Reliability Based Design Optimization with LS-OPT for a Metal Forming Application
The purpose of this paper is to account for uncertainties in the manufacturing processes of metal forming in order to evaluate the random variations with the aid of FE-simulations. Various parameters of the Finite-Element model describing the investigated structural model are affected by randomness. This, of course, leads to a variation of the considered simulation responses such as stresses, displacements, and thickness reductions. On this, for the simulation engineer basic questions arise regarding: (1) the dimension of the range of variation of the simulation responses (2) the significance/contribution of the (input) parameters with respect to specific responses and (3) the reliability of the process design with respect to constraints (failure, damage, requirements, ...). In order to find solutions to these questions several methodologies may be applied that are available in the commercial optimization software LS-OPT (Stander et al. [5]). Some of the methodologies, such as Monte Carlo simulation, meta-model based Monte Carlo simulation, stochastic fields, are discussed in this paper and are demonstrated by means of a metal forming problem. For this, a non-robust design with respect to the specified constraints has been detected. By utilizing reliability based design optimization (RBDO) through LS-OPT, the failure probability (violation of constraints) could be reduced significantly.
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Reliability Based Design Optimization with LS-OPT for a Metal Forming Application
The purpose of this paper is to account for uncertainties in the manufacturing processes of metal forming in order to evaluate the random variations with the aid of FE-simulations. Various parameters of the Finite-Element model describing the investigated structural model are affected by randomness. This, of course, leads to a variation of the considered simulation responses such as stresses, displacements, and thickness reductions. On this, for the simulation engineer basic questions arise regarding: (1) the dimension of the range of variation of the simulation responses (2) the significance/contribution of the (input) parameters with respect to specific responses and (3) the reliability of the process design with respect to constraints (failure, damage, requirements, ...). In order to find solutions to these questions several methodologies may be applied that are available in the commercial optimization software LS-OPT (Stander et al. [5]). Some of the methodologies, such as Monte Carlo simulation, meta-model based Monte Carlo simulation, stochastic fields, are discussed in this paper and are demonstrated by means of a metal forming problem. For this, a non-robust design with respect to the specified constraints has been detected. By utilizing reliability based design optimization (RBDO) through LS-OPT, the failure probability (violation of constraints) could be reduced significantly.