Method for selecting the optimal technology in metal additive manufacturing using an analytical hierarchical process

The research hypothesis of this study revolves around employing Multi-Criteria Decision Analysis (MCDA) techniques, particularly the Analytical Hierarchical Process (AHP), to optimize technology selection in metal additive manufacturing. The data collected and analyzed includes the results of the survey and criteria evaluation relevant to the decision-making process, such as reliability, finishing of the part after printing, complexity of post-processing, sustainability of the process, user preferences, machine price, manufacturing cost, and productivity. The AHP methodology involves constructing a hierarchy structure wherein the goal or objective, criteria, and alternatives are systematically organized. Pairwise comparisons are then made among criteria and alternatives, using a relative importance scale ranging from 1 to 9. These comparisons are recorded in a positive reciprocal matrix, which is then normalized to obtain numerical weights for decision-making. The priority vector or normalized principal eigenvector is computed, representing the relative importance of criteria, and the maximum eigenvalue is determined. Finally, a global ranking of decision alternatives is analyzed based on additive aggregation and normalization of the sum of local priorities of criteria and alternatives.