FIGURE 4.6 Schematic representation of a prototype eddy current sensor for measuring the diameter, electrical conductivity, and temperature of an aluminum rod during extrusion processing. The control system uses sensor-acquired temperature measurements in a feedback loop, performing off-line control of the initial temperature of the billets and online control of the speed of extrusion (itself a heat-generating process). This system will result in improved product quality and reduction of rejected output through in-process temperature and measurement control. (Courtesy National Institute of Standards and Technology.)

enables improved control and/or rejection of bad products at minimum value-added process steps. When coupled with process modeling and elements of artificial intelligence, these sensors promise to usher in a new era of intelligent processing of materials. Developments in this field will require the combined efforts of experts in sensor development, materials modeling, the relationships between process variables and product structure, and artificial intelligence (with a strong emphasis on expert systems). To maximize the impact of such an effort, collaboration between industrial, university, and government laboratories must be achieved at the outset. An expanded effort by funding agencies and national laboratories directed to the intelligent processing of materials could have an immediate impact on the quality of processing of conventional materials and could hasten the introduction of advanced materials. Such an effort would also have the benefit of focusing academic



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