Abstract
In this work, we focus on the computational bridging between the meso- and macro-scale in the context of the hybrid modelling of Internal Traverse Grinding with electro-plated cBN wheels. This grinding process satisfies the manufacturing industry demands for a high rate of material removal along with a high surface quality while minimising the number of manufacturing processes invoked. To overcome the major problem of the present machining process, namely a highly concentrated thermal load which can result in micro-structural damage and dimension errors of the workpiece, a hybrid simulation framework is currently under development. The latter consists of three components. First, a kinematic simulation that models the grinding wheel surface based on experimentally determined measurements is used to calculate the transient penetration history of every grain intersecting with the workpiece. Secondly, an h-adaptive, plane-strain finite element model incorporating elasto-plastic work hardening, thermal softening and ductile damage is used to simulate the proximity of one cBN grain during grinding and to capture the complex thermo-mechanical material response on a meso-scale. For the third component of the framework, the results from the preceding two simulation steps are combined into a macro-scale process model that shall in the future be used to improve manufacturing accuracy and to develop error compensation strategies accordingly. To achieve this objective, a regression analysis scheme is incorporated to approximate the influence of the several cutting mechanisms on the meso-scale and to transfer the homogenisation-based thermo-mechanical results to the macro-scale.
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