The goal of this paper is to show the potential of fuzzy sets and neural networks, often referred to as soft computing, for aiding in all aspects of manufacturing of advanced materials like ceramics. In design and manufacturing of advanced materials it is desirable to find which of the many processing variables contribute most to the desired properties of the material. There is also interest in real-time quality control of parameters that govern material properties during processing stages. This paper briefly introduces the concepts of fuzzy sets and neural networks and shows how they can be used in the design and manufacturing processes. These two computational methods are alternatives to other methods such as the Taguchi method. The two methods are demonstrated by using data collected at NASA Lewis Research Center. Future research directions are also discussed.

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