Making the Case for a Model-Based Definition of Engineering Materials

For over 100 years, designers of aerospace components have used simple requirement-based material and process specifications. The associated standards, product control documents, and testing data provided a certifiable material definition, so as to minimize risk and simplify procurement of materials during the design, manufacture, and operation of engineered systems, such as aerospace platforms. These material definition tools have been assembled to ensure components meet design definitions and design intent. They must ensure the material used meets “equivalency” to that used in the design process. Although remarkably effective, such traditional materials definitions are increasingly becoming the limiting challenge for materials, design, and manufacturing engineers supporting modern, model-based engineering. Demands for cost-effective, higher performance aerospace systems are driving new approaches for multi-disciplinary design optimization methods that are not easily supportable via traditional representations of materials information. Furthermore, property design values having the definitions based on statistical distributions from testing results can leave substantial margin or material capability underutilized, depending on component complexity and the application. Those historical statistical approaches based on macroscopic testing inhibit innovative approaches for enhancing materials definitions for greater performance in design. This can include location-specific properties, hybrid materials, and additively manufactured components. Development and adoption of digital and model-based means of representing engineering materials, within a design environment, is essential to span the widening gap between materials engineering and design. We believe that the traditional approach to defining materials by chemistry ranges, manufacturing process ranges, and static mechanical property minima will migrate to model-based material definitions (MBMDs), due to the many benefits that result from this new capability. This paper reviews aspects of the challenges and opportunities of model-based engineering and model-based definitions.