5. Computer Applications in Hydrometallurgical Processes (Leaching, Extraction, Electrorefining) ? Introduction

The application of computers for control purposes in hydrometallurgical processes is not as well-established as in mineral processing plants. This is not only due to the comparatively new development of large-scale application of hydrometallurgy and the relatively small number of operating plants, but also due to some of the basic dynamic characteristics of hydro- metallurgical processes., Basically there is little difference in the development and application of digital control techniques in hydrometallurgical plants from those techniques widely in use throughout the chemical process industry and in nonslurry applications; particularly for those cases involving liquid streams only, the primary sensing elements are essentially the same. On-stream X-ray fluorescence analysis is a well-established method for determination of metal content in the process streams, and standard equipment is used for the measurement and control of pH, flow, density, temperature, pressure, and other variables. Nevertheless, the high proportion of corrosive slurry streams at elevated temperature and pressure poses a challenge to the instrument engineer concerned with developing long-life, reliable instrumentation. One major difference and potential problem area in developing control systems for hydro- metallurgical processes is related to the very long time constants which are common in the larger plant. In these circumstances, it is important to define the overall control objectives very carefully and be prepared to allow for considerable drift in intermediate variables. In larger projects with many control loops the general advantage of lower costs compared to conventional analog instrumentation can be confidently expected. Also in most cases, the process analysis necessary to design and specify a comprehensive computer control system and the increased operator involvement in implementing digital control systems yield additional benefits due to the increased understanding of the dynamic characteristics of the process.