sliding speeds (10 and 20 mm/min.) were considered. The change of friction conditions was also realised with several typical oils (hydraulic oil LHL 32, machine oil LAN 46 and engine oil SAE 5W-40 C3) commonly used in sheet metal forming operations. Friction tests were conducted at room temperature (24 °C). The main tribological mechanisms accompanying friction (adhesion, flattening, ploughing) were identified using a scanning electron microscope (SEM). The influence of the parameters of the friction process on the value of the COF was determined using artificial neural networks. The lowest value of the COF was recorded when lubricating the sheet metal surface with SAE 5W40 C3 engine oil, which is characterised as the most viscous of all tested lubricants. In dry friction conditions, a decreasing trend of the COF with increasing contact pressure was observed. In the whole range of applied contact pressures (4.38-11.69 MPa), the value of the COF during lubrication with SAE 5W40 C3 engine oil was between 0.14 and 0.17 for a sliding speed of 10 mm/min and between 0.13 and 0.16 for a sliding speed of 20 mm/min. The value of the COF during dry friction was between 0.23 and 0.28 for a sliding speed of 10 mm/min and between 0.22 and 0.26 for a sliding speed of 20 mm/min. SEM micrographs revealed that the main friction mechanism of 6082-T6 aluminium alloys sheet in contact with cold-work tool steel flattens surface asperities. The sensitivity analysis of the input parameters on the value of COF revealed that oil viscosity has the greatest impact on the value of the COF, followed by contact pressure and sliding speed.

Tribological Aspects of Sheet Titanium Forming.

Friction, wear, and lubrication are inherent to all metal-forming processes. Unfortunately, they are particularly troublesome when forming titanium materials, which tend to form titanium buildup on the working surfaces of the forming tools. Lubrication is one of the most effective ways to separate contacting surfaces and eliminate galling, thus reducing tool wear. The paper presents the tribological aspects of titanium sheets forming using environmentally friendly lubricants with the addition of boric acid. The lubricant's effectiveness was assessed on the basis of technological tests, such as the strip drawing test, the Erichsen cupping test, and the formation of spherical drawn parts in industrial conditions. Moreover, the results of the numerical simulation of forming a titanium hat-shaped part are presented. Numerical calculations of forming processes were performed using the PamStamp 2G system based on the finite element method. Both experiments and numerical analyses showed the positive effect of lubricants with boric acid on sheet titanium forming.