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Mohammad Waqar Ali Asad


The limestone quarry is the major source of raw materials for the cement manufacturing operation. Cement production involves the processing of raw materials that contain - SiO2, Al2O3, Fe2O3, CaO, MgO, LOI (loss of ignition), SO3, K2O, Na2O, TiO2, P2O5, and Cl, etc. However, depending upon the available reserves, some additives such as sandstone, fly ash, iron ore, and clay are also mixed with limestone to achieve proper blend acceptable to the plant. During production stage of a cement quarry, required percent content of chemicals in the raw mix may only be achieved through the analysis of alternative quarry plans with the objective to select the one requiring the fewest purchased additives from the market. One of the managerial objectives of a cement manufacturing operation is to minimize the cost of raw materials by satisfying both quantity and quality requirements. Blending of various raw materials to meet strict quality constraints is the basic requirement to accomplish this objective. A linear programming blending optimization model is presented as a short term planning tool, which addresses the objective and constraints of the cement manufacturing operation. The benefits of the model are established in a case study of an existing cement manufacturing operation in the northern part of Pakistan. This application has not only promised a significant cost saving in the provision of raw materials by satisfying quality constraints but also better coordination and engineering control among various departments.


A Self-tuning Fuzzy PID Control Method of Grate Cooler Pressure Based on Kalman Filter

Zhuo Wang, Mingzhe Yuan


A self-tuning fuzzy PID control method of grate cooler pressure based on Kalman filter was developed to overcome the frequently varying working condition and worse signal-to-noise radio of pressure signals. Based on dynamic simulation and characteristics analysis on clinker cooling system, the system variables were determined, then the control model of grate cooler was obtained by system identification. It was shown that this method could inhibit the influence of noise of pressure signals, could enhanced adaptive capability of controller and could improved heat energy recovery efficiency of grate cooler.


Simplified Modeling of Clinker Cooling Based on Long Term Industrial Data



The purpose of the present study is to develop a simplified dynamical model of clinker cooling process performed in grate coolers. The responses of three different pressures to changes of the speed of the first moving grate are modeled and the dynamical results are compared. The developed algorithm computes not only the average parameters but their uncertainty as well. The distributions of the dynamical parameters deviate significantly from the normal one in the most cases. The described simplified dynamics can be utilized for the effective parameterization of a robust controller regulating the clinker cooling process as well as for the construction of efficient simulators.

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