Development of a Goal Programming Model Based on Response Surface and Analytic Hierarchy Process Approaches for Laser Cutting Process Optimization of St-52 Steel Plates

Abstract

This paper presents an integrated model for optimization of laser cutting process of St-52 steel plates with multiple performance characteristics using Goal Programming (GP), Analytic Hierarchy Process (AHP), and Response Surface Methodology (RSM) approaches. In this study, optimum levels of the laser cutting process input parameters namely, material thickness, cutting speed, laser power, and assist gas pressure are obtained. For optimization purposes, four different surface roughness types of a cut surface, surface hardness, cutting time, and heat-affected zone (HAZ) of the cut surface are considered as performance outputs (responses) in this study. Optimization of multiple performance objectives (responses) requires obtaining regression functions with RSM first, and then weighting the regression functions using the AHP and finally combining the multiple functions into a single overall goal within a GP model and solving the model to optimize the laser cutting process. The study clearly shows that the presented optimization model is flexible enough to optimize the laser cutting process for various scenarios and conflicting priorities.