Balance Between Micro- and Macro-Engineering Needs in Processing Research and Education

A mineral or metallurgical process uses various inputs, such as ores, energy and other raw materials, to make different products that fulfill societal needs. The processing of raw materials has changed in recent years due to the increased complexity of processing low-grade ores, intensifying competitiveness and greater constraints. For process improvement, various plant optimization and process modifications must be conducted under environmental, social, political and economic constraints. Processing research and education's success in meeting the process industry's future needs depends on an adequate balance between micro- and macro-engineering approaches. In its simplest form, macro-engineering is concerned with the "big picture," while micro-engineering requires looking at a subset of the process. So macro-engineering may be defined as an investigation of the larger or "whole" system to achieve the desired goals. And micro-engineering may be viewed as a quantitative investigation of a subset of the process, to determine cause-and-effect relationships within the subset. Two different approaches might be used in macro-engineering analysis. In one, the big picture may be viewed without a detailed knowledge of the subunits. With this approach, statistical tools are used to relate input and output parameters. Also, actual plant data or analog models might be used to obtain the desired information. The usefulness of such an approach increases with problem complexity. To attain the desired goals using the second, "model-based," approach, a detailed knowledge of the subunits is often useful and their interactions may be considered. In complex process analysis, the first of these approaches is more useful since less information is needed. However, it is also less exact and more likely to fail if there are significant changes in conditions and interactions. The second approach, on the other hand, is more exact, with greater predictive ability within the narrow subset being considered. Consequently, it is difficult and costly to conduct.