Conference Reports: WORKSHOP ON INTELLIGENT PROCESSING FOR PRIMARY METALS Gaithersburg, MD August 29–30, 1989

The Materials Science and Engineering Laboratory (MSEL) of the National Institute of Standards and Technology (NIST), the Office of Industrial Programs of the Department of Energy (DOE), and the American Iron and Steel Institute (AISI) co-sponsored a Workshop on Intelligent Processing for Primary Metals held at NIST on August 29-30, 1989. Attendance was by invitation and the more than 80 participants were primarily senior technical staff and managers from steel, aluminum, and copper companies. Although 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. U.S. industry does not enjoy leadership in the introduction of new materials technologies into consumer products, as it does in defense systems. Other nations have initiated government-industry programs aimed at the development of advanced processing technology. Advanced manufacturing techniques increasingly demand materials of greater reliability and uniformity at competitive cost. Specific demands for properties and performance can be met by control of the processing of the material from synthesis or raw material production to forming/finishing. Such process control, or "Intelligent Processing of Materials" (IPM), is based on four elements: a process model that relates specific materials properties at each stage of the processing to the final properties; sensors (measurement technology) which can measure the appropriate materials properties in real-time during processing; materials property data which must be coupled with the realtime measurements in the process model; and rapid computational capability for incorporation of sensor data, process model evaluation, and process variable control into an integrated, automated control strategy. The IPM concept differs greatly from conventional automated materials processing. In conventional practice, only the process variables (temperature, pressure, etc.) are automatically controlled to pre-set values which, nevertheless, still allow the microstructure and properties of the material to deviate significantly from the desired values. A critical feature of intelligent processing is the shift from off-line measurements on finished products to on-line measurements in real-time to control processing. The past 5 years have witnessed extensive advances in the enabling technologies needed for intelligent processing of materials. These include: advanced sensors for on-line monitoring of material and process parameters, the knowledge base and materials characterization techniques to develop process models relating process parameters