Enhancing Nano Surface Quality through Optimization for Robotic Wire Arc Additive Manufacturing

Le résumé fourni par la source

Wire arc additive manufacturing is the most promising technique for the deposition of metal components in any industry. Wires of different metals and alloys are directly converted into 3D components through this process. Dimensional and surface accuracy are the major challenges associated with WAAM, and the post-processing required after deposition depends on these factors. Defects can be minimized by selecting suitable input process parameters during deposition. The selection of the proper process parameters ensures the defect-free deposition of WAAM components, and parametric optimization plays an important role in getting optimized outcomes in WAAM. In this paper, Hybrid Multi-Criteria Decision-Making (MCDM) techniques have been used to optimize the process parameters and offer a simple computational procedure. Two important input process parameters – wire feed rate and tool speed – are taken as input parameters, and surface roughness, toe angle, bead height, and depth of penetration have been taken as output responses. A multi-criteria decision-making strategy based on hybrid AHP-MOORA was used to select the optimized process parameters for WAAM. The criteria weight was determined using the AHP (analytic hierarchy process), and the composites were ranked using multiple objective optimizations on the basis of ratio analysis (MOORA). Sensitivity analysis was lastly carried out to determine the ranking’s robustness and stability in relation to the criterion weight.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.