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|INTRODUCTION The Control Problem The need for automatic control in flotation plants stems from frequent and randomly occurring disturbances to the feed slurry. Typical disturbances occur in the solids feedrate, the slurry percent sol ids, and the mineralogy and flotability of the gangue and valuable minerals. In plants where semi -autogenous grinding mills (SAG) are used, feedrate changes are very large and changes in feed percent solids of 1m or more are common. Mineralogy changes between valuable minerals are common, as are changes in the host gangue rock. As these changes occur, the operator can attempt to compensate for them by making adjustments to the flotation cell levels, the dosage rates of the collectors and frothers, the pH, and in some cases the aeration rate of the cells. This problem is sometimes complicated by the fact that different sections of the flotation plant will be processing different ore types at the same time. Potential Savings with Control Flotation control brings about savings or plant improvements in two areas; the first is in improved metallurgy and the second is in reagent savings. Improved metallurgy includes increases in the average plant recovery and achieves target concentrate grade level s more consistently. Average recovery increases between 1.0 and 5.0 percentage points have been widely reported (Paakkinen, 1979; Sutherland, 1984). Reagent savings of up to 40 percent have also been reported (Hales, 1985). VARIABLES OF IMPORTANCE Control led, Manipulated, and Disturbance Variables The initial step in the analysis of the flotation control problem is identification of important variables which can affect the efficiency of separation. The efficiency of separation is represented by a group of controlled variables which can quantify the performance of a flotation circuit. This group includes variables such as grade, recovery, tonnage through- put, and circulating loads. The efficiency of separation of a flotation circuit may generally be defined by a grade recovery map, where each point on this map re- presents a set of operating conditions (see Figure 1). However, the combination of operating conditions must be set to operate close to the economic optimum. The group of operating variables which are changed in order to achieve desired circuit performance are called manipulated variables and can be classified into two|