Principal Component Factor Analysis Applied to Multi-Objective Optimization in the Turning of Hardened AISI 52100 Steel

The manufacturing industry plays a fundamental role in social and economic development but faces the challenge of making its processes more sustainable. In the machining sector, concerns are mainly related to energy consumption, pollutant emissions, and waste generation. In this context, this study analyzes the turning process considering three response variables: material removal rate, surface roughness, and cost. To reduce the dimensionality of the problem, Factor Analysis by Principal Components with Varimax rotation is applied, transforming the original responses into orthogonal functions. These functions are then optimized using the Normal Boundary Intersection method, resulting in 21 Pareto-optimal solutions. The selection of the best combination of parameters depends on the decision-maker, who may take into account criteria such as quality, productivity, technical performance, and environmental impacts, thus fostering choices aligned with sustainability principles.