Flotation has promoted a wide scope of research activities ranging from fundamental chemistry and hydrodynamic studies to studies of industrial operations. In general, fundamental studies have been mainly related to ideal situations. In recent years, however, large efforts have been focusing on achieving a better insight into the actual sub-processes provided by the development of new and more sophisticated instrumentation. Since the massive incorporation of flotation columns, around 15 years ago, a renewed interest in flotation fundamental studies, process modelling and new cell designs have been observed worldwide. The key role of the froth has been recognized as an independent and sometimes rate limiting process step. Thus, separation of pulp and froth process stages seems the most appropriate in terms of process modelling, diagnostic, design and scale-up purposes.In relation to Flotation Equipment development, until the middle of the 1970’s, only the sub-aeration mechanical cells were dominant. Since the 1980’s, the use of pneumatic cells and forced air mechanical cells has emerged strongly. Also, in the last decade, flotation equipment has shown a dramatic increase in size, reaching values of 200m3 in unitary mechanical cells and more than 300m3 in columns.

Flotation process modelling is not a simple task, mostly because of the process complexity, i.e. the presence of a large number of variables that (to a lesser or a greater extent) affect the final outcome of the mineral particles separation based on the differences in their surface properties. The attempts toward the development of the quantitative predictive model that would fully describe the operation of an industrial flotation plant started in the middle of past century and it lasts to this day.

Flotation is a complex multifaceted process that is widely used for the separation of finely ground minerals. The theory of froth flotation is complex and is not completely understood. This fact has been brought many monitoring challenges in a coal processing plant. To solve those challenges, it is important to understand the effect of different parameters on the fine particle separation, and control flotation performance for a particular system.

Flotation is flotation equipment. This process is complex and affected by many factors, with the froth depth and reagent dosage being two of the most important and frequently manipulated variables. There is a new method of switching and optimizing control for the coal flotation process. A hybrid model is built and evaluated using industrial data.

Despite significant effort in modelling and simulating flotation circuits, comprehensive model based control and optimisation implementations on industrial circuits remain scarce. the factors preventing more widespread implementation of model-based control and optimisation applications are investigated by focussing on three aspects. Firstly, the critical variables required in a simplified flotation model are identified. Models that are currently used in control, optimisation and supervisory applications are thereafter analysed to determine to what extent the required variables are modelled. Finally, online instrumentation available to support these models are investigated, also including instrumentation that is still under development and not commonly available in commercial applications. Although models used in control applications tend to focus on subsections of the flotation process, there seem to be a good agreement between the required and modelled variables. Model fitting however often relies on extensive sampling campaigns that will need to be repeated regularly to maintain model accuracy. A number of online measurements of sufficient accuracy are still not available to support these models, compromising the long term reliable use of models in online applications.
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