Radial-axial Ring Rolling Process Research Articles

Rolling Eccentric Steel Rings on an Industrial Radial–Axial Ring Rolling Mill

Various industries, including mechanical engineering, utilize steel rings featuring variable cross-sectional profiles, such as eccentric rings. Presently employed methods for producing eccentric rings possess drawbacks like restricted geometries, significant material wastage or uneven microstructures. The radial–axial ring rolling process serves to create seamless rolled steel rings with near-net-shaped cross-sections. A novel technique involves achieving eccentricity by dynamically adjusting the mandrel’s position during the ring rolling process. This method’s fundamental feasibility has previously been showcased using a blend of oil clay and a labor test bench. Transferring the possibility of manufacturing eccentric rings on industrial radial–axial ring rolling mills would expand the product range of ring manufacturers without encountering drawbacks associated with existing manufacturing processes. The objective of this paper is to demonstrate the basic feasibility of the concept of an industrial radial–axial ring rolling mill. In the first step, FEA simulation studies were carried out to develop the rolling strategy and estimate the achievable eccentricity on the institute’s radial–axial ring mill. Subsequently, the rolling strategy was implemented on an industrial ring rolling mill with the help of a unique technology module programmed in C++. Finally, an eccentric ring was ring rolled and compared with the FEA simulation, and the reproducibility was demonstrated to be successful.

Effects of the Radial-Axial Ring Rolling Process on the Mechanical Properties and Microstructure of Centrifugally Cast AM60 Magnesium Rings

Effects of the Radial-Axial Ring Rolling Process on the Mechanical Properties and Microstructure of Centrifugally Cast AM60 Magnesium Rings

Extreme gradient boosting-inspired process optimization algorithm for manufacturing engineering applications

Design and process optimization are key aspects of manufacturing engineering. This contribution details a machine learning (ML) methodology capable of learning from simulation results, experimental data, or sensor signals, and able to predict and optimize specific user-defined process and design parameters. The prediction-optimization algorithm is based on an enhanced Extreme Gradient Boosting (XGB) algorithm, highly responsive and accurate even for large datasets and complex variable interactions. Once the XGB function is trained, the optimization is carried out by a metaheuristic search algorithm defined according to the Differential Evolution (DE) architecture, allowing for the definition of the combination of independent variables that grant the minimization, or maximization, of the user’s defined objective function. The prediction and optimization capabilities have been assessed by applying the XGB-DE algorithm to a previously published authors' dataset and experimental results relevant for the radial-axial ring rolling (RARR) process, showing a prediction accuracy and optimization capability equal to 2.33% and 27.4%, respectively, with respect to authors’ previous finite element and experimental results. The XGB-DE methodology showed a remarkable capability in catching the trend and global minimum of a multi-variable and complex objective function, such as the one involved in complex thermo-mechanical forming processes.

Numerical Simulation of Intelligent Fuzzy Closed-Loop Control Method for Radial–Axial Ring Rolling Process of Super-Large Rings

During the radial–axial ring rolling (RARR) process of super-large rings, abnormal deformation states such as instability and out of circularity often lead to rolling termination and quality fluctuation of ring products. In this work, an intelligent fuzzy closed-loop control method for RARR process of super-large rings is proposed, i.e., the ring’s offset adaptive fuzzy control (ROAFC) based on the regulation of the axial roll’s rotational speed and the ring’s circularity fuzzy control (RCFC) based on the regulation of the mandrel’s feed speed. In addition, a recursive average filtering algorithm is added to smooth the axial roll’s rotational speed and the mandrel’s feed speed according to the actual situation. Using the ABAQUS/Explicit software and its subroutine VUAMP, the intelligent fuzzy controller of the ring’s offset and circularity in the RARR process is designed, and the finite element (FE) model for RARR process of a Φ10 m super-large ring with an integrated intelligent fuzzy control algorithm is established. The variation laws of the ring’s offset and circularity error in the RARR process are studied with regard to different control methods such as conventional planning control (CPC), ROAFC, RCFC, and comprehensive control of ROAFC combined with RCFC (ROAFC + RCFC). The results obtained show that, compared with the CPC, the ring’s offset is reduced by 84.6% and the circularity error is decreased by 51.9% in the RARR process utilizing comprehensive control of ROAFC + RCFC. The research results provide methodological guidance for realizing the intelligent forming of super-large rings.

On a plastic instability criterion for ultra-large radial-axial ring rolling process with four guide rolls

A dynamic mechanical model is proposed to describe the complexing actions of all the rolls on the ring during the ultra-large radial-axial ring rolling (RARR) process with four guide rolls. Based on the model, the calculation models for bending moment and normal stress at any section of the ring are deduced by force method. If the maximum section bending normal stress exceeds the yield stress of the ring materials, the ring will be distorted thus leading to the instability of the RARR process. According to this, a plastic instability criterion for the ultra-large RARR process with four guide rolls is developed, based on which a mathematical model to calculate the critical guide force for avoiding plastic instability of ring is obtained. The influence rule of the position of guide roll on the dangerous ring section of plastic instability is revealed, from which it is found the dangerous ring section mainly appears at the radial and axial deformation regions and the contact positions of the guide rolls and ring. The optimized layout of guide roll around the ring in favor of stability is determined to be about α1 = 61° and α2 = 119°. The plastic instability criterion is proven to be reliable from the aspects of the critical guide force, the section bending moment and normal stress and the dangerous ring section of plastic instability. Intelligent simulation case studies for the RARR process of ultra-large aluminum alloy ring indicate that the stable forming of the process can be effectively realized by regulating the guide force based on the plastic instability criterion. This work could provide a valuable guidance for the control of guide rolls and the optimization of the ultra-large RARR process with four guide rolls.

Machine Learning-Based Models for the Estimation of the Energy Consumption in Metal Forming Processes

This research provides an insight on the performances of machine learning (ML)-based algorithms for the estimation of the energy consumption in metal forming processes and is applied to the radial-axial ring rolling process. To define the mutual influence between ring geometry, process settings, and ring rolling mill geometries with the resulting energy consumption, measured in terms of the force integral over the processing time (FIOT), FEM simulations have been implemented in the commercial SW Simufact Forming 15. A total of 380 finite element simulations with rings ranging from 650 mm < DF < 2000 mm have been implemented and constitute the bulk of the training and validation datasets. Both finite element simulation settings (input), as well as the FI (output), have been utilized for the training of eight machine learning models, implemented with Python scripts. The results allow defining that the Gradient Boosting (GB) method is the most reliable for the FIOT prediction in forming processes, being its maximum and average errors equal to 9.03% and 3.18%, respectively. The trained ML models have been also applied to own and literature experimental cases, showing a maximum and average error equal to 8.00% and 5.70%, respectively, thus proving once again its reliability.

Multivariable regression and gradient boosting algorithms for energy prediction in the radial-axial ring rolling (rarr) process

Energy prediction and starvation have become an essential part of process planning for the XXI century manufacturing industry due to cost-saving policies and environmental regulations. To this aim, the research presented in this paper details how machine learning-based algorithms can be an effective way to predict and minimize the energy consumptions in the widely spread radial-axial ring rolling (RARR) process. To analyze this bulk metal forming process, 380 numerical simulations have been developed using the commercial SW Simufact Forming 15 and considering three largely utilized materials, the 42CrMo4 steel, the IN 718 superalloy, and the AA6082 aluminum alloy. To create the database for both multi-variable regression and machine learning models, ring outer diameters ranging from 650 mm to 2000 mm and various process conditions including different sets of tool speeds and initial temperatures have been considered. For the case of the multi-variable regression model, to account for all the cross-influences between all the parameters, a second-order function including 26 parameters has been developed, resulting in a reasonable average accuracy (94 %) but also in an impractical huge equation. On the other hand, the machine learning model based on the Gradient Boosting (GB) approach allows obtaining a similar accuracy (96 %) but its compact form allows a more practical utilization and its training can be expanded almost indefinitely, by adding more results from both numerical simulations and experiments. The proposed approach allows to quickly and precisely predict the energy consumption in the RARR process and can be extended to other manufacturing processes.

Investigation of compaction by ring rolling on thermal sprayed coatings

Often mechanical parts have specific requirements in regard to the underlying alloy. Especially for axial symmetric parts like rings an often requested characteristic is a different requirement on the inner surface than on the outer. Therefore, different production processes exist. One strategy is to roll a basic ring e.g., via radial-axial ring rolling (RARR), and create a functional layer afterwards via thermal spraying. The temperature of the ring and the spraying particles influence the bonding behavior and compaction of the thermal sprayed layer benefits its mechanical properties. The hypothesis presented in this paper is a better performing thermal sprayed layer regarding the adhesion of the layer, reduced porosity and improved residual compressive stress through the combination of the thermal spraying process and the radial-axial ring rolling. After an introduction to the industrial processes of radial-axial ring rolling and thermal spraying, the experimental setup and the results are presented. In the first step, the approach of combining these processes includes an experimental design, in which the rolling of the basic ring, consisting of a 1.0570-steel, gets interrupted right before the target diameter is reached. The ring is then transported to the thermal spraying process where the ring gets covered with layers of 316L-Si, sprayed with a pressure of 8 bar, arc voltage of 34.0 V and a wire feedrate of 2.1 m/min. The coated rings were rolled to two different target diameters with a planned degree of deformation of 0.025 and 0.098 only in the radial direction. This deformation leads to an elongation of the outer circumference of 2.56 % and 10.26 %. Due to the rolling process, the applied coatings revealed a compacting effect and, thus, a significant reduction in the total porosity. The main goal of this study is to investigate the material pairings and parameters regarding thermal spraying and RARR to produce an intact coating with adequate adhesion to the substrate. The long term vision is to adapt thermally sprayed coating into the radial-axial ring rolling process.

Towards an intelligent FE simulation for real-time temperature-controlled radial-axial ring rolling process

The rolling path for a radial-axial ring rolling (RARR) process defines the matched motions of all the rolls including the main roll, mandrel, guide rolls and axial rolls. Materials with low thermal conductivity such as titanium alloys show an overheating in the local region of the ring due to the concentration of forming energy. The temperature sensitivity of these materials leads to severe microstructure and forming defects. Therefore, for the RARR process of titanium alloy rings, it is a core industrial technology to plan a rolling path by which the temperature in the whole ring can be maintained within a desired range (a designed control objective of ring temperature) to improve the mechanical properties. In this work, an intelligent real-time temperature-controlled finite element (FE) model for the RARR process of TA15 titanium alloy rings has been developed under ABAQUS/Explicit software. In the intelligent simulation, by establishing a ring growth velocity model relating to the ring temperature, the motions of various rolls could be driven in real time by the control objective of the ring temperature. Without definition of rolling path prior to the simulation, the new intelligent simulation realizes the self-adaptive control of rolling process to maintain the ring temperature within a desired range. By only one calculation, the rolling path satisfying the control objective of temperature can be obtained. This work achieves quick planning of the rolling path for real-time temperature-controlled RARR process.

반경-축 방향 링 롤링 공정의 정의 및 제어를 위한 분석적인 접근법

This research aims to provide a useful algorithm for the prediction of the geometrical expansion of flat rings in the radialaxial ring rolling process in case of multiple variations of the mandrel feeding speed during the process. The proposed algorithm was subjected to a 2-phases validation process, where results were compared with those of laboratory experiments, conducted at 150℃ on rings made of AA-1070 and AA-6061 aluminum alloys, and with numerical simulations, considering 7 different rings with outer diameter ranging from 800 to 2000 ㎜ and made of 42CrMo4 steel alloy, Ti6Al4V titanium alloy and AA-6061 aluminum alloys. In the first and second validation phases, the maximum deviation in the estimation of the outer diameter of the ring has been calculated in 1.7% and 6.82%, respectively. According to the results of the validation, the proposed algorithm is able to properly predict the geometrical expansion of the ring for multiple variations of the mandrel feeding speed during the process and has good accordance with both relatively small and large rings.

Rolling paths design assisted by target-temperature driven intelligent FE simulation of radial-axial ring rolling

The microstructures of hard-to-deform materials such as titanium alloy are very sensitive to temperature change in hot working process. During ring rolling process, unreasonable rolling paths will lead to drastic temperature change in local region of ring, thus damaging the microstructure and performance of rolled ring. This work proposes a method for designing the rolling paths which could accurately control the ring temperature by target-temperature driven intelligent FE simulation. The main idea of target-temperature driven intelligent simulation is introduced. An intelligent 3D-FE model for TA15 titanium alloy ring rolling is established under ABAQUS/Explicit environment. The rolling paths under different initial conditions are obtained by intelligent FE simulations. The influence rule of initial conditions on rolling paths is revealed. The temperature control effects and change under different initial conditions are discussed. Considering the temperature control effects, a feasible range of initial ring temperature is suggested. Using the proposed method, the quick and accurate design for the rolling paths in radial-axial ring rolling process is realized. It is of great significance for the design and optimization of rolling paths and the accurate regulation of ring temperature in actual production.

Slip line model for forces estimation in the radial-axial ring rolling process

In the research presented in this paper, a slip line-based model is proposed for the estimation of both radial and axial force in the radial-axial ring rolling (RARR) process. Based on the shape of the contact arcs between ring and tools in the two deformation gaps present in the ring rolling process, a recursive algorithm for the calculation of the two slip line fields starting from the two pairs of opposite tools is derived and implemented in a commercial spreadsheet software (MS Excel). By considering the stress boundary conditions applied to the portion of material undergoing the deformation, both for the radial and axial deformation gaps, the pressure factors those make the two slip line fields starting from the two opposite tools to intersect are calculated and utilized for the estimation of radial and axial forces, for each round of the process. The developed model has been validated by cross-comparing its results with those of laboratory experiment and numerical simulation. For the validation study case, the average deviations, in comparison to the experimental results, are calculated in 1.86% and 4.55% for the slip line force model whereas in 6.86% and 0.88% for the numerical simulation, for the radial and axial forces respectively. The proposed slip line model has been also utilized for the estimation of radial and axial forming forces of nine different study cases of flat rings having the outer diameter ranging from 800 mm to 2000 mm, observing a maximum deviation, in comparison to the relevant FEM simulation, of 4.92% (radial force) and 5.88% (axial force). The developed slip line force model allows estimating almost in real time and with a reasonable accuracy the process forces and, for this reason, it may be of interest for both industrial and academic researchers dealing with the set-up and control of the radial-axial ring rolling process.

Contact geometry estimation and precise radial force prediction for the radial-axial ring rolling process

In the present research work, the modular parametric design plug-in Grasshopper, available in Rhinoceros 5, is utilized as a pre-processor for the estimation of the projection of the contact length between ring and tools in the radial-axial ring rolling process. The estimated lengths, for each round of the process, are then used in a slip line based force model for the precise estimation of the radial forming force. The proposed method allows reducing the inaccuracies of the traditional approaches since it supersedes the concept of common thickness draft on both mandrel and main roll side, allowing a more precise estimation of the projection of the contact arc between ring and tools, considered to have a unique value on both mandrel side and main roll side. The fulfillment of this last assumption ensures the forming force to have the same value regardless it is calculated on the mandrel side or on the main roll side. The model has been validated by cross-comparing the analytical results with those of laboratory experiment and finite element simulation. The developed analytical model has been also applied to three different study cases where the previous literature models for the calculation of the projection of the contact arc have shown inaccuracies, demonstrating that the proposed approach can overcome these limitations. The positive cross comparisons among laboratory experiment, FEM simulations, and analytical estimations prove the reliability of the proposed approach, as well as its good integration with authors’ previous analytical algorithms.

Temperature estimation and slip-line force analytical models for the estimation of the radial forming force in the RARR process of flat rings

In this study, a mathematical model for the prediction of the temperature evolution in the ring during the radial-axial ring rolling process is developed and used, together with the authors’ previous results, to determine analytically the flow stress of the material during process. These results, combined with Hill's slip-line field solution adapted to the RARR process, allow a fast and reasonably precise calculation of the radial forming force, a key parameter at the preliminary stage of the process design. The approach is validated by applying the proposed model to a case available in the literature and comparing the analytical results with those of the laboratory experiment and FEM simulation. Following the successful comparison, the models were applied to a large variety of flat rings, comparing analytical predictions with the results of FEM simulations. The accuracy of the analytical calculation and the reliability of the proposed models, for different ring configuration and process parameters, are presented and discussed.

Mathematical definition of the 3D strain field of the ring in the radial-axial ring rolling process

The paper focuses on the radial-axial ring rolling process and details a new mathematical approach for the determination of the evolution of the ring geometry during the deformation process, taking into account separately the sequence of incremental deformations occurring when the ring passes through the mandrel-main roll gap and through the axial rolls gap. Based on the determined geometry of the ring, the three strain components of the strain tensor are estimated and the equivalent plastic strain is computed. The proposed approach, taking into account a third strain in each deformation gap, allows an estimation of the equivalent plastic strain, which is a required parameter for the analytical estimation of the flow stress of the material, needed to compute the forming force. Since a direct validation of the strain components is not possible in the industrial RARR process, authors’ models for the determination of geometry and strain, together with preliminary authors’ models for the estimation of strain rate and temperature drop along the process, have been applied to a literature case for the estimation of the radial forming force in order to obtain a validation of the proposed models. Prediction of radial forming force utilizes a literature model based on slip line theory adapted to the ring rolling process. To extend the validation of the approach and to explore the quality of its predictions to other process configurations, different geometry of the ring have been considered and compared with FEM predictions. These comparisons resulted in good agreement between analytical and FEM results as concerns ring geometry evolution, strain tensor prediction and effective strain estimation.

Optimization on cooperative feed strategy for radial–axial ring rolling process of Inco718 alloy by RSM and FEM

During radial–axial ring rolling process, cooperative strategy of the radial–axial feed is critical for dimensional accuracy and thermo mechanical parameters distribution of the formed ring. In order to improve the comprehensive quality of the ring parts, response surface method (RSM) is employed for the first time to optimize the cooperative feed strategy for radial–axial ring rolling process by combining it with an improved and verified 3D coupled thermo-mechanical finite element model. The feed trajectory is put forward to describe cooperative relationship of the radial–axial feed and three variables are designed based on the feed trajectory. In order to achieve multi-objective optimization, four responses including thermo mechanical parameters distribution and rolling force are proposed. Based on the FEM results, RSM is used to establish a response model to depict the function relationship between the objective response and design variables. Through this approximate model, effects of different variables on ring rolling process are analyzed connectedly and optimal feed strategy is obtained by resorting to the optimal chart specific to a constraint condition.

A new approach in modeling of guide and conical rolls in the ring rolling process

One of the modest methods in producing seamless rings is the radial-axial rolling process. Modeling the guide and conical rolls and calculating their respective forces are essential in the simulation of the radial-axial rolling process. The main objective of the present study is to propose a novel approach in the modeling of guide and conical rolls used in the radial-axial ring rolling process. The parts dedicated to the simulation of the process are two complicate formed rings made of Ti-6Al-4 V alloy. To validate the results obtained via the simulation, practical experiments were carried out in which a simple ring made of aluminum alloy was rolled, and practical results were compared with simulation results. Comparing the results shows a proper agreement between simulation and practical results. Consequently, the obtained radial and axial forces and moments from the simulated process can be used to select proper machine tools for the purpose of mainly producing two complicate formed rings.

Blank size dependence of microstructure in radial-axial ring rolling of TA15 titanium alloy by macro-micro FE simulation

The blank size, determining the deformation degree and the ratio of axial to radial feed amount of the radial-axial ring rolling process for TA15 titanium alloy, has a strong effect on the grain size and volume fraction of primary α phase, which determine the mechanical properties of the rolled ring. In this paper, a macro-micro 3D-FE model of the radial-axial ring rolling of TA15 titanium alloy has been developed under ABAQUS software. The ring blank transferring from heating furnace to rolling mill, rolling and cooling after rolling during the whole process are considered in the FE model. And multiple blanks with different rolling ratios and ratios of axial to radial feed amount are designed for a desired TA15 titanium alloy ring. Then, the effects of the blank size on the grain size and volume fraction of primary α phase in the rolled ring are investigated by comprehensive FE simulations. Finally, the optimum blank sizes are obtained by evaluating both the volume fraction of primary α phase and the distribution uniformities of grain size and volume fraction of primary α phase.

The Ring’s Axial Deformation Control Method of Vertical Hot Ring Rolling Process

Axial deformation of the ring during the traditional vertical hot ring rolling (VHRR) process has a considerable effect on the ring products’ quality. In this paper, the ring’s axial deformation of VHRR process of three different rolling modes, that is, open-die mode, close-die mode and open-die mode with conical rolls like the radial-axial ring rolling (RARR) process is analyzed. Three groups of 3D coupled thermo-mechanical FE models of VHRR process are established in software ABAQUS, and the axial deformation and the width spread of the rings are studied in detail. Finally, a special conical roll device was designed and equipped on the traditional VHRR mill, and series of VHRR experiments are conducted, the results of both simulation and VHRR process show that the formed rings utilizing open-die rolling with a special pair of conical rolls has lower axial deformation, smoother end surface and higher precision than the formed rings utilizing open-die rolling and close-die rolling. The research results can supply an effective approach to axial deformation control of traditional VHRR process.

Control method for centering rolls in radial-axial ring rolling process

The control method of centering rolls was developed to ensure the circularity of rings and remove the process instability during a radial-axial ring rolling (RARR) process. The position control method is determined by the growth velocity of rolling rings and mathematical correlations among the key process variables, such as ring geometries, roll shapes, and feed rates of rolls. The moving coordinate of centering rolls were calculated by the growing velocity of an outer radius of the ring, VR, and the angle between the links of the ring’s center with the mandrel’s center and with the centering roll’s center, a, in the RARR process. The growth behavior of a ring and the angle provided moving coordinates for the centering rolls in real time. The hydraulic adjustment mechanism for establishing a successful RARR process is also proposed using the parameter design of the linkage assembly and beam bending theory. In order to verify the reliability of the control method, the FE-simulation under a FORGE software environment and ring rolling experiments of 42CrMo4 rings with an outer diameter of 510mm. The results show that these methods provided a high ring circularity and process stability.