Abstract

We propose an intelligent simulation tool for the optimization of step sizes in manufacturing processes. We demonstrate the generic optimization concept by application to the incremental hole drilling method using an Abaqus model. The universal approach can be transferred to other simulation models such as machining or forming in order to reduce component distortions. The incremental hole drilling method is used for the determination of residual stresses in the outer layers of a material. For the estimation of the measurement error, the method can be extended by dividing the drilling into several steps in radial and depth direction (drilling strategy). In our approach, we divide the Abaqus model into multiple time frames with a feedback control loop in a python framework. For each time frame, a drilling step in radial or depth direction is applied and evaluated with respect to the strain difference to the previous time frame. If the obtained strain difference deceeds a selected value, the calculation is repeated with an increased step size until the calculated strain difference meets the chosen criterion. Our results show that we can optimize the step sizes in the hole drilling method in radial and depth direction with respect to the simulation data. The experimental validation of the optimized simulation results is part of ongoing work. The optimization tool allows to evaluate and adapt single steps of given strategies or to plan new strategies by given characteristics such as overall drilling radius and depth. The flexible approach can be extended by integrating different optimization goals (e.g. minimizing / maximizing step sizes) and new drilling strategies.

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