Global Approach for Optimization and Control of CMT-Based WAAM for SS316L

Metal additive manufacturing process represents the most efficient means of producing intricate and compact components with nearly finished shapes. However, a significant drawback of this method is its substantial time and cost requirements. In contrast, wire arc additive manufacturing, commonly known as WAAM, has emerged as a promising alternative for producing large-scale structures due to its cost-effectiveness and reduced fabrication time. Over the past two decades, researchers have dedicated their efforts to investigating WAAM’s application with aluminium and its alloys. Nevertheless, there has been limited exploration of the WAAM fabrication process for the stainless steels. This study aims to examine the impact of various process parameters on beads quality and geometry, for that we consider three key process parameters: welding speed (WS), wire feed rate (WFR), gas flow rate (GFR). To streamline our experimentation, we employ the multiple-level factorial design method, which helps reduce the number of trials required to identify optimal input variable ranges. Macro-level structural analysis is conducted on the sixteen weld bead samples to assess their geometric properties. Additionally, we employ ANOVA analysis to investigate the relationship between input process variables and output response variables. To gain a deeper insight into these associations, we employ a multiple regression approach. Using the results obtained, we employ the Teaching Learning-Based Optimization method to determine optimal process parameters and anticipate their corresponding results.