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The global marketplace for materials and services requires providers to continually seek improvements in efficiency to maintain their competitive position. Advanced control systems, such as expert systems, adaptive control and adaptive control with learning capabilities, yield substantial increases in processing efficiency when properly implemented. Read more...

Real-time on-line adaptive control of processing systems is possible when the control algorithms include the ability to build multidimensional response surfaces the represent the processes being controlled. These response surfaces, or knowledgescapes, change in real time as processing conditions, process inputs and system parameters change.

KnowledgeScape® is unique in the world of real-time expert control systems because it is designed to control and optimize industrial processes using an integrated toolset of powerful artificial intelligent components. This integrated toolset contains a flexible expert control system that allows both crisp and fuzzy rules, on-line adaptive and competitive neural network models, and genetic algorithms for real-time optimization of the process. In addition to its use to optimize mineral processing plants it is also designed to embed intelligence into any piece of complex processing equipment. Read more...

While used very successfully in process control for some time in Japan [Fur94] fuzzy logic is
still relatively new in other parts of the world. This paper describes some of the workings of fuzzy logic and demonstrates the basics of a fuzzy SAG mill control system. Read more...

Some of the process variables that are commonly monitored on a thickener are torque, rake height, bed level, bed pressure, feed rate and density, underflow rate and density, settling rate, and overflow turbidity. Many of these are easily measured, while some can be difficult. Combining these signals into a coherent control strategy requires forethought and an understanding of the fundamentals of thickener operation. A wide variety of control strategies have been implemented on thickeners, using various combinations of sensors.

Expert control of grinding and flotation plants has been successfully used in the minerals industry since the 1970’s. Read more...

Since the first experiments with computerized expert control of grinding plants in the early 1970’s expert control has steadily progressed in the minerals industry to be very advanced, including not only many artificial intelligence methodologies but advanced computing and measurement systems. A 1970’s expert system will be compared with the latest systems used in the industry along with performance comparisons. Read more...

Expert control of grinding and flotation plants has been successfully used in the minerals industry since the 1970’s. The earliest of these systems were written in a hard-coded fashion in FORTRAN, BASIC or Pascal. Second generation systems were built using the first experimental expert system shells that were being developed in the artificial intelligence community. Read more...