From the WAAM design to the machining process: Optimizing part positioning

Abstract

Wire-fed Additive Manufacturing (AM), such as Plasma Wire-Arc Additive Manufacturing (plasma-WAAM), often produces wavy surfaces, requiring post-processing to attain the required dimensional accuracy and surface smoothness. This study seeks to reduce both machining and material waste. A 3D scanning process was conducted on a part fabricated using plasma WAAM, followed by a mesh triangle reduction to enhance computation efficiency. The target design was aligned with the fabricated part, and normal distances between selected points on the two geometries were calculated. A strategy based on triangular mesh points was developed to categorize these distances concerning the faces of the target design. An optimal positional problem, leveraging a fitness function based on custom indexes, was solved using various stochastic algorithms, ensuring no points of the target design extended beyond the scanned part. The results demonstrated that the proposed method significantly reduces manual operations while maintaining high accuracy. This approach provides an efficient and automated assessment method for additive manufacturing parts before machining. The developed method reduces manual post-processing time and machining waste, offering practical benefits for industries utilizing WAAM. This methodology enhances sustainability objectives within additive manufacturing by reducing material waste and machining needs, thereby promoting environmentally responsible production practices. This research represents a novel and previously unexplored approach within the context of WAAM. It introduces a methodology that integrates custom fitness function and optimization techniques to improve the assessment of WAAM parts, ensuring efficient positioning and reducing waste.