Calculation of the initial capital is one of the primary requirements in the feasibility study of industrial projects. In this paper a typical processing plant has been designed for the feed capacity of 500 to 8000 tons per day in sixteen different steps. A mathematical model in the form of Y=exp( a+b.Ln(X)) has been devised that calculates the cost of some of the machines used in these different capacity plants. In all these models Y is the capital cost and X is the most important variable in choosing the machinery. The total capital cost of all these different capacity plants have been calculated by adding the construction make, building etc to the results obtained from these models. A mathematical model is then introduced tllat calculates the total initial capital requirement for sixteen different capacity lead and zinc processing plants. The methods adopted and the models introduced could be used in the design process of such plants and to evaluate the feasibility of such project

The tailings come from Chadormalu iron ore processing plant is beneficiated by flotation method. The obtained apatite concentrate is dissolved in acidic media and used to produce phosphoric acid. The chemical analysis shows that the phosphoric acid solution contains 75 ppm of arsenic (As) and 313 ppm of Rare Earth Elements (REE). To identify the source of As and REE, the samples taken from flotation feed (tailings of high intensity magnetic separator), flotation tailings, and apatite concentrate were characterized mineralogically using XRD, XRF, ICP-OES, and scanning electron microscopy (SEM) equipped with EDX and WDX. The results revealed that the concentrate containing 35.6% P2O5 is mainly composed of fluorapatite mineral and a small amount of dolomite and calcite. ICP analysis showed that the As and REE contents in the apatite concentrate are 345 ppm and more than 5000 ppm, respectively. Through the SEM studies, it was identified that some parts of REE have been placed in the fluorapatite lattice as substituting for calcium, and the other part is in the form of monazite minerals with dimensions finer than 20 microns. It was also revealed that As is probably substituted for phosphorus (P) in the lattice structure of fluorapatite and monazite minerals. Thus, it will not be possible to recover REE and As before dissolving the apatite concentrate. Therefore, REE must be recovered firstly from the solution by an appropriate method and then As to be separated from the solution by the precipitation method.

In this research, characterization studies of sedimentary phosphate rock from Zanjan Daleer area with respect to processing are investigated. According to mineralogical studies, phosphate ore (Collophane 28.13%), sedimentary mineral and the predominant constituents of the gangues were Calcite (43.53%), Quartz and Dolomite (4.65%). Main composition of phosphate rock were P2O5 (11.9% wt), CaO (36.36% wt), SiO2 (24.49% wt) and MgO (1.01% wt). Microscopic studies showed that apatite pletts had inclusions of Calcite and Quartz (about 15-70 microns). Content of inclusions was considerable. Mineralogy texture is very complicated. Liberation degree determined by grain counting (with optic microscope) and sink and float test methods. From The results of liberation degree studies can be inferred that in dimension about 140 microns about 96% of phosphate particles librated. In desliming step about 8.2% of total phosphate was removed. Optimum grinding time to reaching liberation of phosphate particles was obtained about 10 min and 30 second. Organic material determined by heating method (about 1.66% wt). Scanning electron microscopy studies showed that inclusions and organic materials existed. Specific gravity of phosphate particles and gangues difference was low. Based on the mentioned studies, effective method for processing of phosphate minerals from carbonate and silicate impurities is suggested flotation method.

In the conventional mass balance methods, sampling are carried out to determine the metal content, solid percentage and particle size distribution in the paths (branches) and ultimately the corresponding errors are dispersed. In these methods, there is no information about the amount of feed and the grade (or the metal content) at any moment of time for each mineral processing unit (plant equipment). Thus, in this paper, the quantitative and qualitative values of input feed to each of the operating units in the processing paths were probabilistically investigated using stochastic process theory, and consequently the load distribution in these units was estimated. For this purpose, the processing plant was firstly modeled as a directional and balanced graph. In this graph, each node represents an operating unit and each edge displays a path between two units. The weight of each edge also indicates the passing material weight from the node to another node, which is assigned as a random variable at a specified interval. After modeling the process, the obtained graphical model containing random parameters was analyzed using Markov chain theory. Applying the philosophy outlined in this paper, not only the load distribution, but also the presence probability of each particle or mineral in each of the operational units of the processing plant can be predicted. It is also possible to estimate the tonnage in each unit when the plant is shut down and even the necessary steps are provided to discharge them. In this research, Chadormalu iron ore processing line was modeled using method presented and the results were analyzed and thereafter were reported using probabilistic parameters.

The impact of installing process control systems can be expected in terms of performance improvements through reduced operating costs. Since these installations impose considerable capital expenditure, the profitability of the new systems should be economically justified. Controlled variable trend was reconstructed by a combination of simple waves, which provided a means to simulate the effect of installing a control system (feedback) by removing disturbance waves with high periods (> one cycle per hour). A method was proposed to evaluate the impact of installing a control system either by a reduction of difference between concentrate target quality and operating quality (i.e., bias reduction) or by reduction of scatter of product quality (i.e., variance reduction). Installing automatic control systems not only reduces operating costs, but also may increase revenue from washed coal sales by maintaining plant performance on designed or desired target. It was found that if an appropriate feedback control system is used at the flotation circuit of the Zarand coal washing plant, the variance of concentrate ash content could be decreased from the current value of 0.38 to 0.06. Based on the predicted metallurgical improvement, the payback time of installing a conventional control system for the flotation circuit of the Zarand plant size with the approximate cost of $1,000,000 was found to be 2 years.