A SYSTEMATIC STUDY OF A STATISTICS-BASED METHODOLOGY FOR THE OPTIMIZATION OF PROCESSING-STRUCTURE-PROPERTY RELATIONSHIPS IN MAGNESIUM ALLOYS

This study explores a statistically-based methodology for optimizing processing-structure-property relationships in magnesium alloys, particularly through the design of experiments (DOE) approach. The objective is to streamline alloy development by validating a design consisting of limited experimental runs focused on solute concentrations and heat treatment variables for AZ-series alloys. The methodology was implemented to evaluate mechanical properties and to develop empirical models that correlate processing parameters with structure-properties outcomes. Results indicate that the proposed models can optimize multiple mechanical properties concurrently, leading to efficient development of new alloys tailored for specific performance characteristics while minimizing experimental efforts. This methodology, leveraging existing datasets and avoiding traditional approaches, showcases its potential to reduce costs and time in alloy design and processing optimization.