Intelligent Processing of Materials
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Advanced materials can provide specialized properties, or combinations of properties, that cannot be obtained in conventional materials. However, advanced materials generally require unusual processing operations in order to achieve their unique microstructures and the r e s u l t i n g greatly i m p r o v e d properties. These materials also tend to be expensive because of the high value added by unusual processing operations t h a t m a y be labor i n t e n s i v e . Because the relationships among the processing parameters, microstructure, and resulting material properties and performance are not fully understood, and because the microstructure is difficult to control, reproducibility in these materials is often unsatisfactory. A very promising direction toward overcoming these difficulties involves intelligent processing of materials, a computerbased approach to automatically controlling the evolution of microstructure during processing. In a conventional automated materials p r o c e s s i n g s y s t e m , a u t o m a t i o n involves utilizing sensors to monitor process variables such as temperature and pressure. Data from these sensors are compared with preset values automatically in order to maintain these values with control devices. Nevertheless, the microstructure and properties often experience significant variations. The variations are detected after the fact either by destructive analysis in a quality control laboratory or by nondestructive evaluation (NDE) at the end of the manufacturing process. In contrast, an intelligent processing system utilizes a new class of NDE sensors to characterize the microstructure of the material in real time. Moreover, the real-time data plus data from conventional process variable sensors are transmitted to a computerized decision maker. This computer uses an expert
MRS BULLETIN/APRIL 1988
system to calculate and transmit control signals based on the sensor data, a process model, and process data. Second-generation intelligent processing systems might also utilize artificial intelligence to learn from experience with the process and thereby improve it. T h e s e d i r e c t i o n s are p a r t i c u l a r l y important because U.S. shipments of advanced materials and the products made from them have been valued at about $70 billion this year. The annual world market is estimated to reach $300 billion by the year 2000. There is also a significant U.S. market for conventional materials that can be produced more efficiently by intelligent processing.
This exciting field... combines materials science and engineering with manufacturing practice. Unfortunately, these projections and the opportunities they represent cannot be taken for g r a n t e d . A l t h o u g h the United States is a leading contributor to the world's materials science base, it is beginning to lag in the cost-effective implementation of this knowledge. For example, U.S. industry does not enjoy leadership in introducing new materials technologies in consumer products, as it does in defense products.
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