In this work, published in Rapid Prototyping Journal, we address a crucial challenge in Wire Arc Additive Manufacturing (WAAM): the need for post-processing to achieve the required dimensional accuracy due to the wavy surfaces produced. The study is framed within the growing concern for the demand for more sustainable manufacturing practices, and its main objective is to reduce both machining and material waste.

The challenge lies in determining the optimal position and orientation of the plasma-WAAM fabricated part before proceeding to machining, a question that, to our knowledge, has not been previously addressed using optimization techniques in the context of additive manufacturing.

To address this, we have developed a novel methodology that combines a customized fitness function with stochastic optimization algorithms to assess and enhance the positioning of WAAM components. This approach offers a comprehensive process to optimize the post-processing stage, reducing an index aimed at positioning the part for machining effectively.

The results demonstrate that the proposed method significantly reduces manual operations while maintaining high precision. This approach provides an efficient and automated evaluation for Additive Manufacturing parts before machining, reducing post-processing time and material waste, thereby promoting more environmentally responsible production practices.