November 2023 Volume 5

FORGING RESEARCH

Robotic DED-GMA Preforms for Forging Jared Seals, Grant Moye, Alexandria Finger, Abigail McInnes, Bishal Silwal Georgia Southern University, Statesboro, Georgia, United States

Forging is one of the major manufacturing processes that makes a critical contribution to transportation, aerospace, energy, medical, and countless other sectors. In a conventional forging process, the billet is forged into the final product using an open or closed die [1]. A forging sequence may opt to use a preform in order to reduce the number of extra forging operations and to reduce wasted material. A preform is a piece of stock that resembles the final required shape of the forged part and is manufactured in conjunction with the forging process. Hopper et al [1] have studied the effect of hot forging on the preform AM-produced 316 stainless steel parts. Similarly, Maredla et al. [2] have studied the effect of cold rolling on the microstructure and texture of selective laser melting built Fe-Ni-Cr steel. Preforms are a great candidate for the application of Robotic DED in forging settings because Robotic DED are well suited for medium to large size products. The use of Robotic DED would allow for the rapid production and testing of preforms, reducing the number of forging processes in a given sequence. In this paper, we designed and fabricated a tuning fork preform which is then forged to generate the required dimensioning. A tuning fork was selected for this study and the dimensional accuracy as well as the microstructure after DED

Abstract The goal of this project was to use Robotic Direct Energy Deposition (DED)- metallic wire to fabricate two preforms that would then be forged the rest of the way into a set of tuning forks. The creation of the preforms was done using frequency analysis and the Robotic DED was performed with a KUKA Robotic arm fitted with a Lincoln Electric GMA welder. The preform was removed from the build plate and hand forged to the approximate pre-machined dimensions. The final product then went through hardness testing and microstructure analysis. These results were compared to deposited and heat-treated wall pieces that used the same welding wire. The results show changes in grain morphology and higher hardness after forging. Introduction Robotic DED-GMA, also known as wire arc additive manufacturing (WAAM) is an emerging additive manufacturing (AM) process that combines the processes of gas metal arc welding (GMAW), also known as Metal Inert Gas (MIG), and industrial robots. In this process, a MIG welder is controlled using a six-axis Robotic arm to create a 3D shape out of wire feedstocks. Robotic DED involves melting a wire using an electric arc and depositing it layer by layer to build the desired geometry. Robotic DED results in parts with metallic properties, such as high strength, thermal conductivity, and good mechanical properties similar to conventionally manufactured metal parts. Robotic DED processes can deposit large volumes of metal quickly due to the higher melting and deposition rates of metal wire feedstocks. Robotic DED parts often require post processing operations like machining, grinding, or heat treatment to achieve the desired surface finish and dimensional accuracy. It is compatible with other types of production processes which can add specific features to traditionally manufactured parts. This makes the process viable for producing products that will be subjected to high mechanical stresses, require precise metal properties, or demand robust structural integrity. With the limitations of dimensional accuracy and surface finish, Robotic DED provides a low-cost alternative to other AM processes.

GMA and forging was studied. Experimental Methods

Figure 1: Tuning Fork Dimensions (in mm) and frequency simulation for 440 Hz vibrational frequency The dimensions required for the preforms were calculated beforehand based on the expected geometry profile and altered using Solidworks simulation. Two tuning forks were designed to generate two different frequencies. The first frequency is at 440

FIA MAGAZINE | NOVEMBER 2023 82