Investigating the Effects of Controllable Parameters on Cold-wire Gas Tungsten Arc Weld Bead Geometry

Multi-layer Gas Tungsten Arc Welding (GTAW) is widely used for refurbishing plastic injection molds. This welding process can provide the high quality weld that is required for molds that will be subject to high temperatures and pressures during production. This refurbishing weld process is currently performed manually, which exposes the welders to poor working conditions. GTA welding is a tedious and time consuming process when compared to other welding processes. The advantages of automating this process are two-fold: removing workers from arduous working conditions, and decreasing production cycle time by increasing the deposition rate through robotic control. The purpose of this study was to investigate the e ects of controllable welding parameters on weld bead geometry for standard welding operating ranges when refurbishing plastic injection molds. Another aim was to determine and predict the sensitivity and response, respectively, of base metal orientation on bead geometry. Remanufactured molds require the removal of tool steel, which can be achieved with current CNC machining technology. However, automating the addition tool steel is di cult achieve due to the inherent complexity of the GTA welding process. The work presented in this thesis is an integral component for simplifying the mold remanufacture process by eliminating the guesswork in choosing optimal welding parameters. Through the means of experimental design and statistical analysis, relationships were developed between welding parameters and their e ects on bead height, bead width, penetration, heat a ected zone (HAZ) depth and HAZ width. The regression models were capable of predicting responses in bead geometry within 1 millimeter in variation. The resulting regression models can be extended to cold wire GTA welding applications that require high deposition rates and the capabilities of predicting bead geometry for various base metal orientations