Key Engineering Materials Vols. 651-653

Abstract: This paper describes an automated procedure developed for the identification of Johnson-Cook (JC) law material parameters and Coulomb friction coefficient at the tool-chip interface, in the specific case of metal cutting FE analysis. The procedure has been developed in iSight environment, through the integration between AdvantEdge metal cutting FE code and an appropriately selected optimization algorithm. The identification of JC and friction parameters, in fact, has been performed considering it as an optimization problem, in which the objective function is the numerical/experimental error function minimization (in the specific case, it is related to the forces and temperatures responses). The calibration and validation phases have been performed using forces and temperatures experimental data, collected in orthogonal cutting test on SAF2507 superduplex steel.

Abstract: For the full characterization of the hot working behaviour of a given material a large number of laboratory experiments have to be performed. The experiments themselves are time consuming and the required specimen material can be quite expensive. With the increasing versatility of the testing machines, like dilatometry with easily variable temperatures, overthinking the classical approaches for materials characterization becomes expedient.In this paper a new technique for the reduction of the experimental effort is presented at the example of a 25MoCrS4 case hardening steel. To analyse the potential for the reduction of the experimental effort the classical approach of a full experimental test matrix is chosen. Here 55 flow curves with temperatures between 700 and 1200°C and strain rates from 0.01 to 100/s are experimentally determined. Then a semi-empirical model for strain hardening and dynamic recrystallization is fitted using an automated routine for parameter determination, taking all available flow curves into account. Subsequently, the number of flow curves used to fit the model parameters is gradually reduced. The model accuracy obtained with the reduced experimental data is compared to the initial fit. The natural decrease in accuracy with the use of less data compared to the gain due to the reduction of experimental effort is analysed. In addition optimal distribution of the sampling points in the experimental matrix for a reduced number of experiments is discussed. It is shown that less than a quarter of the full matrix is sufficient to reach accuracies comparable to using the full matrix. Using the vertices and symmetrical distribution of the data within the full experimental matrix allows a drastic reduction of experimental effort while maintaining the initial accuracy. The results suggest that it might be possible to reduce the costs and effort for material characterization by 50-80%.

Abstract: Innovative product characteristics can be realized by hot roll bonding of two or more layers of different materials. To optimize the roll bonding process, an approach to align the strength differences in both materials by a temperature difference between the layers has been proposed. Therefore, the temperature distribution has to be investigated by finite element (FE) simulations. In these simulations the heat transfer coefficient (HTC) between the two aluminum layers is of great importance. With this coefficient the temperature transfer between the two layers can be determined in order to estimate the temperature field and the material strength difference in the layers.In hot roll bonding there are two ranges for the HTC depending on whether bond formation takes place or not. This effect can be used to determine at which pressures bond formation starts. To evaluate the HTC for this application and to determine its value ranges, a simple setup has been developed. This setup allows conducting experiments under defined temperature and pressure conditions. The resulting force-time measurements were used as input values for inverse FE-simulations, with the goal to gather the HTC by inverse modelling the temperature distributions of the specimens. First results show that the range of the pressure dependent HTCs leads up to 21 kW/(m²K) in the unbonded range. In the range where bonding occurred between the specimens, values over 150 kW/(m²K) were estimated. The data for the HTC was implemented in roll bonding simulations as an interaction property. A comparison between the simulated temperature curve and a measured temperature curve during roll bonding showed a good agreement between the temperature values.

Abstract: The stability of a metal forming production process is influenced by several sources of scatter such as variation of material and lubrication properties. Identification of the sources of variation is needed to optimize the process settings or to design a control strategy for the process. Many engineers point out sources of variation by experience, but in complex cases a computational identification algorithm may be used to investigate the process. When using parameter estimation in a control system, process forces can be used for the estimation. However, many parameters may influence the process forces. Therefore extensive models are needed to be able to identify the process parameters, including parameters such as tooling misalignment. In the current work, a thin steel flap bending process is studied. Measurements from an industrial press are used to identify the process parameters. A metamodel based inverse analysis procedure is used. The procedure is extended with proper orthogonal decomposition (POD) of the force curves to increase its convergence rate.

Abstract: Sheet Metal Forming is a widely used process in industry. However, it is also an expensive onedue to the diversity and complexity of methodologies used to obtain the adequate tools combination.In fact, even though there is already finite element based software to compute the final shape of aformed sheet from a given tool, there is no efficient procedure to predict the inverse problem: the toolgeometry from the formed component final shape.The final aim of this work is to improve the current trial-and-error process for the inverse problem.To achieve this objective, an integrated approach for tools geometry manipulation is presented, basedon the parametric NURBS description of the tools surface. This is applied to perform a sensitivityanalysis in order to evaluate the effect of numerical noise and small disturbances on the tools designvariables in the final formed sheet. Furthermore, the robustness of the proposed approach is evaluatedusing two parts with distinct complexity.

Abstract: The domain of the presented work is the design of a computer advisory system which should offer support on general design of production cycle. The idea of functioning of the advisory system is related to the reuse of information gathered from previous processes of production design. The information on the design of entire production cycle is suggested to be split into fragments related to specific production phases in the whole manufacturing chain. The advisory system should provide the possibility of making use of diverse piece of information so as to obtain the full production cycle for a new product similar to others manufactured in the past. The idea of information processing is based on the data mining rules induction methods and is visualized with examples of fasteners manufacturing.

Abstract: It is a great challenge in the development of functional components to determine the optimal blank design (material configuration) of a workpiece according to a specific forming process, while knowing the desired target geometry (spatial configuration). A new iterative non-invasive algorithm, which is purely based on geometrical considerations, is developed to solve inverse form finding problems. The update-step is performed by mapping the nodal spatial difference vector, between the computed spatial coordinates and the desired spatial target coordinates, with a smoothed deformation gradient to the discretized material configuration. The iterative optimization approach can be easily coupled non-invasively via subroutines to arbitrary finite element codes such that the pre-processing, the solving and the post-processing can be performed by the habitual simulation software. This is exemplary demonstrated by an interacting between Matlab (update procedure for inverse form finding) and MSC.MarcMentat (metal forming simulation). The algorithm succeeds for a parameter study of a ring compression test within nearly linear convergence rates, despite highly deformed elements and tangential contact with varying friction parameters.

Abstract: The Game Theory is a good method for finding a compromise between two players in a bargaining problem. The Kalai and Smorodinsky (K-S) method is a solution the bargaining problem where players make decisions in order to maximize their own utility, with a cooperative approach. Interesting applications of the K-S method can be found in engineering multi-objective optimization problems, where two or more functions must be minimized. The aim of this paper is to develop an optimization algorithm aimed at rapidly finding the Kalai and Smorodinsky solution, where the objective functions are considered as players in a bargaining problem, avoiding the search for the Pareto front. The approach uses geometrical consideration in the space of the objective functions, starting from the knowledge of the so-called Utopia and Nadir points. An analytical solution is proposed and initially tested with a simple minimization problem based on a known mathematical function. Then, the algorithm is tested (thanks to a user friendly routine built-in the finite element code Forge®) for FEM optimization problem of a wire drawing operation, with the objective of minimizing the pulling force and the material damage. The results of the simulations are compared to previous works done with others methodologies.

Abstract: The present work aims at determining the optimal working conditions for the manufacturing of the AA6061-T6 Al alloy by the hydroforming process. As case study a stepped geometry was used. A numerical model was created using the commercial explicit Finite Element code LS-DYNA. The plastic behaviour of the investigated alloy was modelled implementing experimental data (flow stress curves, Lankford coefficients and Forming Limit Curves) and using two different yield criteria: an anisotropic one (Barlat ‘89) and the conventional isotropic one (Von Mises). Finite Element models were tuned using experimental data from warm hydroforming tests: comparing both the sheet thinning and the die cavity filling, quite different friction conditions had to be supposed for obtaining a good fitting with both the yield criteria.Finite Element models were finally used for evaluating the working range of the hydroforming process: results from a CCD simulation plan were imported within an integration platform (modeFRONTIER) to evaluate the optimal hydroforming conditions based on a multi-objective genetic algorithm optimization. Quite different results in terms of optimization and working range were obtained when adopting different yield criteria.

Abstract: Uncertainty is inevitable in sheet metal metal forming process. Aleatory uncertainties in material properties, blank thickness and friction condition are inherent irreducible variabilities in sheetmetal forming. However, optimal design configurations which are obtained by conventional designoptimization methods are not always able to meet the desired targets due to the effect of uncertainties.In order to tackle this problem, a multi-objective robust design optimization (MORDO) applied forsheet metal draw bending process is introduced in this paper. In addition, since the MORDO of sheetmetal forming involves considering serveral conflicting criteria, a Pareto multiple objective criteriadecision-making approach based on capability indices is proposed.