Although computers now run many materials-processing operations, they rely mainly on empirical information--they are programmed essentially to maintain a prescribed set of conditions, such as temperature and pressure. While this method has led to remarkable success, it is inherently limited by past experience. Overcoming these limitations is the goal of the new technology of intelligent--or
... [Show full abstract] knowledge-based--processing of materials. The basic aim of this approach is to organize knowledge in an accessible form and use it to improve process control, boost productivity, and, ultimately, make superior products. At the heart of intelligent processing are mathematical models that quantitatively relate a material's properties, such as strength and flexibility, to its internal structure. The models also explain how this structure depends on the conditions under which the material is produced. The goal is to devise models that apply to a broad class of materials, reducing the need for time-consuming and costly laboratory experiments every time a new process emerges. By fostering a better understanding of a material, how it can be made, and how it behaves, intelligent processing should also make possible much more accurate control of processes now in use.