Generic Neural Network Technology To Improve Complex Materials Manufacturing

By the early 1990s, the functions of complex materials such as composites, ceramics, and semiconductors had multiplied, and their importance to various manufacturing industries had escalated. Despite this expanded role, intelligent manufacturing of complex materials was based on techniques known to a handful of manufacturing engineers rather than on defined methods. To find more efficient and less expensive ways to produce quality products, Honeywell, Inc., wanted to add neural networks (that is, systems that can learn, infer, and model complex processes that lack explicit rules) to optimize the manufacturing processes of new complex materials.