The work presented in this report is an attempt to allow density-based topology optimization algorithms to take into account machining costs when optimizing. To this end, and estimation model for the cost of 2.5-axis CNC milling was developed based on the principles of Design for
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The work presented in this report is an attempt to allow density-based topology optimization algorithms to take into account machining costs when optimizing. To this end, and estimation model for the cost of 2.5-axis CNC milling was developed based on the principles of Design for Manufacturing.

This estimation model was implemented in a generic topology optimization algorithm in five steps of complexity. The behaviour of the model was evaluated at each step by means of a set of experiments, showing how the addition of the cost estimation influences the optimization results.

The most promising results from the experiments are validated with Autodesk Fusion 360, with which the designs were programmed to be machined on a CNC mill. The machining times from this software were used to calculate the actual machining costs and these were compared to the machining costs estimated by the optimizer.

Two formulations of the method were found to be useful for estimating the machining cost of designs. A simple formulation that uses the shape factor and the differentiation between internal and external pockets to estimate the cost resulted in a cost saving of 13% at the expensive of a compliance increase of 9%. The more complex formulation uses multiple pocket domains to evaluate pocket-specific properties. This allowed a more accurate estimation of the costs, but did not result in a better performing optimization. The cost saving was comparable at 12%, but the compliance increased by 16%.

It was concluded that there is a use for both methods. The simple formulation allows to find cheaper designs, but does not allow much control in the cost estimation. The complex formulation however can be used to fine-tune the method for a specific situation, which could enable it to perform better that the simple formulation.