Predictive Model for Tensile Ductility and Optimization of Process Variables for Arc-Welded and Tempered Micro-alloyed Steel

Abstract

Abstract

The over reliance on trial and error technique by many engineers/welders in the selection of optimum conditions of welding and heat treatment process variables to maximize the mechanical properties of steel weldment for enhanced performance in service has always been a huge challenge. Therefore, to avoid this time consuming practice, which most often do not produced welds with satisfactory quality in terms of fitness for service and cost.This research study has therefore, provides a systematical approach in developing an appropriate mathematical relationship between the process and response variables, with an optimization method for finding the welding and heat treatment process variables to maximize tensile ductility of the arc-welded and tempered micro-alloyed steel.The response surface methodology based on optimal design was employed to model and optimize the process variables. The results of the analysis of variance of the developed model for percent elongation indicated that it is statistically significant at p<0.0001. The regression coefficient (R²) and adjusted coefficient (R²_adj.) values of97.77% and 95.76% respectively, indicate that the developed model can adequately approximate the actual response data in the design space, and a proof that it is valid.Predicted and experimental results of the validation tests were found to be in reasonable agreements. This implies that the optimization technique adopted was reliable. The optimum input values of the process variables that resulted in maximum percent elongation of29.523% inthe micro-alloyed steelweldmentwere welding current setting of 101.408amps, tempering temperature of 450⁰C and soaking time of 120.0003 minutes.